Optimal Control of Quadruple Tank System Using Genetic Algorithm

Abstract

Multivariable framework includes in excess of one control loop, these loops communicate with each other, in such a way, to the point that solitary information influences its own output as well as influences different process outputs. The quadruple tank system is basically a water level control issue and the best research facility case to break down the nonlinearities and interactions in process enterprises. Traditional controller techniques, similar to (PI) with (IMC), don't advance the framework. Consequently the optimization techniques, for example, Bacteria Foraging optimization(BFO), Particle swarm Optimization(PSO),and the proposed strategy Genetic Algorithm(G.A),are used to enhance the dynamic and steady state error execution of the framework to deal with the nonlinearities and interactions. Mat lab recreations are utilized to appear the best execution and reasonable comparison between all controllers’ strategies.