AUTHORS: Parikshit Kishor Singh, Surekha Bhanot, Harekrishna Mohanta, Vinit Bansal

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ABSTRACT: This paper describes, with extensive experimentation and simulation, three aspects of strong acid (Hydrochloric acid, HCl) and strong base (Sodium Hydroxide, NaOH) based pH neutralization process: (i) dynamic modeling, (ii) control, and (iii) optimization. Dynamic pH model based on Artificial Neural Network (ANN) has been used for various simulation studies involving servo and regulatory operations in Fuzzy Logic Control (FLC) scheme, and in optimization of pH controller parameters. This paper compares performance variables, such as Integral of Squared Errors (ISE), and maximum overshoot or undershoots, of optimized fuzzy control technique for servo and regulatory operations. The present work also describes finding optimum parameter settings of the pH controller using various search and optimization techniques such as Genetic Algorithm (GA), Differential Evolution (DE), and Particle Swarm Optimization (PSO), and the convergence of optimization techniques

KEYWORDS: - pH neutralization process, artificial neural network, system identification, fuzzy logic, nonlinear control, genetic algorithm, particle swarm optimization, differential evolution

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