Hybrid genetic algorithm-swarm intelligence-based tuning of temperature controller for continuously stirred tank reactor. (2016)

• Record Type: Journal Article
• Authors: Kantha, Aditya Sarjak; Utkarsh, Ayush; Jatoth, Ravi Kumar
• Is Part Of: International journal of modelling, identification and control. Volume 25:Number 3(2016)
• Page Start: 239
• Page End: 248
• Publication Date: 2016
• Subjects: CSTR control -- continuously stirred tank reactors -- PID control -- PSO -- particle swarm optimisation -- GAs -- hybrid GA-PSO -- temperature optimisation -- genetic algorithms -- swarm intelligence -- controller tuning -- temperature control -- modelling; Engineering -- Methodology -- Periodicals; Science -- Methodology -- Periodicals; 001.42
• Languages: English
• ISSNs: 1746-6172

Abstract

This paper presents a hybrid model of swarm intelligence and genetic algorithm for tuning of PID controller parameters for a temperature control of continuously stirred tank reactor which is generally used to carry out chemical reactions in an industry on a large scale. A time domain study of different methods for tuning of PID controller parameters was performed and it was found that particle swarm optimisation (PSO) performance was better than genetic algorithm (GA). But in recent literature hybrid mechanisms are used for tuning of controllers and a hybrid of GA-PSO gave the better output results in the observations hence it is proposed here to control the temperature of continuous stirred tank reactor.