Tuning of Robust PID Controller with Filter for SISO System Using Evolutionary Algorithms

This paper discusses the performance comparison of Evolutionary Algorithm techniques with a view to tuning the desired design parameters of robust PID controller with filter. The design parameters of robust PID controller such as proportional gain K-p, integral time constant T-i, derivative time constant T-d and filter time constant t(d)/N for Single Input Single Output (SISO) system are computed using Real coded Genetic Algorithm (RGA), Differential Evolution (DE) algorithm and Particle Swarm Optimization (PSO) algorithm. The design parameters are optimized using the statistical measures in twenty independent simulation runs. The computed design parameters obtained using Evolutionary Algorithms are used to determine the performance specifications of the Robust PID controller. The performance specifications determined are robustness with respect to model uncertainties and disturbance attenuation, set point tracking, load disturbance rejection and control energy. The test systems used to ascertain the performance specifications are Phase Locked Loop (PLL) system with motor control and Magnetic Levitation system (MLS). For PLL system, the output response obtained using the computed design parameters by RGA algorithm has proved to be better than DE and PSO. For MLS system, the output response obtained using the computed design parameters by DE algorithm has been better than PSO and RGA.