Hybrid genetic algorithm-swarm intelligence based tuning of continuously stirred tank reactor

Abstract

This paper presents a hybrid model of particle swarm optimization and genetic algorithm for tuning of PID controller parameters for a concentration control of isothermal continuously stirred tank reactor which is generally used to carry out chemical reactions in an industry on a large scale. The time domain study of different methods for tuning of PID controller parameters were observed and it was found that PSO(Particle Swarm Optimization)performance was better than GA(Genetic Algorithm) but the hybrid of GA-PSO gave the best output results in the observation to control the concentration of isothermal continuous stirred tank reactor.