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This study proposes an advanced control strategy that combines Fuzzy Multi-Model Control (FMMC) and Sliding Mode Control (SMC) to improve the regulation of chemical processes characterized by nonlinear dynamics. The approach is based on a Takagi–Sugeno (TS) fuzzy model, where each rule represents a local linear subsystem, allowing for smooth transitions between operating regions and thereby enhancing the overall control system’s robustness. By integrating the adaptive nature of fuzzy modeling with SMC, the proposed controller achieves superior performance in both transient and steady-state responses when compared to conventional methods, demonstrating its effectiveness for complex industrial processes.

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PSO Tuning of Fuzzy Multi-model Sliding Mode Controller for Thermal Process

  • 会议论文

  • 发表日期：

    2026年

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  • Marco Herrera,
  • Luis Caiza,
  • Diego Benítez,
  • Noel Pérez-Pérez,
  • Oscar Camacho,
  • Alvaro Prado

摘要

This study proposes an advanced control strategy that combines Fuzzy Multi-Model Control (FMMC) and Sliding Mode Control (SMC) to improve the regulation of chemical processes characterized by nonlinear dynamics. The approach is based on a Takagi–Sugeno (TS) fuzzy model, where each rule represents a local linear subsystem, allowing for smooth transitions between operating regions and thereby enhancing the overall control system’s robustness. By integrating the adaptive nature of fuzzy modeling with SMC, the proposed controller achieves superior performance in both transient and steady-state responses when compared to conventional methods, demonstrating its effectiveness for complex industrial processes.