Intelligent controller implementation for a bioprocess

Proportional-integral-derivative (PID) controller act as efficient controllers for controlling all kinds of industrial process with best performance. A number of chemical processes in the industries are controlled using PID controllers. However, the industrial processes are generally more complicate and nonlinear which can yields inferior performance when controlled by conventional PID controllers. In order to enhance the performance of that kind of process optimal controllers are needed for best control strategy. Genetic algorithm is a type of evolutionary algorithm that is widely accessed in this respect. In this paper Genetic Algorithm is proposed to enhance the performance of Bioprocesses. The working methodology and efficiency of the proposed method are compared with that of traditional methods namely conventional PID controller and LQG controller. The obtained results shows that GA based controllers enhance the performance of the process with best stability.