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Stability analysis of dynamic nonlinear interval type-2 TSK fuzzy control systems based on describing function

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This paper focuses on the limit cycles prediction problem to discuss the stability analysis of dynamic nonlinear interval type-2 Takagi–Sugeno–Kang fuzzy control systems (NIT2 TSK FCSs) with adjustable parameters. First,… Click to show full abstract

This paper focuses on the limit cycles prediction problem to discuss the stability analysis of dynamic nonlinear interval type-2 Takagi–Sugeno–Kang fuzzy control systems (NIT2 TSK FCSs) with adjustable parameters. First, in order to alleviate computational burden, a simple architecture of NIT2 TSK FCS using two embedded nonlinear type-1 TSK fuzzy control systems (NT1 TSK FCSs) is proposed. Then, describing function (DF) of NIT2 TSK FCS is obtained based on the DFs of embedded NT1 TSK FCSs. Subsequently, integrating the stability equation and parameter plane approaches provides a solution to identify the limit cycle and the asymptotically stable regions. Moreover, particle swarm optimization technique is applied to minimize the limit cycle region. Furthermore, for robust design, a gain-phase margin tester is utilized to specify the minimum gain margin ( $$\hbox {GM}_{\mathrm{min}}$$ GM min ) and phase margin ( $$\hbox {PM}_{\mathrm{min}}$$ PM min ) when limit cycles can arise. Finally, two simulation examples are considered to validate the advantages of the presented method.

Keywords: tsk; stability analysis; control systems; fuzzy control

Journal Title: Soft Computing
Year Published: 2020

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