Hybrid PSO - Bacterial Foraging Based Intelligent PI Controller Tuning for pH Process

Abstract

The control of pH process is a difficult problem due to its inherent nonlinearity and time-varying characteristics. For the pH process, Proportional Integral (PI) control has been successfully used for many years. Tuning of the PI controller is necessary for the satisfactory operation of the system. This paper proposes a hybrid approach involving Bacterial Foraging Optimization (BFO) Algorithm and Particle Swarm Optimization (PSO) algorithm for determining the optimal proportional-Integral (PI) controller parameters for control of a pH Process. The BFO algorithm depends on random search directions which may lead to delay in reaching the global solution. The PSO may lead to possible entrapment in local minimum solutions. The proposed hybrid approach has stable convergence characteristic and good computational efficiency. Simulation results clearly illustrate that the proposed approach is very efficient in improving the step response characteristics such as, reducing the Mean Square Error (MSE), rise time and settling in control of a pH process.