Optimal measurement methods for distributed parameter system identification

Optimal Measurement Methods for Distributed Parameter System Identification

Volumn , Issue , 2004, Pages 1-371

  Uciński, Dariusz ^a  

^a UNIVERSITY OF ZIELONA GÓRA   (Poland)

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[No Author keywords available]

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EID: 85055519558     PISSN: None     EISSN: None     Source Type: Book    
DOI: 10.1201/9780203026786     Document Type: Book

References (357)

1. S. I. Aihara. Consistency of extended least square parameter estimate for stochastic distributed parameter systems. In G. Bastin and M. Gevers, editors, Proc. 4th European Control Conf., Brussels, Belgium, 1–4 July 1997. EUCA, 1997. Published on CD-ROM.
2. M. Amouroux and J. P. Babary. Sensor and control location problems. In M. G. Singh, editor, Systems & Control Encyclopedia. Theory, Technology, Applications, volume 6, pages 4238–4245. Pergamon Press, Oxford, 1988.
3. B. Andó, G. Cammarata, A. Fichera, S. Graziani, and N. Pitrone. A procedure for the optimization of air quality monitoring networks. IEEE Transactions on Systems, Man, and Cybernetics — Part C: Applications and Reviews, 29(1):157–163, Feb. 1999.
4. H. M. Antia. Numerical Methods for Scientists and Engineers. Birkhäuser, Basel, 2nd edition, 2002.
5. M. Armstrong. Basic Linear Geostatistics. Springer-Verlag, Berlin, 1998.
6. K. J. Åström. Introduction to Stochastic Control Theory. Academic Press, New York, 1970.
7. A. C. Atkinson. Optimum experimental designs for parameter estimation and for discrimination between models in the presence of prior information. In V. Fedorov, W. G. Müller, and I. N. Vuchkov, editors, Model Oriented Data-Analysis. A Survey of Recent Methods, Proc. 2nd IIASA Workshop in St. Kyrik, Bulgaria, May 28–June 1 1990, pages 3–30, Heidelberg, 1992. Physica-Verlag.
8. A. C. Atkinson and A. N. Donev. Optimum Experimental Designs. Clarendon Press, Oxford, 1992.
9. A. C. Atkinson and V. V. Fedorov. The design of experiments for discriminating between two rival models. Biometrika, 62(1):57–70, 1975.
10. A. C. Atkinson and V. V. Fedorov. Optimal design: Experiments for discriminating between several models. Biometrika, 62(2):289–303, 1975.
11. V. V. Azhogin, M. Z. Zgurovski, and J. Korbicz. Filtration and Control Methods for Stochastic Distributed-Parameter Processes. Vysha Shkola, Kiev, 1988. (In Russian).
12. A. V. Balakrishnan. Applied Functional Analysis. Springer-Verlag, New York, 2nd edition, 1981.
13. N. V. Banichuk. Introduction to Optimization of Structures. Springer-Verlag, New York, 1990.
14. H. T. Banks. Computational issues in parameter estimation and feedback control problems for partial differential equation systems. Physica D, 60:226–238, 1992.
15. H. T. Banks and B. G. Fitzpatrick. Statistical methods for model comparison in parameter estimation problems for distributed systems. Journal of Mathematical Biology, 28:501–527, 1990.
16. H. T. Banks and K. Kunisch. Estimation Techniques for Distributed Parameter Systems. Systems & Control: Foundations & Applications. Birkhäuser, Boston, 1989.
17. H. T. Banks, R. C. Smith, and Y. Wang. Smart Material Structures: Modeling, Estimation and Control. Research in Applied Mathematics. Masson, Paris, 1996.
18. J. Baumeister, W. Scondo, M. A. Demetriou, and I. G. Rosen. Online parameter estimation for infinite-dimensional dynamical systems. SIAM Journal on Control and Optimization, 35(2):679–713, Mar. 1997.
19. M. B. Beck. Uncertainty, identifiability, and predictability in environmental models. In P. C. Young, editor, Concise Encyclopedia of Environmental Systems, pages 638–644. Pergamon Press, Oxford, 1993.
20. A. F. Bennett. Inverse Methods in Physical Oceanography. Cambridge Monographs on Mechanics and Applied Mathematics. Cambridge University Press, Cambridge, 1992.
21. E. Berger. Asymptotic behaviour of a class of stochastic approximation procedures. Probability Theory and Related Fields, 71:517–552, 1986.
22. D. P. Bertsekas. Nonlinear Programming. Optimization and Computation Series. Athena Scientific, Belmont, MA, 2nd edition, 1999.
23. D. P. Bertsekas and J. N. Tsitsiklis. Introduction to Probability. Athena Scientific, Belmont, MA, 2003.
24. V. D. Blondel and J. N. Tsitsiklis. A survey of computational complexity results in systems and control. Automatica, 36(9):1249–1274, 2000.
25. J. A. Borrie. Stochastic Systems for Engineers. Modelling, Estimation and Control. Prentice Hall, New York, 1992.
26. G. E. P. Box and W. J. Hill. Discrimination among mechanistics models. Technometrics, 9(1):57–71, 1967.
27. S. Boyd, L. El Ghaoui, E. Feron, and V. Balakrishnan. Linear Matrix Inequalities in System and Control Theory. Society for Industrial and Applied Mathematics, Philadelphia, 1994.
28. S. Boyd and L. Vandenberghe. Convex Optimization. Cambridge University Press, Cambridge, 2004.
29. D. W. Brewer. The differentiability with respect to a parameter of the solution of a linear abstract Cauchy problem. SIAM Journal on Mathematical Analysis, 13(4):607–620, July 1982.
30. H. Brezis. Analyse fonctionnelle. Théorie et applications. Mathématiques appliquées pour la maîtrise. Masson, Paris, 1987.
31. U. N. Brimkulov, G. K. Krug, and V. L. Savanov. Design of Experiments in Investigating Random Fields and Processes. Nauka, Moscow, 1986. (In Russian).
32. A. E. Bryson. Applied Linear Optimal Control. Examples and Algorithms. Cambridge University Press, Cambridge, 2002.
33. A. E. Bryson, Jr. Dynamic Optimization. Addison-Wesley, New York, 1999.
34. A. E. Bryson Jr. and Y.-C. Ho. Applied Optimal Control. Optimization, Estimation and Control. Hemisphere Publishing Corp., New York, 2nd edition, 1975.
35. R. L. Burden and J. D. Faires. Numerical Analysis. Prindle, Weber & Schmidt, Boston, 1985.
36. A. L. Burke, T. A. Duever, and A. Pendilis. Model discrimination via designed experiments: Discriminating between the terminal and penultimate models on the basis of composition data. Macromolecules, 27:386–399, 1994.
37. ∞ Methods. Addison-Wesley, Menlo Park, CA, 1999.
38. A. G. Butkovskiy and A. M. Pustyl’nikov. Mobile Control of Distributed Parameter Systems. John Wiley & Sons, New York, 1987.
39. L. Carotenuto, P. Muraca, and G. Raiconi. Optimal location of a moving sensor for the estimation of a distributed-parameter process. International Journal of Control, 46(5):1671–1688, 1987.
40. M. Carter and B. van Brunt. The Lebesgue-Stieltjes Integral. A Practical Introduction. Springer-Verlag, New York, 2000.
41. W. F. Caselton, L. Kan, and J. V. Zidek. Quality data networks that minimize entropy. In A. Walden and P. Guttorp, editors, Statistics in the Environmental and Earth Sciences, chapter 2, pages 10–38. Halsted Press, New York, 1992.
42. W. F. Caselton and J. V. Zidek. Optimal monitoring network design. Statistics & Probability Letters, 2:223–227, 1984.
43. T. K. Chandra. A First Course in Asymptotic Theory of Statistics. Narosa Publishing House, New Delhi, 1999.
44. D.-s. Chang. Design of optimal control for a regression problem. The Annals of Statistics, 7(5):1078–1085, 1979.
45. G. Chavent. Identification of functional parameters in partial differential equations. In R. E. Goodson and M. Polis, editors, Identification of Parameters in Distributed Systems, pages 31–48. The American Society of Mechanical Engineers, New York, 1974.
46. G. Chavent. Distributed parameter systems: Identification. In M. G. Singh, editor, Systems & Control Encyclopedia. Theory, Technology, Applications, volume 2, pages 1193–1197. Pergamon Press, Oxford, 1987.
47. G. Chavent. Identifiability of parameters in the output least square formulation. In É. Walter, editor, Identifiability of Parametric Models, pages 67–74. Pergamon Press, Oxford, 1987.
48. G. Chavent. On the theory and practice of non-linear least-squares. Adv. Water Resources, 14(2):55–63, 1991.
49. W. H. Chen and J. H. Seinfeld. Optimal location of process measurements. International Journal of Control, 21(6):1003–1014, 1975.
50. X. Chen, H. Qi, L. Qi, and K.-l. Teo. Smooth convex approximation to the maximum eigenvalue function. Journal of Global Optimization, 2001. (Submitted for publication).
51. L. H. Chiang, E. L. Russell, and R. D. Braatz. Fault Detection and Diagnosis in Industrial Systems. Springer-Verlag, London, 2001.
52. C.-B. Chung and C. Kravaris. Identification of spatially discontinuous parameters in second-order parabolic systems by piecewise regularisa-tion. Inverse Problems, 4:973–994, 1988.
53. COMSOL AB. Partial Differential Equation Toolbox for Use with Matlab. User’s Guide. The MathWorks, Inc., Natick, MA, 1995.
54. D. Cook and V. Fedorov. Constrained optimization of experimental design. Statistics, 26:129–178, 1995.
55. R. W. Cottle. Manifestations of the Schur complement. Linear Algebra and Its Applications, 8:189–211, 1974.
56. D. R. Cox and N. Reid. The Theory of the Design of Experiments. Chapman and Hall, Boca Raton, FL, 2000.
57. N. A. C. Cressie. Statistics for Spatial Data. John Wiley & Sons, New York, revised edition, 1993.
58. R. F. Curtain and A. J. Pritchard. Functional Analysis in Modern Applied Mathematics. Academic Press, London, 1977.
59. R. F. Curtain and H. Zwart. An Introduction to Infinite-Dimensional Linear Systems Theory. Texts in Applied Mathematics. Springer-Verlag, New York, 1995.
60. R. Daley. Atmospheric Data Analysis. Cambridge University Press, Cambridge, 1991.
61. J. Darlington, C. C. Pantelides, B. Rustem, and B. A. Tanyi. An algorithm for constrained nonlinear optimization under uncertainty. Automatica, 35:217–228, 1999.
62. J. Darlington, C. C. Pantelides, B. Rustem, and B. A. Tanyi. Decreasing the sensitivity of open-loop optimal solutions in decision making under uncertainty. European Journal of Operational Research, 121:343–362, 2000.
63. R. Dautray and J.-L. Lions. Mathematical Analysis and Numerical Methods for Science and Technology, volume 5: Evolution Problems I. Springer-Verlag, Berlin, 1992.
64. N. de Nevers. Air Pollution Control Engineering. McGraw Hill, Boston, 2nd edition, 2000.
65. M. A. Demetriou. Activation policy of smart controllers for flexible structures with multiple actuator/sensor pairs. In A. El Jai and M. Fliess, editors, Proc. 14th Int. Symp. Mathematical Theory of Networks and Systems, Perpignan, France, 19–23 June 2000, 2000. Published on CD-ROM.
66. M. A. Demetriou, A. Paskaleva, O. Vayena, and H. Doumanidis. Scanning actuator guidance scheme in a 1-D thermal manufacturing process. IEEE Transactions on Control Systems Technology, 11(5):757–764, 2003.
67. M. A. Demetriou and I. G. Rosen. On the persistence of excitation in the adaptive estimation of distributed parameter systems. Technical Report 93–4, Center for Applied Mathematical Sciences, University of Southern California, Los Angeles, Mar. 1993.
68. A. Y. Dubovitskii and A. A. Milyutin. Extremum problems in the presence of restrictions. U.S.S.R. Computational Mathematics and Mathematical Physics, 5(3):395–453, 1965. (In Russian).
69. G. E. Dullerud and F. Paganini. A Course in Robust Control Theory. A Convex Approach. Springer-Verlag, New York, 2000.
70. A. Dvoretzky. Stochastic approximation revisited. Advances in Applied Mathematics, 7:220–227, 1986.
71. G. N. Dyubin and V. G. Suzdal. Introduction to Applied Game Theory. Nauka, Moscow, 1981. (In Russian).
72. A. El Jai. Distributed systems analysis via sensors and actuators. Sensors and Actuators A, 29:1–11, 1991.
73. A. El Jai and M. Amouroux, editors. Proceedings of the First International Workshop on Sensors and Actuators in Distributed Parameter Systems, Perpignan, France, 16–18 December 1987, Perpignan, 1987. IFAC.
74. A. El Jai and M. Amouroux. Automatique des systèmes distribués. Hermès, Paris, 1990.
75. A. El Jai and A. J. Pritchard. Sensors and Controls in the Analysis of Distributed Systems. John Wiley & Sons, New York, 1988.
76. Z. Emirsajłow. The Linear Quadratic Control Problem for Infinite Dimensional Systems with Terminal Targets. Technical University Publishers, Szczecin, 1991.
77. S. M. Ermakov, editor. Mathematical Theory of Experimental Design. Nauka, Moscow, 1983. (In Russian).
78. S. M. Ermakov and A. A. Zhigljavsky. Mathematical Theory of Optimal Experiments. Nauka, Moscow, 1987. (In Russian).
79. M. Eslami. Theory of Sensitivity in Dynamic Systems. An Introduction. Springer-Verlag, Berlin, 1994.
80. R. E. Ewing and J. H. George. Identification and control for distributed parameters in porous media flow. In F. Kappel, K. Kunisch, and W. Schappacher, editors, Proc. 2nd Int. Conf. Distributed Parameter Systems, Vorau, Austria, 1984, Lecture Notes in Control and Information Sciences, pages 145–161, Berlin, 1984. Springer-Verlag.
81. R. R. Fedorenko. Approximate Solution of Optimal Control Problems. Nauka, Moscow, 1978. (In Russian).
82. V. V. Fedorov. Theory of Optimal Experiments. Academic Press, New York, 1972.
83. V. V. Fedorov. Optimal design with bounded density: Optimization algorithms of the exchange type. Journal of Statistical Planning and Inference, 22:1–13, 1989.
84. V. V. Fedorov. Design of spatial experiments: Model fitting and prediction. Technical Report TM-13152, Oak Ridge National Laboratory, Oak Ridge, TN, 1996.
85. V. V. Fedorov and P. Hackl. Model-Oriented Design of Experiments. Lecture Notes in Statistics. Springer-Verlag, New York, 1997.
86. V. V. Fedorov and V. Khabarov. Duality of optimal design for model discrimination and parameter estimation. Biometrika, 73(1):183–190, 1986.
87. K. Felsenstein. Optimal Bayesian design for discriminating among rival models. Computational Statistics & Data Analysis, 14:427–436, 1992.
88. B. G. Fitzpatrick. Bayesian analysis in inverse problems. Inverse Problems, 7:675–702, 1991.
89. B. G. Fitzpatrick. Large sample behavior in Bayesian analysis of nonlinear regression models. Journal of Mathematical Analysis and Applications, 192:607–626, 1995.
90. B. G. Fitzpatrick and G. Yin. Empirical distributions in least squares estimation for distributed parameter systems. Journal of Mathematical Systems, Estimation, and Control, 5(1):37–57, 1995.
91. W. H. Fleming and R. W. Rishel. Deterministic and Stochastic Optimal Control. Applications of Mathematics. Springer-Verlag, New York, 1975.
92. I. Ford, D. M. Titterington, and C. P. Kitsos. Recent advances in nonlinear experimental design. Technometrics, 31(1):49–60, 1989.
93. M. Galicki. The planning of robotic optimal motions in the presence of obstacles. The International Journal of Robotics Research, 17(3):248– 259, Mar. 1998.
94. M. Galicki and D. Uciński. Optimal control of robots under constraints on state variables. Studia z Automatyki i Informatyki, 23:95–111, 1998. (In Polish).
95. M. Galicki and D. Uciński. Optimal trajectory planning for many redundant manipulators. In Proc. 6th Nat. Conf. Robotics, Świeradów-Zdrój, 9–12 September 1998, volume 1, pages 171–178, Wrocław, 1998. Technical University Press. (In Polish).
96. M. Galicki and D. Uciński. Time-optimal motions of robotic manipulators. Robotica, 18:659–667, 2000.
97. W. Gander and J. Hřebíček. Solving Problems in Scientific Computing Using MAPLE and MATLAB. Springer-Verlag, Berlin, 1993.
98. J. Gilbert and L. Gilbert. Elements of Modern Algebra. Prindle, Weber & Schmidt, Boston, 1984.
99. M. X. Goemans. Semidefinite programming in combinatorial optimization. Mathematical Programming, 79:143–162, 1997.
100. L. Goldstein. Minimizing noisy functionals in Hilbert space: An extension of the Kiefer-Wolfowitz procedure. Journal of Theoretical Probability, 1(2):189–204, 1988.
101. G. C. Goodwin and R. L. Payne. Dynamic System Identification. Experiment Design and Data Analysis. Mathematics in Science and Engineering. Academic Press, New York, 1977.
102. V. Gopal and L. T. Biegler. Large scale inequality constrained optimization and control. IEEE Control Systems, 18(6):59–68, 1998.
103. P. Grabowski. Lecture Notes on Optimal Control Systems. University of Mining and Metallurgy Publishers, Cracow, 1999.
104. W. H. Greene. Econometric Analysis. Prentice Hall, Upper Saddle River, NJ, 5th edition, 2003.
105. W. A. Gruver and E. Sachs. Algorithmic Methods in Optimal Control. Pitman Publishing Limited, London, 1980.
106. W. W. Hager. Updating the inverse of a matrix. SIAM Review, 31(2):221–239, 1989.
107. L. M. Haines. Optimal design for nonlinear regression models. Communications in Statistics — Theory and Methods, 22(6):1613–1627, 1993.
108. P. W. Hammer. Parameter identification in parabolic partial differential equations using quasilinearization. Journal of Mathematical Systems, Estimation, and Control, 6(3):251–295, 1996.
109. R. F. Hartl, S. P. Sethi, and R. G. Vickson. A survey of the maximum principles for optimal control problems with state constraints. SIAM Review, 37(2):181–218, June 1995.
110. E. J. Haug, K. K. Choi, and V. Komkov. Design Sensitivity Analysis of Structural Systems. Mathematics in Science and Engineering. Academic Press, Orlando, FL, 1986.
111. A. Heck. Introduction to Maple. Springer-Verlag, New York, 2nd edition, 1996.
112. ∞ Methods. Theory, Optimization and Design. Society for Industrial and Applied Mathematics, Philadelphia, 1998.
113. R. Hettich and K. O. Kortanek. Semi-infinite programming: Theory, methods and applications. SIAM Review, 35(3):380–429, 1993.
114. N. G. Hogg. Oceanographic data for parameter estimation. In P. Malanotte-Rizzoli, editor, Modern Approaches to Data Assimilation in Ocean Modeling, Elsevier Oceanography, pages 57–76. Elsevier, Amsterdam, 1996.
115. P. Holnicki, A. Kałuszko, M. Kurowski, R. Ostrowski, and A. Żo-chowski. An urban-scale computer model for short-term prediction of air pollution. Archiwum Automatyki i Telemechaniki, XXXI(1–2):51– 71, 1986.
116. D. Holtz and J. S. Arora. An efficient implementation of adjoint sensitivity analysis for optimal control problems. Structural Optimization, 13:223–229, 1997.
117. A. D. Ioffe and V. M. Tikhomirov. Theory of Extremal Problems. Nauka, Moscow, 1974. (In Russian).
118. V. Isakov. Inverse Problems for Partial Differential Equations. Applied Mathematical Sciences. Springer-Verlag, New York, 1998.
119. M. Z. Jacobson. Fundamentals of Atmospheric Modeling. Cambridge University Press, Cambridge, 1999.
120. J. Jakubowski and R. Sztencel. An Introduction to Probability Theory. SCRIPT, Warsaw, 2000. (In Polish).
121. R. I. Jennrich. Asymptotic properties of non-linear least squares estimators. The Annals of Mathematical Statistics, 40(2):633–643, 1969.
122. C. Johnson. Numerical Solution of Partial Differential Equations by the Finite Element Method. Cambridge University Press, Cambridge, 1987.
123. R. Kalaba and K. Spingarn. Control, Identification and Input Optimization. Plenum Press, New York, 1982.
124. D. C. Kammer. Sensor placement for on-orbit modal identification and correlation of large space structures. In Proc. American Control Conf., San Diego, California, 23–25 May 1990, volume 3, pages 2984–2990, 1990.
125. D. C. Kammer. Effects of noise on sensor placement for on-orbit modal identification of large space structures. Transactions of the ASME, 114:436–443, Sept. 1992.
126. L. V. Kantorovich and G. P. Akilov. Functional Analysis. Nauka, Moscow, 1984. (In Russian).
127. S. Karlin and W. J. Studden. Tchebycheff Systems: With Applications in Analysis and Statistics. John Wiley & Sons, New York, 1966.
128. P. Kazimierczyk. Optimal experiment design; Vibrating beam under random loading. Technical Report 7/1989, Institute of Fundamental Technological Research, Polish Academy of Sciences, Warsaw, 1989.
129. L. G. Khachiyan. A polynomial algorithm for linear programming. Soviet Mathematics Doklady, 20:191–194, 1979.
130. A. Y. Khapalov. Optimal measurement trajectories for distributed parameter systems. Systems & Control Letters, 18(6):467–477, June 1992.
131. A. I. Khuri and J. A. Cornell. Response Surfaces. Design and Analyses. Statistics: Textbooks and Monographs. Marcel Dekker, New York, 2nd edition, 1996.
132. J. Kiefer and J. Wolfowitz. Optimum designs in regression problems. The Annals of Mathematical Statistics, 30:271–294, 1959.
133. J. Klamka. Controllability of Dynamical Systems. Mathematics and Its Applications. Kluwer Academic Publishers, Dordrecht, The Netherlands, 1991.
134. W. Kołodziej. Mathematical Analysis. Polish Scientific Publishers, Warsaw, 1979. (In Polish).
135. J. Korbicz and D. Uciński. Sensors allocation for state and parameter estimation of distributed systems. In W. Gutkowski and J. Bauer, editors, Proc. IUTAM Symposium, Zakopane, Poland, 31 August–3 September 1993, pages 178–189, Berlin, 1994. Springer-Verlag.
136. J. Korbicz, D. Uciński, A. Pieczyński, and G. Marczewska. Knowledge-based fault detection and isolation system for power plant. Applied Mathematics and Computer Science, 3(3):613–630, 1993.
137. J. Korbicz, M. Z. Zgurovsky, and A. N. Novikov. Suboptimal sensors location in the state estimation problem for stochastic non-linear distributed parameter systems. International Journal of Systems Science, 19(9):1871–1882, 1988.
138. J. Korbicz and M. Z. Zgurowski. Estimation and Control of Stochastic Distributed-Parameter Systems. Państwowe Wydawnictwo Naukowe, Warsaw, 1991. (In Polish).
139. K. Kovarik. Numerical Models in Grounwater Pollution. Springer-Verlag, Berlin, 2000.
140. A. Kowalewski. Optimal Control of Infinite Dimensional Distributed Parameter Systems with Delays. University of Mining and Metallurgy Publishers, Cracow, 2001. (In Polish).
141. C. Kravaris and J. H. Seinfeld. Identification of parameters in distributed parameter systems by regularization. SIAM Journal on Control and Optimization, 23(2):217–241, Mar. 1985.
142. A. Królikowski and P. Eykhoff. Input signals design for system identification: A comparative analysis. In Prep. 7-th IFAC/IFORS Symp. Identification and System Parameter Estimation, York, pages 915–920, 1985.
143. M. Krzyśko. Lectures on Probability Theory. Wydawnictwa Naukowo-Techniczne, Warsaw, 2000. (In Polish).
144. C. S. Kubrusly. Distributed parameter system identification: A survey. International Journal of Control, 26(4):509–535, 1977.
145. C. S. Kubrusly and H. Malebranche. Sensors and controllers location in distributed systems — A survey. Automatica, 21(2):117–128, 1985.
146. K. Kunisch. A review of some recent results on the output least squares formulation of parameter estimation problems. Automatica, 24(4):531– 539, 1988.
147. H. J. Kushner and A. Shwartz. Stochastic approximation in Hilbert space: Identification and optimization of linear continuous parameter systems. SIAM Journal on Control and Optimization, 23(5):774–793, Sept. 1985.
148. H. J. Kushner and G. G. Yin. Stochastic Approximation Algorithms and Applications. Applications of Mathematics. Springer-Verlag, New York, 1997.
149. P. K. Lamm. Estimation of discontinuous coefficients in parabolic systems: Applications to reservoir simulation. SIAM Journal on Control and Optimization, 25(1):18–37, Jan. 1987.
150. K. Lange. Numerical Analysis for Statisticians. Springer-Verlag, New York, 1999.
151. I. Lasiecka. Active noise control in an acoustic chamber: Mathematical theory. In S. Domek, R. Kaszyński, and L. Tarasiejski, editors, Proc. 5th Int. Symp. Methods and Models in Automation and Robotics, Międzyzdroje, Poland, 25–29 August 1998, volume 1, pages 13–22, Szczecin, 1998. Wyd. Uczelniane Polit. Szczecińskiej.
152. I. Lasiecka and R. Triggiani. Control Theory for Partial Differential Equations: Continuous and Approximation Theories, volume I and II of Encyclopedia of Mathematics and Its Applications. Cambridge University Press, Cambridge, 2000.
153. H. W. J. Lee, K. L. Teo, and A. E. B. Lim. Sensor scheduling in continuous time. Automatica, 37:2017–2023, 2001.
154. H. W. J. Lee, K. L. Teo, V. Rehbock, and L. S. Jennings. Control parametrization enhancing technique for optimal discrete-valued control problems. Automatica, 35:1401–1407, 1999.
155. A. S. Lewis. Derivatives of spectral functions. Mathematics of Operations Research, 21(3):576–588, 1996.
156. A. S. Lewis. Nonsmooth analysis of eigenvalues. Mathematical Programming, 84:1–24, 1999.
157. A. S. Lewis. The mathematics of eigenvalue optimization. Mathematical Programming, Ser. B 97:155–176, 2003.
158. A. S. Lewis and M. L. Overton. Eigenvalue optimization. Acta Numer-ica, 5:149–190, 1996.
159. LF 95. Lahey/Fujitsu Fortran 95 Language Reference. Revision F. Lahey Computer Systems, Inc., Incline Village, NV, 2000.
160. J.-L. Lions. Contrôle optimal de systèmes gouvernés par des équations aux dérivées partielles. Études mathématiques. Dunod, Paris, 1968.
161. Y. Lou and P. D. Christofides. Optimal actuator/sensor placement for nonlinear control of the Kuramoto-Sivashinsky equation. IEEE Transactions on Control Systems Technology, 11(5):737–745, 2003.
162. B. Lucquin and O. Pironneau. Introduction to Scientific Computing. John Wiley & Sons, Chichester, 1998.
163. D. G. Luenberger. Optimization by Vector Space Methods. John Wiley & Sons, New York, 1969.
164. K. C. P. Machielsen. Numerical Solution of Optimal Control Problems with State Constraints by Sequential Quadratic Programming in Function Space. PhD thesis, Technische Universiteit Eindhoven, Eindhoven, The Netherlands, Mar. 1987.
165. E. B. Magrab. An Engineer’s Guide to Matlab. Prentice Hall, Upper Saddle River, NJ, 2000.
166. P. Malanotte-Rizzoli, editor. Modern Approaches to Data Assimilation in Ocean Modeling. Elsevier Oceanography. Elsevier, Amsterdam, 1996.
167. K. Malanowski, Z. Nahorski, and M. Peszyńska, editors. Modelling and Optimization of Distributed Parameter Systems. International Federation for Information Processing. Kluwer Academic Publishers, Boston, 1996.
168. H. Malebranche. Simultaneous state and parameter estimation and location of sensors for distributed systems. International Journal of Systems Science, 19(8):1387–1405, 1988.
169. K. Malinowski. Issues of hierarchical computations. In R. Wyrzykowski, B. Mochnacki, H. Piech, and J. Szopa, editors, Proc. 3rd Int. Conf. Parallel Processing & Applied Mathematics, Kazimierz Dolny, Poland, 14–17 September 1999, pages 110–120, Czestochowa, 1999.
170. G. I. Marchuk. Methods of Computational Mathematics. Nauka, Moscow, 1989. (In Russian).
171. H. Marcinkowska. Distributions, Sobolev Spaces, Differential Equations. Polish Scientific Publishers, Warsaw, 1993. (In Polish).
172. MathWorks. Using MATLAB. Version 6. The MathWorks, Inc., Natick, MA, 2002.
173. K. Maurin. Analysis. Vol. I: Elements. Mathematical Library. Polish Scientific Publishers, Warsaw, 5th edition, 1991. (In Polish).
174. R. K. Mehra. Optimal input signals for parameter estimation in dynamic systems-survey and new results. IEEE Transactions on Automatic Control, 19(6):753–768, Dec. 1974.
175. R. K. Mehra. Optimization of measurement schedules and sensor designs for linear dynamic systems. IEEE Transactions on Automatic Control, 21(1):55–64, 1976.
176. L. P. Meissner. Essential Fortran 90 & 95. Common Subset Edition. Unicomp, 1997.
177. V. P. Mikhailov. Partial Differential Equations. Nauka, Moscow, 1976. (In Russian).
178. A. J. Miller. Non-linear programming using DONLP2: Fortran 90 version. Code obtainable from http://www.ozemail.com.au/~milleraj/donlp2.html, 1998.
179. W. Mitkowski. Stabilization of Dynamic Systems. Wydawnictwa Naukowo-Techniczne, Warsaw, 1991. (In Polish).
180. K. W. Morton. Numerical Solution of Convection-Diffusion Problems. Chapman & Hall, London, 1996.
181. W. G. Müller. Collecting Spatial Data. Optimum Design of Experiments for Random Fields. Contributions to Statistics. Physica-Verlag, Heidelberg, 2nd revised edition, 2001.
182. W. G. Müller and A. Pázman. Design measures and approximate information matrices for experiments without replications. Journal of Statistical Planning and Inference, 71:349–362, 1998.
183. W. G. Müller and A. Pázman. Measures for designs in experiments with correlated errors. Biometrika, 90(2):423–434, 2003.
184. W. G. Müller and A. C. Ponce de Leon. Discriminating between two binary data models: Sequentially designed experiments. Journal of Statistical Computation and Simulation, 55:87–100, 1996.
185. A. Munack. Optimal sensor allocation for identification of unknown parameters in a bubble-column loop bioreactor. In A. V. Balakrishnan and M. Thoma, editors, Analysis and Optimization of Systems, Part 2, Lecture Notes in Control and Information Sciences, volume 63, pages 415–433. Springer-Verlag, Berlin, 1984.
186. R. E. Munn. The Design of Air Quality Monitoring Networks. Macmillan Publishers Ltd, London, 1981.
187. K. Nakano and S. Sagara. Optimal measurement problem for a stochastic distributed parameter system with movable sensors. International Journal of Systems Science, 12(12):1429–1445, 1981.
188. K. Nakano and S. Sagara. Optimal scanning measurement problem for a stochastic distributed-parameter system. International Journal of Systems Science, 19(7):1069–1083, 1988.
189. W. Näther. Effective Observation of Random Fields. BSB B. G. Teubner Verlagsgesellschaft, Leipzig, 1985.
190. I. M. Navon. Practical and theoretical aspects of adjoint parameter estimation and identifiability in meteorology and oceanography. available at http://www.scri.fsu.edu/~navon/pubs/index.html.
191. P. Neittaanmäki and D. Tiba. Optimal Control of Nonlinear Parabolic Systems. Theory, Algorithms, and Applications. Monographs and Textbooks in Pure and Applied Mathematics. Marcel Dekker, Inc., New York, 1994.
192. R. Nixdorf. An invariance principle for a finite dimensional stochastic approximation method in a Hilbert space. Journal of Multivariate Analysis, 15:252–260, 1984.
193. M. Nørgaard, O. Ravn, N. K. Poulsen, and L. K. Hansen. Neural Networks for Modelling and Control of Dynamic Systems. A Practi-tioner’s Handbook. Advanced Textbooks in Control and Signal Processing. Springer-Verlag, London, 2000.
194. D. Nychka, W. W. Piegorsch, and L. H. Cox, editors. Case Studies in Environmental Statistics. Lecture Notes in Statistics, volume 132. Springer-Verlag, New York, 1998.
195. D. Nychka and N. Saltzman. Design of air-quality monitoring networks. In D. Nychka, W. W. Piegorsch, and L. H. Cox, editors, Case Studies in Environmental Statistics, Lecture Notes in Statistics, volume 132, pages 51–76. Springer-Verlag, New York, 1998.
196. T. E. O’Brien and J. O. Rawlings. A nonsequential design procedure for parameter estimation and model discrimination in nonlinear regression models. Journal of Statistical Planning and Inference, 55:77–93, 1996.
197. D. Y. Oh and H. C. No. Determination of the minimal number and optimal sensor location in a nuclear system with fixed incore detectors. Nuclear Engineering and Design, 152:197–212, 1994.
198. S. Omatu and K. Matumoto. Distributed parameter identification by regularization and its application to prediction of air pollution. International Journal of Systems Science, 22(10):2001–2012, 1991.
199. S. Omatu and K. Matumoto. Parameter identification for distributed systems and its application to air pollution estimation. International Journal of Systems Science, 22(10):1993–2000, 1991.
200. S. Omatu and J. H. Seinfeld. Distributed Parameter Systems: Theory and Applications. Oxford Mathematical Monographs. Oxford University Press, New York, 1989.
201. M. L. Overton. Large-scale optimization of eigenvalues. SIAM Journal on Control and Optimization, 2(1):88–120, 1992.
202. P. Y. Papalambros and D. J. Wilde. Principles of Optimal Design. Modeling and Computation. Cambridge University Press, Cambridge, 2nd edition, 2000.
203. A. Papoulis. Probability, Random Variables, and Stochastic Processes. McGraw Hill, New York, 3rd edition, 1991.
204. E. Parzen. An approach to time series analysis. The Annals of Mathematical Statistics, 32(4):951–989, 1961.
205. E. Parzen. Stochastic Processes. Holden-Day, San Francisco, 1962.
206. M. Patan. Optimal Observation Strategies for Parameter Estimation of Distributed Systems. PhD thesis, University of Zielona Góra, Zielona Góra, Poland, 2004.
207. V. V. Patel, G. Deodhare, and T. Viswanath. Some applications of randomized algorithms for control system design. Automatica, 38:2085– 2092, 2002.
208. A. Pázman. Foundations of Optimum Experimental Design. Mathematics and Its Applications. D. Reidel Publishing Company, Dordrecht, The Netherlands, 1986.
209. A. Pázman and W. G. Müller. Optimal design of experiments subject to correlated errors. Statistics & Probability Letters, 52:29–34, 2001.
210. G. C. Pflug. Optimization of Stochastic Models. The Interface Between Simulation and Optimization. Engineering and Computer Science: Discrete Event Dynamic Systems. Kluwer Academic Publishers, Boston, 1996.
211. G. A. Phillipson. Identification of Distributed Systems. Modern Analytic and Computational Methods in Science and Mathematics. Elsevier, New York, 1971.
212. D. A. Pierre. Optimization Theory with Applications. Series in Decision and Control. John Wiley & Sons, New York, 1969.
213. N. Point, A. Vande Wouwer, and M. Remy. Practical issues in distributed parameter estimation: Gradient computation and optimal experiment design. Control Engineering Practice, 4(11):1553–1562, 1996.
214. E. Polak. On the mathematical foundations of nondifferentiable optimization in engineering design. SIAM Review, 29(1):21–89, 1987.
215. E. Polak. Optimization. Algorithms and Consistent Approximations. Applied Mathematical Sciences. Springer-Verlag, New York, 1997.
216. M. P. Polis. The distributed system parameter identification problem: A survey of recent results. In Proc. 3rd IFAC Symp. Control of Distributed Parameter Systems, Toulouse, France, pages 45–58, 1982.
217. A. C. Ponce de Leon and A. C. Atkinson. Optimum experimental design for discriminating between two rival models in the presence of prior information. Biometrika, 78(3):601–608, 1991.
218. W. H. Press, S. A. Teukolsky, W. T. Vetterling, and B. P. Flannery. Numerical Recipes in FORTRAN. The Art of Parallel Scientific Computing. Cambridge University Press, Cambridge, 2nd edition, 1992.
219. W. H. Press, S. A. Teukolsky, W. T. Vetterling, and B. P. Flannery. Numerical Recipes in Fortran 90. The Art of Parallel Scientific Computing. Cambridge University Press, Cambridge, 2nd edition, 1996.
220. L. Pronzato. Removing non-optimal support points in D-optimum design algorithms. Statistics & Probability Letters, 63:223–228, 2003.
221. L. Pronzato and É. Walter. Robust experiment design via stochastic approximation. Mathematical Biosciences, 75:103–120, 1985.
222. L. Pronzato and É. Walter. Robust experiment design via maximin optimization. Mathematical Biosciences, 89:161–176, 1988.
223. B. N. Pshenichnyi. Necessary Conditions for an Extremum. Marcel Dekker, Inc., New York, 1971.
224. F. Pukelsheim. Optimal Design of Experiments. Probability and Mathematical Statistics. John Wiley & Sons, New York, 1993.
225. F. Pukelsheim and S. Rieder. Efficient rounding of approximate designs. Biometrika, 79(4):763–770, 1992.
226. F. Pukelsheim and A. Wilhelm. A contribution to the discussion of the paper “ Constrained optimization of experimental design” by D. Cook and V. Fedorov. Statistics, 26:168–172, 1995.
227. R. Pytlak. Numerical Methods for Optimal Control Problems with State Constraints. Springer-Verlag, Berlin, 1999.
228. R. Pytlak and R. B. Vinter. A feasible directions algorithm for optimal control problems with state and control constraints: Convergence analysis. SIAM Journal on Control and Optimization, 36:1999–2019, 1998.
229. R. Pytlak and R. B. Vinter. Feasible direction algorithm for optimal control problems with state and control constraints: Implementation. Journal of Optimization Theory and Applications, 101(3):623–649, June 1999.
230. A. Quarteroni, R. Sacco, and F. Saleri. Numerical Mathematics. Springer-Verlag, New York, 2000.
231. Z. H. Quereshi, T. S. Ng, and G. C. Goodwin. Optimum experimental design for identification of distributed parameter systems. International Journal of Control, 31(1):21–29, 1980.
232. E. Rafajłowicz. Design of experiments for parameter identification of the static distributed systems. Systems Science, 4(4):349–361, 1978.
233. E. Rafajłowicz. Design of experiments for eigenvalue identification in distributed-parameter systems. International Journal of Control, 34(6):1079–1094, 1981.
234. E. Rafajłowicz. Optimal experiment design for identification of linear distributed-parameter systems: Frequency domain approach. IEEE Transactions on Automatic Control, 28(7):806–808, July 1983.
235. E. Rafajłowicz. Optimization of actuators for distributed parameter systems identification. Problems of Control and Information Theory, 13(1):39–51, 1984.
236. E. Rafajłowicz. Adaptive input sequence design for linear distributed-parameter systems identification. Large Scale Systems, 11:43–58, 1986.
237. E. Rafajłowicz. Choice of Optimum Input Signals in Linear Distributed-Parameter Systems Identification. Monographs. Technical University Press, Wrocław, 1986. (In Polish).
238. E. Rafajłowicz. Optimum choice of moving sensor trajectories for distributed parameter system identification. International Journal of Control, 43(5):1441–1451, 1986.
239. E. Rafajłowicz. Information equivalence of sensors-controllers configurations in identification of homogeneous static distributed systems. In Y. Sunahara, S. G. Tzafestas, and T. Futagami, editors, Proc. IMACS/IFAC Int. Symp. Modelling and Simulation of Distributed Parameter Systems, Hiroshima, Japan, 6–9 October 1987, pages 553–557, 1987.
240. E. Rafajłowicz. Distributed parameter systems analysis by tracking stationary points of their states. International Journal of Systems Science, 19(4):613–620, 1988.
241. E. Rafajłowicz. Reduction of distributed system identification complexity using intelligent sensors. International Journal of Control, 50(5):1571–1576, 1989.
242. E. Rafajłowicz. Time-domain optimization of input signals for distributed-parameter systems identification. Journal of Optimization Theory and Applications, 60(1):67–79, 1989.
243. E. Rafajłowicz. Optimum input signals for parameter estimation in systems described by linear integral equations. Computational Statistics & Data Analysis, 9:11–19, 1990.
244. E. Rafajłowicz. Optimal measurement schedules and sensors’ location for estimating intensities of random sources. In S. Bańka, S. Domek, and Z. Emirsajłow, editors, Proc. 2nd Int. Symp. Methods and Models in Automation and Robotics, Międzyzdroje, Poland, 30 August–2 September 1995, volume 1, pages 169–174, Szczecin, 1995. Wyd. Uczelniane Polit. Szczecińskiej.
245. E. Rafajłowicz. Algorithms of Experimental Design with Implementations in MATHEMATICA. Akademicka Oficyna Wydawnicza PLJ, Warsaw, 1996. (In Polish).
246. E. Rafajłowicz. Selective random search for optimal experiment designs. In A. C. Atkinson, L. Pronzato, and H. P. Wynn, editors, MODA 5 — Advances in Model-Oriented Data Analysis and Experimental Design: Proc. 5th Int. Workshop in Marseilles, France, June 22–26 1998, Contributions to Statistics, chapter 9, pages 75–83. Physica-Verlag, Heidelberg, 1998.
247. E. Rafajłowicz and W. Myszka. Computational algorithm for input-signal optimization in distributed-parameter systems identification. International Journal of Systems Science, 17(6):911–924, 1986.
248. M. M. Rao. Measure Theory and Integration. John Wiley & Sons, New York, 1987.
249. P. A. Raviart and J.-M. Thomas. Introduction à l’analyse numérique des équations aux dérivées partielles. Mathématiques appliquées pour la maîtrise. Masson, Paris, 1992.
250. R. Reemtsen and S. Görner. Numerical methods for semi-infinite programming: A survey. In R. Reemtsen and J.-J. Rückmann, editors, Semi-Infinite Programming, pages 195–275. Kluwer Academic Publishers, Boston, 1998.
251. H. Reinhard. Équations aux dérivées partielles. Introduction. Dunod, Paris, 1991.
252. M. Renardy and R. C. Rogers. An Introduction to Partial Differential Equations. Texts in Applied Mathematics. Springer-Verlag, New York, 1993.
253. P. Révész. Robbins-Monro procedure in a Hilbert space and its application in the theory of learning processes I. Studia Scientiarum Mathematicarum Hungarica, 8:391–398, 1973.
254. P. Révész. Robbins-Monro procedure in a Hilbert space II. Studia Scientiarum Mathematicarum Hungarica, 8:469–472, 1973.
255. R. T. Rockafellar. Convex Analysis. Princeton University Press, Princeton, 1970.
256. S. Rolewicz. Functional Analysis and Control Theory. Polish Scientific Publishers, Warsaw, 1974. (In Polish).
257. E. W. Sacks. Semi-infinite programming in control. In R. Reemtsen and J.-J. Rückmann, editors, Semi-Infinite Programming, pages 389– 411. Kluwer Academic Publishers, Boston, 1998.
258. J. Sacks and D. Ylvisaker. Designs for regression problems with correlated errors. The Annals of Mathematical Statistics, 37(1):66–89, 1966.
259. J. Sacks and D. Ylvisaker. Designs for regression problems with correlated errors: Many parameters. The Annals of Mathematical Statistics, 39(1):49–69, 1968.
260. J. Sacks and D. Ylvisaker. Designs for regression problems with correlated errors III. The Annals of Mathematical Statistics, 41(6):2057– 2074, 1970.
261. M. Sahm and R. Schwabe. A note on optimal bounded designs. In A. Atkinson, B. Bogacka, and A. Zhigljavsky, editors, Optimum Design 2000, chapter 13, pages 131–140. Kluwer Academic Publishers, Dordrecht, The Netherlands, 2001.
262. K. Schittkowski. Numerical Data Fitting in Dynamical Systems — A Practical Introduction with Applications and Software. Kluwer Academic Publishers, Dordrecht, The Netherlands, 2002.
263. R. Schwabe. Optimum Designs for Multi-Factor Models. Springer-Verlag, New York, 1996.
264. A. L. Schwartz. Theory and Implementation of Numerical Methods Based on Runge-Kutta Integration for Solving Optimal Control Problems. PhD thesis, University of California, Berkeley, 1996.
265. G. A. F. Seber and C. J. Wild. Nonlinear Regression. John Wiley & Sons, New York, 1989.
266. K. Shimizu and E. Aiyoshi. Necessary conditions for min-max problems and algorithms by a relaxation procedure. IEEE Transactions on Automatic Control, AC-25(1):62–66, 1980.
267. A. Shwartz and N. Berman. Abstract stochastic approximations and applications. Stochastic Processes and their Applications, 31:133–149, 1989.
268. J. Sikora. Numerical Approaches to the Impedance and Eddy-Current Tomographies. Technical University Press, Warsaw, 2000. (In Polish).
269. S. D. Silvey. Optimal Design. An Introduction to the Theory for Parameter Estimation. Chapman and Hall, London, 1980.
270. S. D. Silvey, D. M. Titterington, and B. Torsney. An algorithm for optimal designs on a finite design space. Communications in Statistics — Theory and Methods, 14:1379–1389, 1978.
271. S. Simons. Minimax theorems. In C. A. Floudas and P. M. Pardalos, editors, Encyclopedia of Optimization, volume 3, pages 284–289. Kluwer Academic Publishers, Dordrecht, The Netherlands, 2001.
272. E. Skubalska-Rafajłowicz and E. Rafajłowicz. Searching for optimal experimental designs using space-filling curves. Applied Mathematics and Computer Science, 8(3):647–656, 1998.
273. J. Sokołowski and J.-P. Zolesio. Introduction to Shape Optimization: Shape Sensitivity Analysis. Computational Mathematics. Springer-Verlag, Berlin, 1992.
274. J. C. Spall. Introduction to Stochastic Search and Optimization. Estimation, Simulation, and Control. John Wiley & Sons, Hoboken, NJ, 2003.
275. P. Spellucci. A new technique for inconsistent QP problems in the SQP method. Mathematical Methods of Operations Research, 47:355–400, 1998.
276. P. Spellucci. An SQP method for general nonlinear programs using only equality constrained subproblems. Mathematical Programming, 82:413– 448, 1998.
277. M. C. Spruill and W. J. Studden. A Kiefer-Wolfowitz theorem in a stochastic process setting. The Annals of Statistics, 7(6):1329–1332, 1979.
278. R. C. St. John and N. R. Draper. D-optimality for regression designs: A review. Technometrics, 17(1):15–23, 1975.
279. W. E. Stewart, Y. Shon, and G. E. P. Box. Discrimination and goodness of fit of multiresponse mechanistic models. AIChE Journal, 44(6):1404– 1412, 1998.
280. J. F. Sturm. Primal-Dual Interior Point Approach to Semidefinite Programming. PhD thesis, Erasmus University, Rotterdam, 1997. Tinbergen Institute Series 156.
281. P. J. Sturm, R. A. Almbauer, and R. Kunz. Air quality study for the city of Graz, Austria. In H. Power, N. Moussiopoulos, and C. A. Brebbia, editors, Urban Air Pollution, Vol. 1, chapter 2, pages 43–100. Computational Mechanics Publications, Southampton, 1994.
282. N.-Z. Sun. Inverse Problems in Groundwater Modeling. Theory and Applications of Transport in Porous Media. Kluwer Academic Publishers, Dordrecht, The Netherlands, 1994.
283. N.-Z. Sun. Mathematical Modeling of Groundwater Pollution. Springer-Verlag, New York, 1996.
284. A. Sydow, T. Lux, P. Mieth, M. Schmidt, and S. Unger. The DYMOS model system for the analysis and simulation of regional air pollution. In R. Grützner, editor, Modellierung und Simulation im Umweltbereich, pages 209–219. Vieweg-Verlag, Wiesbaden, 1997.
285. A. Sydow, T. Lux, H. Rosé, W. Rufeger, and B. Walter. Conceptual design of the branch-oriented simulation system DYMOS (dynamic models for smog analysis). Transactions of the Society for Computer Simulation International, 15(3):95–100, 1998.
286. T. Szántai. Approximation of multivariate probability integrals. In C. A. Floudas and P. M. Pardalos, editors, Encyclopedia of Optimization, volume 1, pages 53–59. Kluwer Academic Publishers, Dordrecht, The Netherlands, 2001.
287. J. C. Taylor. An Introduction to Measure and Probability. Springer-Verlag, New York, 1997.
288. R. Tempo, E. W. Bai, and F. Dabbene. Probabilistic robustness analysis: Explicit bounds for the minimum number of samples. Systems & Control Letters, 30:237–242, 1997.
289. R. Tempo and F. Dabbene. Probabilistic robustness analysis and design of uncertain systems. In G. Picci and D. S. Gilliam, editors, Dynamical Systems, Control, Coding, Computer Vision. New Trends, Interfaces, and Interplay, Progress in Systems and Control Theory, pages 263–282. Birkhäuser, Basel, 1999.
290. K. L. Teo and Z. S. Wu. Computational Methods for Optimizing Distributed Systems. Academic Press, Orlando, FL, 1984.
291. A. N. Tikhonov and V. Y. Arsenin. Solutions of Ill-Posed Problems. John Wiley & Sons, New York, 1977.
292. D. M. Titterington. Aspects of optimal design in dynamic systems. Technometrics, 22(3):287–299, 1980.
293. C. Tocci and S. Adams. Applied Maple for Engineers and Scientists. Artech House, Boston, 1996.
294. B. Torsney. Computing optimising distributions with applications in design, estimation and image processing. In Y. Dodge, V. V. Fedorov, and H. P. Wynn, editors, Optimal Design and Analysis of Experiments, pages 316–370. Elsevier, Amsterdam, 1988.
295. B. Torsney and S. Mandal. Construction of constrained optimal designs. In A. Atkinson, B. Bogacka, and A. Zhigljavsky, editors, Optimum Design 2000, chapter 14, pages 141–152. Kluwer Academic Publishers, Dordrecht, The Netherlands, 2001.
296. D. A. Tortorelli and P. Michaleris. Design sensitivity analysis: Overview and review. Inverse Problems in Engineering, 1(1):71–105, 1994.
297. 2-distance projection onto the canonical simplex: A simple algorithm. Algo Research Quarterly, pages 53–56, Dec. 2001.
298. D. Uciński. Optimal sensor location for parameter identification of distributed systems. Applied Mathematics and Computer Science, 2(1):119–134, 1992.
299. D. Uciński. Optimal design of moving sensors trajectories for identification of distributed parameter systems. In Proc. 1st Int. Symp. Methods and Models in Automation and Robotics, Międzyzdroje, Poland, 1–3 September 1994, volume 1, pages 304–309, Szczecin, 1994. Wyd. Uczelniane Polit. Szczecińskiej.
300. D. Uciński. Optimal selection of measurement locations for identification of parameters in distributed systems. In S. Bańka, S. Domek, and Z. Emirsajłow, editors, Proc. 2nd Int. Symp. Methods and Models in Automation and Robotics, Międzyzdroje, Poland, 30 August–2 September 1995, volume 1, pages 175–180, Szczecin, 1995. Wyd. Uczelniane Polit. Szczecińskiej.
301. D. Uciński. Optimal planning of moving sensor trajectories in parameter estimation of distributed systems. In Proc. 6th Nat. Conf. Robotics, Świeradów-Zdrój, 24–26 September 1996, volume 1, pages 225–233, Wrocław, 1996. Technical University Press. (In Polish).
302. D. Uciński. Optimal planning of sensor movements along given paths for distributed parameter systems identification. In Proc. 3rd Int. Symp. Methods and Models in Automation and Robotics, Międzyzdroje, Poland, 10–13 September 1996, volume 1, pages 187–192, Szczecin, 1996. Wyd. Uczelniane Polit. Szczecińskiej.
303. D. Uciński. Measurement optimization with moving sensors for parameter estimation of distributed systems. In A. Sydow, editor, Proc. 15th IMACS World Congress on Scientific Computation, Modelling and Applied Mathematics, Berlin, Germany, August 1997, volume 5, pages 191–196, Berlin, 1997. Wissenschaft & Technik Verlag.
304. D. Uciński. Optimal location of scanning sensors for parameter identification of distributed systems from noisy experimental data. In P. S. Szczepaniak, editor, Proc. 9th Int. Symp. System-Modelling-Control, Zakopane, Poland, 27 April–1 May 1998, 1998. Published on CD-ROM.
305. D. Uciński. A robust approach to the design of optimal trajectories of moving sensors for distributed-parameter systems identification. In A. Beghi, L. Finesso, and G. Picci, editors, Proc. 13th Int. Symp. Mathematical Theory of Networks and Systems, Padova, Italy, 6–10 July 1998, pages 551–554, Padova, 1998. Il Poligrafo.
306. D. Uciński. Towards a robust-design approach to optimal location of moving sensors in parameter identification of DPS. In S. Domek, R. Kaszyński, and L. Tarasiejski, editors, Proc. 5th Int. Symp. Methods and Models in Automation and Robotics, Międzyzdroje, Poland, 25–29 August 1998, volume 1, pages 85–90, Szczecin, 1998. Wyd. Uczelniane Polit. Szczecińskiej.
307. D. Uciński. Optimum design of sensor locations in parameter estimation of distributed systems. Studia z Automatyki i Informatyki, 24:151–167, 1999. (In Polish).
308. D. Uciński. Robust design of sensor locations in parameter estimation of distributed systems. In Z. Bubnicki and J. Józefczyk, editors, Proc. 13th Nat. Conf. Automatics, Opole, Poland, 21–24 September 1999, volume 1, pages 289–292, 1999. (In Polish).
309. D. Uciński. A technique of robust sensor allocation for parameter estimation in distributed systems. In P. M. Frank, editor, Proc. 5th European Control Conf., Karlsruhe, Germany, 31 August–3 September 1999. EUCA, 1999. Published on CD-ROM.
310. D. Uciński. Optimal sensor location for parameter estimation of distributed processes. International Journal of Control, 73(13):1235–1248, 2000.
311. D. Uciński. Optimization of sensors’ allocation strategies for parameter estimation in distributed systems. Systems Analysis — Modelling — Simulation, 37:243–260, 2000.
312. D. Uciński. Sensor motion planning with design criteria in output space. In A. C. Atkinson, P. Hackl, and W. Müller, editors, mODa 6, Proc. 6th Int. Workshop on Model-Oriented Data Analysis, Puchberg/Schneeberg, Austria, 2001, pages 235–242, Heidelberg, 2001. Physica-Verlag.
313. D. Uciński and A. C. Atkinson. Experimental design for time-dependent models with correlated observations. Studies in Nonlinear Dynamics & Econometrics, 8(2), 2004. Article No. 13.
314. D. Uciński and B. Bogacka. T-optimum design for discrimination between two multivariate dynamic models. Journal of the Royal Statistical Society: Series B (Statistical Methodology), 2004. (Accepted for publi-cation).
315. D. Uciński and B. Bogacka. T-optimum designs for multiresponse dynamic heteroscedastic models. In A. Di Bucchianico, H. Läuter, and H. P. Wynn, editors, mODa 7, Proc. 7th Int. Workshop on Model-Oriented Data Analysis, Heeze, The Netherlands, 2004, pages 191–199, Heidelberg, 2004. Physica-Verlag.
316. D. Uciński and M. A. Demetriou. An approach to the optimal scanning measurement problem using optimum experimental design. In Proc. American Control Conference, Boston, MA, 2004. Published on CD-ROM.
317. D. Uciński and A. El Jai. On weak spreadability of distributed-parameter systems and its achievement via linear-quadratic control techniques. IMA Journal of Mathematical Control and Information, 14:153–174, 1997.
318. D. Uciński and S. El Yacoubi. Modelling and simulation of an ecological problem by means of cellular automata. In S. Domek, R. Kaszyński, and L. Tarasiejski, editors, Proc. 5th Int. Symp. Methods and Models in Automation and Robotics, Międzyzdroje, Poland, 25–29 August 1998, volume 1, pages 289–293, Szczecin, 1998. Wyd. Uczelniane Polit. Szczecińskiej.
319. D. Uciński and S. El Yacoubi. Parameter estimation of cellular automata models. In R. Wyrzykowski, B. Mochnacki, H. Piech, and J. Szopa, editors, Proc. 3rd Int. Conf. Parallel Processing & Applied Mathematics, Kazimierz Dolny, Poland, 14–17 September 1999, pages 168–176, Częstochowa, 1999.
320. D. Uciński and J. Korbicz. Parameter identification of two-dimensional distributed systems. International Journal of Systems Science, 21(2):2441–2456, 1990.
321. D. Uciński and J. Korbicz. An algorithm for the computation of optimal measurement trajectories in distributed parameter systems iden-tification. In A. Isidori, S. Bittanti, E. Mosca, A. D. Luca, M. D. Di Benedetto, and G. Oriolo, editors, Proc. 3rd European Control Conf., Roma, Italy, 5–8 September 1995, volume 2, pages 1267–1272. EUCA, 1995.
322. D. Uciński and J. Korbicz. Optimal location of movable sensors for distributed-parameter system identification. In P. Borne, M. Staroswiecki, J. P. Cassar, and S. El Khattabi, editors, Proc. Symp. Control, Optimization and Supervision of 1st IMACS Int. Multiconf. CESA’96, Lille, France, 9–12 July 1996, volume 2, pages 1004–1009, 1996.
323. D. Uciński and J. Korbicz. Measurement optimization with minimax criteria for parameter estimation in distributed systems. In G. Bastin and M. Gevers, editors, Proc. 4rd European Control Conf., Brussels, Belgium, 1–4 July 1997. EUCA, 1997. Published on CD-ROM.
324. D. Uciński and J. Korbicz. Optimization of sensors’ allocation strategies for parameter estimation in distributed systems. In P. Borne, M. Ksouri, and A. El Kamel, editors, Proc. Symp. Modeling, Analysis and Control of 2nd IMACS Int. Multiconf. CESA’98, Nabeul-Hammamet, Tunisia, 1–4 April 1998, volume 1, pages 128–133, 1998.
325. D. Uciński and J. Korbicz. On robust design of sensor trajectories for parameter estimation of distributed systems. In Proc. 14th IFAC World Congress, Beijing, China, 5–9 July 1999, volume H: Modeling, Identification, Signal Processing I, pages 73–78, 1999.
326. D. Uciński and J. Korbicz. Path planning for moving sensors in parameter estimation of distributed systems. In Proc. 1st Workshop on Robot Motion and Control RoMoCo’99, Kiekrz, Poland, 28–29 June, 1999, pages 273–278, 1999.
327. D. Uciński and J. Korbicz. Optimal sensor allocation for parameter estimation in distributed systems. Journal of Inverse and Ill-Posed Problems, 9(3):301–317, 2001.
328. D. Uciński, J. Korbicz, and M. B. Zaremba. On optimization of sensors motions in parameter identification of two-dimensional distributed systems. In J. W. Neuwenhuis, C. Praagman, and H. L. Trentelman, editors, Proc. 2nd European Control Conf., Groningen, The Netherlands, 28 June–1 July 1993, volume 3, pages 1359–1364. ECCA, 1993.
329. D. Uciński and M. Patan. Optimal location of discrete scanning sensors for parameter estimation of distributed systems. In Proc. 15th IFAC World Congress, Barcelona, Spain, 22–26 July 2002, 2002. Published on CD-ROM.
330. M. van de Wal and B. de Jager. A review of methods for input/output selection. Automatica, 37:487–510, 2001.
331. M. van Loon. Numerical smog prediction, I: The physical and chemical model. Technical Report NM-R9411, Centrum voor Wiskunde en Informatica, Amsterdam, 1994.
332. M. van Loon. Numerical smog prediction, II: Grid refinement and its application to the Dutch smog prediction model. Technical Report NM-R9523, Centrum voor Wiskunde en Informatica, Amsterdam, 1995.
333. A. Vande Wouwer, N. Point, S. Porteman, and M. Remy. On a practical criterion for optimal sensor configuration — Application to a fixed-bed reactor. In Proc. 14th IFAC World Congress, Beijing, China, 5–9 July, 1999, volume I: Modeling, Identification, Signal Processing II, Adaptive Control, pages 37–42, 1999.
334. L. Vandenberghe and S. Boyd. Semidefinite programming. SIAM Review, 38(1):49–95, 1996.
335. L. Vandenberghe and S. Boyd. Connections between semi-infinite and semidefinite programming. In R. Reemtsen and J.-J. Rückmann, editors, Semi-Infinite Programming, pages 277–294. Kluwer Academic Publishers, Boston, 1998.
336. L. Vandenberghe and S. Boyd. Applications of semidefinite programming. Applied Numerical Mathematics, 29:283–299, 1999.
337. L. Vandenberghe, S. Boyd, and S.-P. Wu. Determinant maximization with linear matrix inequality constraints. SIAM Journal on Matrix Analysis and Applications, 19(2):499–533, 1998.
338. A. Venot, L. Pronzato, É. Walter, and J.-F. Lebruchec. A distribution-free criterion for robust identification, with applications in system modelling and image processing. Automatica, 22(1):105–109, 1986.
339. A. D. Ventzel. A Course on the Theory of Stochastic Processes. Nauka, Moscow, 1975. (In Russian).
340. M. Vidyasagar. A Theory of Learning and Generalization with Applications to Neural Networks and Control Systems. Springer-Verlag, London, 1997.
341. M. Vidyasagar. An introduction to some statistical aspects of PAC learning theory. Systems & Control Letters, 34:115–124, 1998.
342. M. Vidyasagar. Statistical learning theory and randomized algorithms for control. IEEE Control Systems, 18(6):69–85, Dec. 1998.
343. M. Vidyasagar. Randomized algorithms for robust controller synthesis using statistical learning theory. Automatica, 37:1515–1528, 2001.
344. G. Wahba. On the regression design problem of Sacks and Ylvisaker. The Annals of Mathematical Statistics, 42(3):1035–1053, 1971.
345. G. Wahba. Parameter estimation in linear dynamic systems. IEEE Transactions on Automatic Control, AC-25(2):235–238, 1980.
346. H. Walk and L. Zsidó. Convergence of the Robbins-Monro method for linear problems in a Banach space. Journal of Mathematical Analysis and Applications, 139:152–177, 1989.
347. É. Walter and L. Pronzato. Robust experiment design: Between qualitative and quantitative identifiabilities. In É. Walter, editor, Identifiability of Parametric Models, pages 104–113. Pergamon Press, Oxford, 1987.
348. É. Walter and L. Pronzato. Qualitative and quantitative experiment design for phenomenological models — A survey. Automatica, 26(2):195– 213, 1990.
349. É. Walter and L. Pronzato. Identification of Parametric Models from Experimental Data. Communications and Control Engineering. Springer-Verlag, Berlin, 1997.
350. J. Warga. Optimal Control of Differential and Functional Equations. Academic Press, New York, 1972.
351. D. Williams. Weighing the Odds. A Course in Probability and Statistics. Cambridge University Press, Cambridge, 2001.
352. W.-K. Wong. A unified approach to the construction of minimax designs. Biometrika, 79(3):611–619, 1992.
353. G. Yin and B. G. Fitzpatrick. On invariance principles for distributed parameter identification algorithms. Informatica, 3(1):98–118, 1992.
354. G. Yin and Y. M. Zhu. On H-valued Robbins-Monro processes. Journal of Multivariate Analysis, 34:116–140, 1990.
355. M. B. Zarrop. Optimal Experiment Design for Dynamic System Identification. Springer-Verlag, New York, 1979.
356. M. B. Zarrop and G. C. Goodwin. Comments on “ Optimal inputs for system identification”. IEEE Transactions on Automatic Control, AC-20(2):299–300, Apr. 1975.
357. H. Zwart and J. Bontsema. An application-driven guide through infinite-dimensional systems theory. In G. Bastin and M. Gevers, editors, European Control Conference 1997: Plenaries and Mini-Courses, pages 289–328. CIACO, Ottignies/Louvain-la-Neuve, 1997.