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A new data-driven sliding mode learning control for discrete-time MIMO linear systems

Author

Listed:
  • Lei Cao
  • Shouli Gao
  • Dongya Zhao

Abstract

A new data-driven sliding mode learning control (DDSMLC) is designed for a class of discrete-time MIMO linear systems in the presence of uncertainties. In this scheme, a new control is designed to enforce the states to reach and remain on the sliding surface. In addition, a recursive algorithm using system measured data is adopted to estimate the unknown system parameters, so a complete data-driven sliding mode control is designed, which does not need to know any parameters in the system. Moreover, the chattering is reduced because there is no non-smooth control used in DDSMLC. After the strict stability analysis, the effectiveness of DDSMLC is validated by MATLAB simulations.

Suggested Citation

  • Lei Cao & Shouli Gao & Dongya Zhao, 2022. "A new data-driven sliding mode learning control for discrete-time MIMO linear systems," International Journal of Industrial and Systems Engineering, Inderscience Enterprises Ltd, vol. 42(2), pages 211-229.
    • Handle: RePEc:ids:ijisen:v:42:y:2022:i:2:p:211-229
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