Intelligent Tuning of PID Controller to Balance the Shape Memory Wire Actuated Ball and Beam System

The ball on beam system is a highly nonlinear laboratory model which helps to understand the modern and classical control theory. This paper emphasizes the position control of a ball on beam system which is actuated by shape memory alloy wires in an antagonistic configuration. The shape memory alloy actuator provides the necessary force to actuate the beam in the left and right directions of angular position. To achieve effective control of any system it is necessary to design the controller optimally but it is very difficult due to the requirement of proper tuning which is not feasible by the conventionally designed controller. The objective of this paper is the optimal design of the well-received PID controller by using intelligent tuning techniques to drive the system with the best performance. Since the genetic algorithm and particle swarm optimization are the numerical algorithms that have been extensively used to solve all types of complex engineering problems to improve their performance, these algorithms are used to tune the PID controller. The results of genetic algorithm and particle swarm optimization are benchmarked with a conventionally designed PID controller.