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Intelligent Tuning of PID Controller to Balance the Shape Memory Wire Actuated Ball and Beam System
Physical Mesomechanics ( IF 1.6 ) Pub Date : 2021-03-02 , DOI: 10.1134/s1029959920060181
M. Banu Sundareswari , G. Then Mozhi , K. Dhanalakshmi

Abstract

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.



中文翻译:

PID控制器的智能调整以平衡形状记忆线致动的球和梁系统

摘要

光束控制系统是一个高度非线性的实验室模型,有助于理解现代和经典控制理论。本文重点介绍了球形束系统的位置控制,该球形系统由形状记忆合金丝以对立构型致动。形状记忆合金致动器提供必要的力,以在左右角位置方向上致动光束。为了实现对任何系统的有效控制,有必要对控制器进行最佳设计,但是由于需要适当的调整,这是非常困难的,而这是常规设计的控制器无法实现的。本文的目的是通过使用智能调整技术来驱动性能最佳的PID控制器的最佳设计。由于遗传算法和粒子群优化是广泛用于解决所有类型的复杂工程问题以提高其性能的数值算法,因此这些算法可用于调整PID控制器。遗传算法和粒子群优化的结果以常规设计的PID控制器为基准。

更新日期:2021-03-02
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