|تعداد مشاهده مقاله||2,363,659|
|تعداد دریافت فایل اصل مقاله||1,661,810|
WOA-based Interval Type II Fuzzy Fractional-order Controller Design for a Two-Link Robot Arm
|Journal of Electrical and Computer Engineering Innovations (JECEI)|
|مقاله 9، دوره 7، شماره 1، فروردین 2019، صفحه 69-82 اصل مقاله (2.01 M)|
|نوع مقاله: Original Research Paper|
|شناسه دیجیتال (DOI): 10.22061/jecei.2019.5783.256|
|F. Jamshidi1؛ M. Vaghefi* 2|
|1Department of Electrical Engineering, Faculty of Engineering, Fasa University, Fasa, Iran|
|2Department of Electrical Engineering, Islamic Azad University, Shiraz Branch, Shiraz, Iran|
|تاریخ دریافت: 13 دی 1396، تاریخ بازنگری: 05 تیر 1397، تاریخ پذیرش: 10 آبان 1397|
|Background and Objectives: A robot arm is a multi-input multi-output and non-linear system that has many industrial applications. Parameter uncertainties and external disturbances attenuate the performance of this system and a controller design is hence necessary to overcome them.|
Methods: In this paper, the interval Type II Fuzzy fractional-order proportional integral differential (IT2FO-FPID) controller is designed to control a robot arm with 2 degrees of freedom (two-link robot arm). Whale optimization algorithm (WOA) is used to determine the optimal value of controller parameters. The performance of IT2FO-FPID is compared with PID, fractional-order PID (FOPID) and Fuzzy FOPID whose parameters are determined by WOA. The performance of IT2FO-FPID whose parameters are determined by WOA, genetic algorithm, and particle swarm optimization methods are compared.
Results: Quantitative and qualitative results of simulations indicate performance improvement with the IT2FO-FPID controller. The ability of WOA in optimizing the parameters of the IT2FO-FPID controller is demonstrated.
Conclusion: Sensitivity analysis and the study of the effect of parameter variations and disturbances confirm the robust performance of WOA-based IT2FO-FPID.
|Fractional order proportional integral differential؛ Interval type 2 fuzzy؛ Whale optimization algorithm؛ Genetic algorithm؛ Particle swarm Optimization|
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