Journal of South China University of Technology(Natural Science Edition) ›› 2012, Vol. 40 ›› Issue (9): 81-86,92.

• Electronics, Communication & Automation Technology • Previous Articles     Next Articles

One-Sided SPSA-Based Data-Driven Control Algorithm with Dynamic Deviations

Ai Wei  Zhu Xue-feng   

  1. School of Automation Science and Engineering,South China University of Technology,Guangzhou 510640,Guangdong,China
  • Received:2011-09-02 Revised:2012-06-13 Online:2012-09-25 Published:2012-08-01
  • Contact: 哀微(1979-) ，女，博士，讲师，主要从事无模型控制、数据驱动控制研究． E-mail:aiwei@scut.edu.cn
  • About author:哀微(1979-) ，女，博士，讲师，主要从事无模型控制、数据驱动控制研究．
  • Supported by:

    国家自然科学基金资助项目( 60704012 ) ; 华南理工大学中央高校基本科研业务费专项资金资助项目( 2011ZM0120)

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Abstract:

Using simultaneous-perturbation stochastic approximation ( SPSA) algorithm to establish a data-driven control method is feasible when the mathematical models of controlled systems are totally unknown. In this paper,the principle and effectiveness of both the SPSA algorithm and its improved algorithms are investigated,and the shortcomings of the SPSA algorithm in the control-oriented situation,such as lower gradient approximation efficiency,are analyzed. Then,a one-sided SPSA algorithm is proposed for the control problem,which saves one-third data
compared with the SPSA algorithm in the actual control,thus obtaining enough convergence rate and accuracy of the optimization procedure for the control problem. Then,by combining the one-sided SPSA algorithm and the datadriven control method,a data utilization scheme is designed based on dynamic deviations,and the connection weights in a neural network function approximator are adjusted directly and adaptively. Simulatied results show that the proposed data-driven control method secures excellent control over nonlinear systems without the help of any model.

Key words: simultaneous-perturbation stochastic approximation, data-driven control, gradient approximation, onesided SPSA, data utilization, nonlinear systems

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