Swarm Intelligence Based Tuning of Controller Parameters for Concentration Control of Isothermal Continuous Stirred Tank Reactor

Abstract

Basically chemical reactor is a reactor which is used to perform chemical operations. Chemical reactors are of many types like isothermal chemical reactor and non-isothermal chemical reactor. In recent years control of process plant has gained a widespread research interest. Multi input multi output control, RGA based decoupling control are some of the advanced control techniques which are being used in industries. The increasing complexity of modern control systems has emphasized the idea of applying new approaches in order to solve design problems for different control engineering applications. Proportional-Integral-Derivative (PID) control schemes have been widely used in most of process control systems represented by chemical processes for a long time. However, tuning of PID controller is a very complex task, involving a lot of design and process dynamic aspect. Swarm intelligence, which has caught the eyes of researchers due to its simplicity, low computational cost, and good performance, makes it a possible choice for tuning of PID controllers, to increase their performance. This dissertation discusses, in detail, the Particle Swarm Optimization (PSO) algorithm, and its implementation in PID controller tuning to get the optimal tuning parameters. The PID controller is used to control the product concentration of isothermal CSTR. First of all mathematical modeling of the process is performed using experimental plant data. After the mathematical modeling, different controllers are designed to meet the control objective. PSO is used to optimally tune the PID controller.