Complex stochastic systems modelling and control via iterative machine learning

Neurocomputing

Volumn 71, Issue 13-15, 2008, Pages 2685-2692

  Wang, Aiping ^a   Afshar, Puya ^b   Wang, Hong ^b  

^a ANHUI UNIVERSITY   (China)

^b UNIVERSITY OF MANCHESTER   (United Kingdom)

Author keywords

Iterative learning mechanism; Probability density functions; RBF neural networks; Stochastic systems

Indexed keywords

ARTIFICIAL INTELLIGENCE; COMPLEX NETWORKS; FUNCTIONS; ITERATIVE METHODS; LEARNING SYSTEMS; PROBABILITY DISTRIBUTIONS; RADIAL BASIS FUNCTION NETWORKS; STOCHASTIC CONTROL SYSTEMS; STOCHASTIC SYSTEMS;

CLOSED-LOOP PERFORMANCE; COMPLEX STOCHASTIC SYSTEMS; ITERATIVE LEARNING MECHANISM; MODELLING AND CONTROLS; PROBABILITY DENSITY FUNCTIONS (PDFS); RADIAL BASIS FUNCTION NEURAL NETWORKS; RBF NEURAL NETWORK; STOCHASTIC DISTRIBUTION;

PROBABILITY DENSITY FUNCTION;

ARTIFICIAL NEURAL NETWORK; BATCH PROCESS; CONFERENCE PAPER; CONTROL SYSTEM; CONTROLLED STUDY; LEARNING ALGORITHM; MACHINE LEARNING; MATHEMATICAL MODEL; PRIORITY JOURNAL; PROCESS DESIGN; STOCHASTIC MODEL; SYSTEM ANALYSIS; TASK PERFORMANCE;

EID: 56449097174     PISSN: 09252312     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.neucom.2007.06.018     Document Type: Conference Paper

References (26)

1. H. Baki, P. Kabore, H. Wang, A new approximation for the modelling and control of bounded stochastic distributions, in: Proceedings of the UKACC International. Conference on Control, 4-7 September 2000, University of Cambridge, 2000.
2. G.M. Campbell, C. Webb, On predicting roller milling performance, Part I: The breakage equation, Powder Technol. 115 (2001) 234-242.
3. T.L. Clarke-Pringle, J.F. MacGregor, Optimization of molecular-weight distribution using batch-to-batch adjustments, Ind. Eng. Chem. Res. 37 (1998) 3660-3669.
4. L. Guo, H. Wang, PID controller design for output PDFs of stochastic systems using linear matrix inequalities, IEEE Trans. Syst. Man Cybern. Part B 35 (2005) 65-71.
5. L. Guo, H. Wang, Generalised discrete-time PI control of output PDFs using square root B-spline expansion, Automatica 41 (2005) 159-162.
6. L. Guo, H. Wang, Fault detection and diagnosis for general stochastic systems using B-spline expansions and nonlinear filters, IEEE Trans. Circuits Syst. Part I 52 (2005) 1644-1652.
7. L. Guo, H. Wang, Minimum entropy filtering for multivariate stochastic systems with non-Gaussian noises, IEEE Trans. Autom. Control 51 (2006) 670-695.
8. C.D. Immanuel, F.J. Doyle III, Open-loop control of particle size distribution on semi-batch emulsion copolymerisation using a genetic algorithm, Chem. Eng. Sci. 57 (2002) 4415-4427.
9. P. Kabore, H. Baki, H. Wang, Linearized controller design for the output PDFs using square root based B-spline models, in: Proceedings of the 15th IFAC World Congress, 21-26 July 2002, Barcelona, 2002, pp. 2694-2699.
10. D. Manca, M. Rovaglio, Infrared thermographic image processing for the operation and control of heterogeneous combustion chambers, Combust. Flame 130 (2002) 277-297.
11. D. Sbarbaro, O. Farias, A. Zawadsky, Real-time monitoring and characterization of flames by principal-component analysis, Combust. Flame 132 (2003) 591-595.
12. G.A. Smook, Handbook for Pulp and Paper Technologists, Angus Wilde Publications Inc., Vancouver, 1992.
13. H. Wang, Bounded Dynamic Stochastic Systems: Modelling and Control, Springer, London, 2000.
14. H. Wang, Control of the output probability density functions for a class of nonlinear stochastic systems, in: Proceedings of the IFAC Workshop on Algorithms and Architectures for Real-time Control, 15-17 April 1998, Cancun, Mexico, 1998, pp. 95-99.
15. H. Wang, Robust control of the output probability density functions for multivariable stochastic systems with guaranteed stability, IEEE Trans. Autom. Control 41 (1999) 2103-2107.
16. H. Wang, Model reference adaptive control of the output stochastic distributions functions for unknown linear stochastic systems, Int. J. Syst. Sci. 30 (1999) 707-715.
17. H. Wang, H. Baki, P. Kabore, Control of bounded dynamic stochastic distributions using square root models: An applicability study in papermaking system, Trans. Inst. Meas. Control 23 (2001) 51-68.
18. H. Wang, P. Kabore, H. Baki, Lyapunov based controller design for bounded dynamic stochastic distribution control, IEEE Proc. Control Theory Appl. 148 (2001) 245-250.
19. H.Wang, H. Yue, A rational spline model approximation and control of output probability density function for dynamic stochastic systems, Trans. Inst. Meas. Control 25 (2003) 93-105.
20. H. Wang, Weight vector based linear control of output probability density functions for dynamic stochastic systems using a rational model approximation, in: Proceedings of the Third IEEE International Conference on Control Theory and Applications, 12-14 December 2001, Pretoria, South Africa, 2001, pp. 192-196.
21. H. Wang, J.H. Zhang, Bounded stochastic distribution control for pseudo ARMAX systems, IEEE Trans. Autom. Control 46 (2001) 486-490.
22. H. Wang, Control of conditional output probability density functions for general nonlinear and non-Gaussian dynamic stochastic systems, IEEE Proc. Control Theory Appl. 150 (2003) 55-60.
23. H. Wang, Minimum entropy control of non-Gaussian dynamic stochastic systems, IEEE Trans. Autom. Control 47 (2002) 398-403.
24. H. Wang, W. Lin, Applying observer based FDI techniques to detect faults in dynamic and bounded stochastic distributions, Int. J. Control 73 (2000) 1424-1438.
25. H. Yue, E. Brown, J. Jiao, H. Wang, On-line web formation control using stochastic distribution methods, in: Proceedings of Control Systems, 3-5 June 2002, Stockholm, Sweden, 2002, pp. 318-322.
26. H. Yue, H. Wang, Minimum entropy control of closed loop tracking errors for dynamic stochastic systems, IEEE Trans. Autom. Control 48 (2003) 118-122.