Self-tuning PID Controller using Genetic Algorithm

This work presents design, modeling, simulation and hardware implementation of a separately excited DC motor speed control using Field Programmable Analog Array (FPAA) Technology. The framework presents a low power self-tuning analog Proportional-Integral-Derivative (PID) controller using a model-free tuning method, this overcomes the problems associated with reconfigurable analog arrays. In comparison with a self-tuning digital PID controller, the analog self-tuning PID controller combines the advantages of low power, no quantization noise, high bandwidth and high speed. The prototype hardware uses a commercially available field programmable analog array and Genetic Algorithm as tuning method. The practical results show that a self-tuned controller can outperform a hand tuned solution and demonstrate adaptability to plant drift, also it shows enhancement in the reduction of overshoot, settling time and the steady-state transient response of the controlled plant.