DocumentCode :
550483
Title :
Iterative learning control algorithms based on complex stochastic distribution systems
Author :
Yi Yang ; Sun Changyin ; Guo Lei
Author_Institution :
Inst. of Autom., Southeast Univ., Nanjing, China
fYear :
2011
fDate :
22-24 July 2011
Firstpage :
1367
Lastpage :
1371
Abstract :
In this paper, a new generalized iterative learning algorithm is first proposed based on complex non-Gaussion stochastic control systems. Following designed neural networks are used to approximate the output PDF of the stochastic system in the repetitive processes or the batch processes, the tracking control to PDF is transformed into a parameter adaptive tuning problem in NN basis function. Under this framework, we study a new model free iterative learning control problem and propose a convex optimization algorithm based on a set of designed LMIs and L1 performance index. Such an algorithm has the advantage of the improvement of the closed-loop output PDF tracking performance and robustness. Simulation results are given to demonstrate the effectiveness of the proposed approach.
Keywords :
adaptive control; closed loop systems; control system synthesis; convex programming; distributed parameter systems; iterative methods; learning systems; linear matrix inequalities; neurocontrollers; performance index; position control; stochastic systems; LMI; batch processes; closed-loop output PDF tracking performance; complex stochastic distribution systems; convex optimization algorithm; generalized iterative learning algorithm; neural network basis function; non-Gaussion stochastic control systems; parameter adaptive tuning problem; performance index; probability density functions; repetitive processes; tracking control; Algorithm design and analysis; Artificial neural networks; Optimization; Process control; Robustness; Stochastic processes; Stochastic systems; Iterative Learning Control; L1 Optimization Index; Stochastic Distribution Control;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Control Conference (CCC), 2011 30th Chinese
Conference_Location :
Yantai
ISSN :
1934-1768
Print_ISBN :
978-1-4577-0677-6
Electronic_ISBN :
1934-1768
Type :
conf
Filename :
6000822
Link To Document :
بازگشت