Self-tuning control based on multi-innovation stochastic gradient parameter estimation

Systems and Control Letters

Volumn 58, Issue 1, 2009, Pages 69-75

  Zhang, Jiabo ^a   Ding, Feng ^a   Shi, Yang ^b  

^a JIANGNAN UNIVERSITY   (China)

^b UNIVERSITY OF SASKATCHEWAN   (Canada)

Author keywords

Adaptive control; Multi innovation identification methods; Parameter estimation; Recursive identification; Self tuning control; Stochastic gradient

Indexed keywords

CLOSED LOOP CONTROL SYSTEMS; COMMUNICATION CHANNELS (INFORMATION THEORY); DIGITAL CONTROL SYSTEMS; DISCRETE TIME CONTROL SYSTEMS; METAL ANALYSIS; MODEL STRUCTURES; PARAMETER ESTIMATION; RECURSIVE FUNCTIONS; TUNING;

ADAPTIVE CONTROL; MULTI-INNOVATION IDENTIFICATION METHODS; RECURSIVE IDENTIFICATION; SELF-TUNING CONTROL; STOCHASTIC GRADIENT;

IDENTIFICATION (CONTROL SYSTEMS);

EID: 57249097181     PISSN: 01676911     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.sysconle.2008.08.005     Document Type: Article

References (16)

1. Åström K.J., and Wittenmak B. On self-tuning regulators. Automatica 9 2 (1973) 185-199
2. Goodwin G.C., and Sin K.S. Adaptive Filtering Prediction and Control (1984), Prentice-hall, Englewood Cliffs, NJ
3. Ding F., Chen T., and Iwai Z. Adaptive digital control of Hammerstein nonlinear systems with limited output sampling. SIAM Journal on Control and Optimization 45 6 (2007) 2257-2276
4. Ding F., and Chen T. Least squares based self-tuning control of dual-rate systems. International Journal of Adaptive Control and Signal Processing 18 8 (2004) 697-714
5. Delyon B. General results on the convergence of stochastic algorithms. IEEE Transactions on Automatic Control 41 9 (1996) 1245-1255
6. Fang H., and Chen H.F. Stability and instability of limit points for stochastic approximation algorithms. IEEE Transactions on Automatic Control 45 3 (2000) 413-420
7. Buche R., and Kushner H.J. Stochastic approximation and user adaptation in a competitive resource sharing system. IEEE Transactions on Automatic Control 45 5 (2000) 844-853
8. Greblicki W. Stochastic approximation in nonparametric identification of Hammerstein systems. IEEE Transactions on Automatic Control 47 11 (2002) 1800-1810
9. Caines P., and Laforune S. Adaptive control with recursive identification for stochastic linear systems. IEEE Transactions on Automatic Control 29 4 (1984) 312-321
10. Radenkovi M.S., and Stankovi S. Strong consistency of parameter estimates in direct self-tuning control algorithms based on stochastic approximation. Automatica 26 3 (1990) 533-544
11. Radenkovic M.S., and Michel A.N. Almost sure rate of convergence of the parameter estimates in stochastic approximation algorithm. IEEE Transactions on Automatic Control 45 6 (2000) 1161-1166
12. Ding F., and Chen T. Performance analysis of multi-innovation gradient type identification methods. Automatica 43 1 (2007) 1-14
13. Ding F., Chen H.B., and Li M. Multi-innovation least squares identification methods based on the auxiliary model for MISO systems. Applied Mathematics and Computation 187 2 (2007) 658-668
14. J.B. Zhang, F. Ding, Y. Shi, Multi-innovation gradient parameter estimation based adaptive control for discrete-time Systems, in: Proceedings of the IEEE International Conference on Automation and Logistics, Jinan, China, August 18-21, 2007, pp. 399-404
15. Ding F., and Chen T. Identification of Hammerstein nonlinear ARMAX systems. Automatica 41 9 (2005) 1479-1489
16. Ding F., Liu P.X., and Yang H.Z. Parameter identification and intersample output estimation for dual-rate systems. IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans 38 4 (2008) 966-975