Design and Control of Magnetic Levitation System by Optimizing Fractional Order PID Controller Using Ant Colony Optimization Algorithm

被引:60
作者
Mughees, Abdullah [1 ]
Mohsin, Syed Ali [1 ]
机构
[1] Natl Univ Comp & Emerging Sci, Dept Elect Engn, Islamabad 44000, Pakistan
关键词
FOPID controller; fractional calculus; ant colony optimization; Maglev mathematical model; Routh-Hurwitz stability; MATLAB-simulink; first principle modeling; SLIDING-MODE CONTROL; REAL-TIME IMPLEMENTATION; NONLINEAR CONTROL; NEURAL-NETWORK; PREDICTIVE CONTROL; REFERENCE GOVERNOR; STATE; CONSTRAINTS; PERFORMANCE;
D O I
10.1109/ACCESS.2020.3004025
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
MAGnetic LEVitation (Maglev) is a multi-variable, non-linear and unstable system that is used to levitate a ferromagnetic object in free space. This paper presents the stability control of a levitating object in a magnetic levitation plant using Fractional order PID (FOPID) controller. Fractional calculus, which is used to design the FOPID controller, has been a subject of great interest over the last few decades. FOPID controller has five tunning parameters including two fractional-order parameters (lambda and mu). The mathematical model of the Maglev plant is obtained by using first principle modeling and the laboratory model (CE152). Maglev plant and FOPID controller both have been designed in MATLAB-Simulink. The designed model of the Maglev system can be further used in the process of controller design for other applications. The stability of the proposed system is determined via the Routh Hurwitz stability criterion. Ant Colony Optimization (ACO) algorithm and Ziegler Nichols method has been used to fine-tune the parameters of FOPID controller. FOPID controller output results are compared with the traditional IOPID controller for comparative analysis. FOPID controller, due to its extra tuned parameters, has shown extremely efficient results in comparison to the traditional IOPID controller.
引用
收藏
页码:116704 / 116723
页数:20
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