Covariance matrix adaptation evolution strategy based design of centralized PID controller
In this paper, design of centralized PID controller using Covariance Matrix Adaptation Evolution Strategy (CMAES) is presented. Binary distillation column plant described by Wood and Berry (WB) having two inputs and two outputs and by Ogunnike and Ray (OR) having three inputs and three outputs are considered for the design of multivariable PID controller. Optimal centralized PID controller is designed by minimizing IAE for servo response with unit step change. Simulations are carried out using SIMULINK-MATLAB software. The statistical performances of the designed controllers such as best, mean, standard deviations of IAE and average functional evaluations for 20 independent trials. For the purpose of comparison, recent version of real coded Genetic Algorithm (RGA) with simulated binary crossover (SBX) and conventional BLT method are used. In order to validate the performance of optimal PID controller for robustness against load disturbance rejection, load regulation experiment with step load disturbance is conducted. Also, to determine the performance of optimal PID controller for robustness against model uncertainty, servo and load response with +20% variations in gains and dead times is conducted. Simulation results reveal that for both OR and WB systems, CMAES designed centralized PID controller is better than other methods and also it is more robust against model uncertainty and load disturbance.
pid control cmaes real coded genetic algorithm mimo system controller tuning