Self-learning variable structure control for a class of sensor-actuator systems

Sanfeng Chen, Shuai Li, Bo Liu, Yuesheng Lou, Yongsheng Liang

Research output: Journal article publicationJournal articleAcademic researchpeer-review

3 Citations (Scopus)

Abstract

Variable structure strategy is widely used for the control of sensor-actuator systems modeled by Euler-Lagrange equations. However, accurate knowledge on the model structure and model parameters are often required for the control design. In this paper, we consider model-free variable structure control of a class of sensor-actuator systems, where only the online input and output of the system are available while the mathematic model of the system is unknown. The problem is formulated from an optimal control perspective and the implicit form of the control law are analytically obtained by using the principle of optimality. The control law and the optimal cost function are explicitly solved iteratively. Simulations demonstrate the effectiveness and the efficiency of the proposed method.
Original languageEnglish
Pages (from-to)6117-6128
Number of pages12
JournalSensors (Switzerland)
Volume12
Issue number5
DOIs
Publication statusPublished - 1 May 2012
Externally publishedYes

Keywords

  • Bellman equation
  • Principle of optimality
  • Self-learning
  • Sensor-actuator system
  • Variable structure control

ASJC Scopus subject areas

  • Analytical Chemistry
  • Atomic and Molecular Physics, and Optics
  • Biochemistry
  • Instrumentation
  • Electrical and Electronic Engineering

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