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首页> 外文期刊>IETE Journal of Research >Robust 2-DOF FOPID Controller Design for Maglev System Using Jaya Algorithm
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Robust 2-DOF FOPID Controller Design for Maglev System Using Jaya Algorithm

机译：使用Jaya算法的Maglev系统强大的2-DOF FOPID控制器设计

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摘要

In this paper, 1-Degree of Freedom (1-DOF) and 2-Degree of Freedom (2-DOF) Integer Order (IO) and Fractional Order (FO) Proportional-Integral-Derivative (PID) Controller has been designed for the Magnetic Levitation (Maglev) system. Maglev is one of the most versatile research-oriented laboratory instruments in the field of control systems engineering. The controller for the Maglev system is designed in such a way that a ferromagnetic ball can precisely levitate in a controlled electromagnetic field with particular design specifications. The controller parameters can be appropriately identified by optimizing the objective function with various popular artificial intelligence based evolutionary optimization algorithms. The 2-DOF controller structure takes care of both reference signal tracking and disturbance rejection through the feedback path. The 1 and 2-DOF controller structures with both Integer as well as Fractional Order approaches for different nonlinear systems were already discussed in various papers. However, the application of the Fractional Order control technique on a highly nonlinear Maglev system using the Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Hybrid Particle Swarm Optimization (Hybrid PSO), and recently developed Jaya Algorithm is of our interest. Observation of the final analysis based on different simulation results states that as the controller structure moves from 1-DOF to 2-DOF, the performance of the system and the control signal gets improved. The robustness analysis has also been incorporated in this study which shows that the 1 and 2-DOF IOPID and FOPID controllers designed using different optimization algorithms for the Maglev plant are robust in nature.
机译：本文设计了1度 - 自由度（1-DOF）和2度自由度（2-DOF）整数（IO）和分数级（FO）比例 - 积分衍生物（PID）控制器已经为此设计磁悬浮（Maglev）系统。 Maglev是控制系统工程领域中最通用的面向研究的实验室仪器之一。用于Maglev系统的控制器以这样的方式设计，使得铁磁球可以精确地在具有特定设计规格的受控电磁场中的浮动。通过优化具有各种流行的人工智能的进化优化算法，可以通过优化目标函数来适当地识别控制器参数。 2-DOF控制器结构通过反馈路径处理参考信号跟踪和干扰抑制。在各种纸上已经讨论了具有整数的1和2-DOF控制器结构以及用于不同非线性系统的分数阶方法。然而，使用遗传算法（GA），粒子群优化（PSO），混合粒子群优化（Hybrid PSO）和最近开发的Jaya算法，在高度非线性Maglev系统上应用了分数级磁悬浮系统的应用是我们的兴趣。基于不同仿真结果的最终分析观察，当控制器结构从1-DOF移动到2-DOF时，系统的性能和控制信号得到改善。该研究还载入了鲁棒性分析，表明使用针对Maglev植物的不同优化算法设计的1和2-DOF和FoPID控制器本质上是稳健的。

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