Control of CSTR using firefly and hybrid firefly-biogeography based optimization (BBFFO) algorithm

Abstract

Continuous Stirred Tank Reactor (CSTR) is the core of numerous procedures due to its simple structure, low cost, stable and productive activity. This paper presents PID controller tuning by using firefly and hybrid Firefly with biogeography based optimization (BBFFO) algorithms for continuously stirred tank reactor (CSTR). In this paper, BBO-FF is iterated to come to the ideal or the close to the ideal of PID controller parameters. Principle accentuate is given to improve the progression reaction and cost proficiency attributes. The CSTR framework is simulated with the proposed hybrid controller which improves the robustness as well as the behavior of the framework. Simulation results demonstrate the adequacy and the effectiveness of the hybridization also present significant upgrade of the time reaction parameters, for example settling time, rise time, overshoot, and integral time absolute error. Studies appeared that the proposed versatile techniques with metaheuristic calculations are quick and efficient in the reduction of error. Both Firefly and Biogeography based optimization is Metaheuristic methodology. The proposed approach BBFFO-PID is compared with the PSO-PID controller in terms of performance indices. Hybridization of the Firefly algorithm with BBO Algorithm for PID controller tuning of CSTR is simulated on MATLAB 2014Ra.