Time delays in industrial, biological, and chemical processes can significantly hinder system performance, which conventional PID controllers may not adequately address. This paper presents Fractional-Order Proportional Integral Derivative (FOPID) controller using particle swarm optimization (PSO) to achieve robust control for time delay systems (TDSs). The proposed PSO-FOPID method optimizes controller parameters by minimizing the Integral of Squared Error (ISE). Simulations conducted using MATLAB/Simulink demonstrate that the PSO-FOPID controller outperforms Integer-Order PID (IOPID), Fractional \(M_\text {s}\) Constrained Integral Gain Optimization Method (FMIGO), and Fractional-order Proportional Integral (FOPI) controllers in terms of overshoot, rise time, settling time, and disturbance rejection. The PSO-FOPID controller achieves the lowest ISE value, exhibiting enhanced performance in time-domain parameters and robustness against gain variations.

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Robust Control of Time Delay Systems Using Particle Swarm Optimized Fractional-Order PID Controller

  • Diptee S. Patil,
  • Sharad P. Jadhav

摘要

Time delays in industrial, biological, and chemical processes can significantly hinder system performance, which conventional PID controllers may not adequately address. This paper presents Fractional-Order Proportional Integral Derivative (FOPID) controller using particle swarm optimization (PSO) to achieve robust control for time delay systems (TDSs). The proposed PSO-FOPID method optimizes controller parameters by minimizing the Integral of Squared Error (ISE). Simulations conducted using MATLAB/Simulink demonstrate that the PSO-FOPID controller outperforms Integer-Order PID (IOPID), Fractional \(M_\text {s}\) Constrained Integral Gain Optimization Method (FMIGO), and Fractional-order Proportional Integral (FOPI) controllers in terms of overshoot, rise time, settling time, and disturbance rejection. The PSO-FOPID controller achieves the lowest ISE value, exhibiting enhanced performance in time-domain parameters and robustness against gain variations.