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Design and implementation of Adaptive Mixed Fuzzy Controller for MIMO nonlinear systems

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  • Puviyarasi, B.
  • Murukesh, C.

Abstract

The controller techniques for the Multiple-Input/Multiple-Output process is complex because of the difference in process dynamics that arise as a variation in process operating condition and the performance of non-linear dynamic coupling. In this work evolves real coded Genetic Algorithm tuned Adaptive Mixed Fuzzy Controller (AMFC) for Two Cylindrical Tank Interacting Level System (TCTILS). First, Adaptive Traditional Fuzzy Controller (ATFC) is developed and its output response is control action for every individual tank. Secondly, to reduce the coupling dynamics, a suitable Adaptive Coupling Fuzzy Controller (ACFC) is included into ATFC to reduce the coupling dynamic effect between each DOF. The real coded Genetic Algorithm (RGA) is used to compute the optimal scale factors for ATFC and ACFC. The simulation performance shows that the RGA tuned AMFC control scheme understands the proper dynamic behaviour of the system, a complete output response with minimum interaction and good disturbance rejection of external load.

Suggested Citation

  • Puviyarasi, B. & Murukesh, C., 2023. "Design and implementation of Adaptive Mixed Fuzzy Controller for MIMO nonlinear systems," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 203(C), pages 71-91.
    • Handle: RePEc:eee:matcom:v:203:y:2023:i:c:p:71-91
    DOI: 10.1016/j.matcom.2022.06.019
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    References listed on IDEAS

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    1. Lygouras, J.N. & Kodogiannis, V.S. & Pachidis, Th. & Tarchanidis, K.N. & Koukourlis, C.S., 2008. "Variable structure TITO fuzzy-logic controller implementation for a solar air-conditioning system," Applied Energy, Elsevier, vol. 85(4), pages 190-203, April.
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