Majority of the optimization algorithms possess sluggish convergence and inadequate solution accuracy owing to the non-linear characteristics of the system. The Coupled tank system is one such classical benchmark control problem possessing nonlinear characteristics that offers difficulty as far as the control objective is concerned owing to the interaction existing between its controlled variables. Meta-heuristic optimization algorithms endeavor to obtain the best (viable) solution among all the potential solutions for an optimization problem. In this work, a novel meta-heuristic known as Grey Wolf Optimizer (GWO) algorithm for a multivariable coupled tank system is designed and presented. The GWO algorithm is a novel SI (Swarm Intelligence) optimization algorithm inspired by grey wolves which mimics their leadership hierarchy and hunting mechanism in nature. The control performance which depends on the choice of tuning parameters are optimized with the GWO algorithm to optimize the PI controller parameters to attain an optimum solution for the chosen coupled tank system. The effectiveness of the designed controller in set-point tracking and disturbance rejection with GWO algorithm is assessed and the results interpreted by means of simulation using MATLAB SIMULINK software.

Nonlinear Process; Interaction; Multivariable; coupled tank system; Optimization; Controller design.