Self-tuning PID controller using genetic algorithm

Abstract EN

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 selftuning 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.