Grey wolf optimizer algorithm-based tuning of fuzzy control systems with reduced parametric sensitivity
Document Type
Journal Article
Publication Title
IEEE Transactions on Industrial Electronics
Publisher
Institute of Electrical and Electronics Engineers Inc.
Place of Publication
United States
School
School of Engineering
RAS ID
22214
Abstract
This paper proposes an innovative tuning approach for fuzzy control systems (CSs) with a reduced parametric sensitivity using the Grey Wolf Optimizer (GWO) algorithm. The CSs consist of servo system processes controlled by Takagi-Sugeno-Kang proportional-integral fuzzy controllers (TSK PI-FCs). The process models have second-order dynamics with an integral component, variable parameters, a saturation, and dead-zone static nonlinearity. The sensitivity analysis employs output sensitivity functions of the sensitivity models defined with respect to the parametric variations of the processes. The GWO algorithm is used in solving the optimization problems, where the objective functions include the output sensitivity functions. GWO's motivation is based on its low-computational cost. The tuning approach is validated in an experimental case study of a position control for a laboratory nonlinear servo system, and TSK PI-FCs with a reduced process small time constant sensitivity are offered.
DOI
10.1109/TIE.2016.2607698
Access Rights
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Comments
Precup, R. E., David, R. C., & Petriu, E. M. (2017). Grey wolf optimizer algorithm-based tuning of fuzzy control systems with reduced parametric sensitivity. IEEE Transactions on Industrial Electronics, 64(1), 527-534. https://doi.org/10.1109/TIE.2016.2607698