Evolutionary Algorithm Based Controller Design for Multivariable Coupled Tank System

This paper presents a control strategy for a multivariable system of an interacting Coupled Tank System (CTS). A conventional Proportional Integral Derivative (PID) controller technique is used, to maintain the water level of both the tanks of the CTS, by controlling input to the two water pumps. The model reference adaptive control (mrac) strategy has been used to improve the performance of the PID controller for the CTS. Evolutionary algorithm based optimization techniques such as Ant Colony Optimization (ACO) and Harmony Search Optimization (HSO) have been used to get the PID controller parameters for the closed loop system and the performances have been compared.