Improved Performance of Cascade Control System using Genetic Algorithm
Cascade control is an approach over Conventional single-input single output-control systems to improve the performance of the system under the influence of strong disturbances. Most of the processes in the chemical industries are controlled using PID controllers. However, most of the processes are complex and nonlinear in nature resulting into their poor performance when controlled by traditional tuned PID controllers. The need for improved performance of the process has led to the development of optimal controllers. Genetic algorithm (GA) is an evolutionary algorithm that is widely used in this respect. Tuning of the PID parameters continues to be important as these parameters have a great influence on the transient response of control system. In this work GA is proposed to improve the performance of a Cascade control (CC) systems with inner loop process (Flow) and outer loop process (level) of interconnected system. A GA is applied to tune PID controllers of outer loop for the best tuning parameters. Simulation results are provided to illustrate the performance of proposed controller design method and results are discussed on set point variation, disturbance rejection and variation of parameters.
Index terms - Cascade control; PID controller; Genetic algorithm