Issues on robust adaptive feedback control

IFAC Proceedings Volumes (IFAC-PapersOnline)

Volumn 16, Issue , 2005, Pages 547-577

  Athans, Michael ^a,b   Fekri, Sajjad ^a   Pascoal, Antonio ^a  

^a INSTITUTE FOR SYSTEMS AND ROBOTICS   (Portugal)

^b MASSACHUSETTS INSTITUTE OF TECHNOLOGY   (United States)

Author keywords

Adaptive control; Multiple model adaptive control; Robust adaptive control; Robust control; Robust synthesis

Indexed keywords

ROBUST CONTROL; STOCHASTIC SYSTEMS;

ADAPTIVE CONTROL; DESIGN METHODOLOGY; HYPOTHESIS TESTING; MULTIPLE-MODEL ADAPTIVE CONTROLS; PRECISE DEFINITION; ROBUST ADAPTIVE FEEDBACK CONTROL; ROBUST PERFORMANCE; ROBUST-ADAPTIVE CONTROL;

FEEDBACK;

EID: 79960739631     PISSN: 14746670     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.3182/20050703-6-cz-1902.01036     Document Type: Conference Paper

References (59)

1. Anderson, B. D. O. and J. B. Moore (1979). Optimal Filtering. Prentice Hall.
2. Anderson, B. D. O. and J. B. Moore (1990). Optimal Control - Linear Quadratic Methods. Prentice Hall. NJ, USA.
3. Anderson, B. D. O. et al. (2000). Multiple model adaptive control. part 1: Finite controller coverings. Int. J. of Robust and Nonlinear Control 10(11-12), 909-929.
4. Anderson, B. D. O. et al. (2001). Multiple model adaptive control with safe switching. Int. J. of Adaptive Control and Signal Processing 15(5), 445-470.
5. Åström, K. J. (2000). Limitations on control system performance. European Journal of Control 6(1), 1-19.
6. nd ed., Addison-Wesley. MA, USA.
7. Athans, M. et al. (1977). The stochastic control of the F-8C aircraft using the multiple model adaptive control (MMAC) method - part I: Equilibrium flight. IEEE Trans. on Automatic Control 22(5), 768-780.
8. Athans, M. and C. B. Chang (1976). Adaptive estimation and parameter identification using multiple model estimation algorithms. Technical Report 1976-28. MIT Lincoln Lab., Lexington, MA, USA.
9. Balas, G. J. (2003). Private communication re mixed-μ software.
10. th ed., The Math Works Inc.
11. Baram, Y. (1976). Information, consistent estimation and dynamic system identification. PhD thesis. MIT. Cambridge, MA, USA.
12. Baram, Y. and N. R. Sandell (1978a). Consistent estimation on finite parameter sets with application to linear systems identification. IEEE Trans. on Automatic Control 23(3), 451-454.
13. Baram, Y. and N. R. Sandell (1978b). An information theoretic approach to dynamical systems modeling and identification. IEEE Trans. on Automatic Control 23(1), 61-66.
14. th IEEE Mediterranean Conference on Control and Automation (MED'05). Limassol, Cyprus.
15. Chang, C. and M. Athans (1978). State estimation for discrete systems with switching parameters. IEEE Trans. on Aerospace and Electronic System 14(3), 418-425.
16. Corradini, M. L. et al. (2004). Robust stabilization of multivariable uncertain plants via switching control. IEEE Trans. on Automatic Control 49(1), 107-114.
17. Doob, J. L. (1953). Stochastic Processes. John Wiley & Sons, Inc., New York.
18. th IEEE Mediterranean Conference on Control and Automation (MED'04). Kusadasi, Turkey.
19. Fekri, S. et al. (2004b). RMMAC: A novel robust adaptive control scheme - Part I: Architecture. Proc. of the IEEE Conf. on Decision and Control. Paradise Island, Bahamas.
20. Fekri, S. et al. (2004c). RMMAC: A novel robust adaptive control scheme - Part II: Performance evaluation. Proc. of the IEEE Conf. on Decision and Control. Paradise Island, Bahamas.
21. Fekri, S. (2005). Robust adaptive MIMO control using multiple-model hypothesis testing and mixed- synthesis. PhD thesis. Instituto Superior Técnico. Lisbon, Portugal.
22. Gelb, A. (1974). Applied Optimal Estimation. MIT Press. MA, USA.
23. Gernander, U. (1959). Stochastic Processes and Statistical Inference. Vol. 1. Arkiv für Mathematic.
24. Gray, R. M. (2001). Probability, Random Processes, and Ergodic Properties. Springer Verlag.
25. Greene, C. S. (1975). An analysis of the multiple model adapative control algorithm. PhD thesis. MIT. Cambridge, MA, USA.
26. Greene, C. S. and A. S. Willsky (1980). An analysis of the multiple model adaptive control algorithm. Proc. of the IEEE Conf. on Decision and Control. pp. 1142-1145.
27. Grewal, M. S. et al. (2001). Global Positioning Systems, Inertial Navigation, and Integration. John Wiley & Sons, Inc.
28. Halmos, P. R. (1956). Lectures on Ergodic Theory. Chelsea Publ. Co., New York.
29. Hawkes, R. M. and J. Moore (1976). Performance of bayesian parameter estimators for linear signal models. IEEE Trans. on Automatic Control 21(4), 523-527.
30. Hespanha, J. P. et al. (2001). Multiple model adaptive control. part 2: switching. Int. J. of Robust and Nonlinear Control 11(5), 479-496.
31. Ioannou, P. and J. Sun (1996). Robust Adaptive Control. Prentice Hall. NJ, USA.
32. Jun, M. and M. G. Safonov (1999). Automatic PID tuning: An application of unfalsified control. Proc. IEEE CCA/CACSD. pp. 328-333.
33. Kosut, R. L. and B. D. O. Anderson (1988). Adaptive control via finite modelling and robust control. IFAC Workshop on Robust Adaptive Control pp. 91-95.
34. Kwakernaak, H. and R. Sivan (1972). Linear Optimal Control Systems. John Wiley. NY, USA.
35. Lainiotis, D. G. (1971). Optimal adaptive estimation: Structure and parameter adaptation. IEEE Trans. on Automatic Control AC- 16(2), 160-170.
36. Landau, I. D. (1979). Adaptive Control: The Model Reference Approach. Marcel Dekker. NY, USA.
37. Ljung, L. (1976). On the Consistency of Prediction Error Identification Methods. pp. 121-164. in System Identification: Advances and Case Studies, (R. K. Mehra and D. G. Lainiotis, eds.). Academic Press. New York.
38. Magill, D. T. (1965). Optimal adaptive estimation of sampled stochastic processes. IEEE Trans. on Automatic Control AC-10(4), 434-439.
39. Maybeck, P. S. and J. Griffin (1997). MMAE/MMAC control for bending with multiple uncertain parameters. IEEE Trans. on Aerospace and Electronic System 33(3), 903-912.
40. Morse, A. S. (1996). Supervisory control of families of linear set-point controllers - part 1: Exact matching. IEEE Trans. on Automatic Control 41(10), 1413-1431.
41. Morse, A. S. (1997). Supervisory control of families of linear set-point controllers - part 2: Robustness. IEEE Trans. on Automatic Control 42(11), 1500-1515.
42. Morse, A. S. (1998). A bound for the disturbance - to - tracking - error gain of a supervised set point control system. pp. 23-41. in Perspectives in Control Theory and Applications, (D. Normand-Cyrot, ed.). Springer-Verlag. Berlin.
43. Morse, A. S. (2004). Analysis of a supervised set-point control containing a compact continuum of finite-dimensional linear controllers. Proc. MTNS. Belgium.
44. Narendra, K. S. and A. Annaswamy (1988). Stable Adaptive Systems. Prentice Hall. NJ, USA.
45. Narendra, K. S. and J. Balakrishnan (1997). Adaptive control using multiple models. IEEE Trans. on Automatic Control 42(2), 171-187.
46. Rohrs, C. E. et al. (1985). Robustness of continuous-time adaptive control algorithms in the presence of unmodeled dynamics. IEEE Trans. on Automatic Control 30(9), 881-889.
47. Safonov, M. G. and T.-C. Tsao (1995). The Unfalsified Control Concept: A Direct Path From Experiment To Controller. pp. 196-214. in Feed-back Control, Nonlinear Systems, and Complexity, (B. A. Francis and A. R. Tannenbaum, eds.). Springer-Verlag.
48. Safonov, M. G. and T.-C. Tsao (1997). The unfalsified control concept and learning. IEEE Trans. on Automatic Control 42(6), 843-847.
49. Sastry, S. and M. Bodson (1989). Adaptive Control: Stability, Convergence and Robustness. Prentice-Hall. NJ, USA.
50. Schiller, G. and P. S. Maybeck (1997). Control of a large space structure using MMAE/MMAC techniques. IEEE Trans. on Aerospace and Electronic System 33(4), 1122-1130.
51. Schott, K. D. and B. W. Bequette (1997). Multiple Model Adaptive Control. pp. 269-292. in Multiple Model Approaches to Modelling and Control, (R. Murray-Smith and T. A. Johnsen eds.). Taylor & Francis. London.
52. Shomber, H. R. (1980). An extended analysis of the multiple model adaptive control algorithm. PhD thesis. MIT. Cambridge, MA, USA.
53. Willner, D. (1973). Observation and control of partially unknown systems. PhD thesis. MIT. Cambridge, MA, USA.
54. Yared, K. I. (1979). Maximum likelihood identification of state space models for linear dynamic systems. PhD thesis. MIT. Cambridge, MA, USA.
55. Young, P. M. et al. (1992). Practical computation of the mixed-μ problem. Proc. of the American Control Conf.. Chicago, IL. pp. 2190-2194.
56. Young, P. M. et al. (1995). Computing bounds for the mixed-μ problem. Int. J. of Robust and Nonlinear Control 5, 573-590.
57. Young, P. M. (1994). Controller design with mixed uncertainties. Proc. of the American Control Conf.. Baltimore, MD. pp. 2333-2337.
58. Zhou, K. et al. (1996). Robust and Optimal Control. Prentice-Hall. NJ, USA.
59. Zhou, K. (1998). Essential of Robust Control. Prentice-Hall. NJ, USA.