Genetic Algorithm Based Controllers Used In Multi Variable System

Abstract

There are many systems in the world which are non- linear in feature. To regulate such processes, most enterprises relied solely on single loop control. In the process industries, multivariable device design is in high demand. The quadruple tank system is a multivariable, non-linear, and dynamic operation. The law of mass balance equations and energy equations apply to this method. Because of the interactions between the process variables, maintaining the tank level in a four-tank system is difficult. There are several traditional controls available for quadruple tank systems to regulate the tank's water level in the current process. However, not all controllers are suitable for implementation, and the performance accuracy during implementation is unreliable. As a result, in this papert, controllers such as Proportional Integral, Particle Swarm Optimization, and others are developed, simulated, and their output is compared using criterion such as settling time, peak overshoot, rise time and steady state error.