PSO-Based PID Parameter Optimization
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The Particle Swarm Optimization (PSO) algorithm is a widely-used optimization technique that has gained significant traction in PID parameter tuning. This population-based intelligent algorithm mimics the collective foraging behavior of bird flocks to search for optimal solutions. In PID control applications, PSO optimizes key performance metrics such as settling time, overshoot, and steady-state error to achieve superior control performance. Implementation typically involves defining a fitness function that quantifies system performance, with particles representing potential PID gain combinations (Kp, Ki, Kd) navigating the search space through velocity updates based on personal and global best positions. The algorithm's iterative process continues until convergence criteria are met, making PSO-based PID optimization a prominent research area in control systems engineering.
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