CSA based PID Controller Design Technique for optimizing Various Integral Errors

Control design plays a significant role in almost all types of industries. Proportional-integral-derivative (PID) controllers are an integral part of process control loops. PID controllers are popular for their simplicity of implementation and broad applicability. In recent years, various metaheuristic algorithms and modified hybrid algorithms have been applied to design the controllers. The aim of this paper is to design a controller with high versatility, accuracy and good control quality. In this research paper, first, a novel tuning method based on Crow Search Algorithm (CSA) is proposed to optimize parameters of PID controller: $K_{p}, K_{i}$ and Kd. Each crow represents a feasible solution for the PID parameters. Second, four objective functions have been explored and the effectiveness and convergence rates of CSA-PID controller is evaluated therein for two different control problems. Last, comparison has been carried out between CSA optimized PID The main advantage of CSA is its simplicity, faster convergence rate, ease of implementation and easy understanding. As per findings based on statistical analysis, Crow search Algorithm (CSA) has been found to be more reliable. Simulation results based on two control problems and four evaluation functions have been tested for set point tracking, load rejection capability, noise suppression and modelling errors.