Chinese Journal of Intelligent Science and Technology ›› 2021, Vol. 3 ›› Issue (4): 449-455.doi: 10.11959/j.issn.2096-6652.202144

• Special Column: Data Based Learning and Optimization • Previous Articles     Next Articles

Action dependent heuristic online tracking control for a class of nonaffine systems

Huiling ZHAO1,2,3,4, Ding WANG1,2,3,4, Jin REN1,2,3,4   

  1. 1 Faculty of Information Technology, Beijing University of Technology, Beijing 100124, China
    2 Beijing Key Laboratory of Computational Intelligence and Intelligent System, Beijing 100124, China
    3 Beijing Institute of Artificial Intelligence, Beijing 100124, China
    4 Beijing Laboratory of Smart Environmental Protection, Beijing 100124, China
  • Revised:2021-11-20 Online:2021-12-15 Published:2021-12-01
  • Supported by:
    The National Natural Science Foundation of China(61773373);The National Natural Science Foundation of China(61890930-5);The National Natural Science Foundation of China(62021003);The National Key Research and Development Project of China(2021ZD0112300-2);The National Key Research and Development Project of China(2018YFC1900800-5);Beijing Natural Science Foundation(JQ19013)


To solve the tracking control problem for nonaffine systems, an online design method was developed by using the action dependent heuristic dynamic programming (ADHDP) structure.Firstly, the tracking control problem for the unknown nonaffine system was transformed into the error regulation problem.Then, the ADHDP tracking controller was designed and the online learning method was adopted to synchronize the system control with the training of action networks and critic networks, so that the desired trajectory could be tracked by the system state.Finally, a simulation example was given to verify the effectiveness of the proposed method.

Key words: tracking control, online learning, action dependent design

CLC Number: 

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