A technique for designing an Intelligent PID controller using Very Large Scale Integrated circuits (VLSI) is presented. The PID controller parameters are optimized using the Particle Swarm Optimization (PSO) algorithm, which identifies errors and controls the system with multiple iterations of different parameters. The optimization process focuses on parameters such as gain, delay, lag, and various times to solve problems. To evaluate the system's performance, a new function that includes system adjusting time, rise time, overshoot, and system error is defined. The circuits are tested and implemented as intelligent PID controllers on VLSI devices in a laboratory plant. The algorithm applied to the PID controller reduces iterations and enables rapid control action, resulting in improved system time delay and performance. The optimization technique is applied to improve the system's response. Finally, the Intelligent PID controller is implemented in FPGA.
Intelligent PID controller, VLSI, Particle Swarm Optimization (PSO), gain, delay, lag, system adjusting time, rise time, overshoot, system error, laboratory plant, FPGA
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