Adaptive fuzzy prescribed performance control for a class of uncertain chaotic economical system

Author(s):  
Ling Li ◽  
Yeguo Sun
2020 ◽  
Vol 2020 ◽  
pp. 1-10
Author(s):  
Xudong Cao ◽  
Jianjun Wang ◽  
Wei Xiang

This paper proposes an adaptive fuzzy prescribed performance control (PPC) method of a class of uncertain nonlinear systems. Different from the traditional PPC approach that requires the exact values of the initial conditions, by using a new type of performance function, the proposed PPC scheme together with a composite adaptation law works effectively even without the knowledge of initial conditions. Meanwhile, the constructed disturbance observer and fuzzy logic systems can estimate system uncertainties including external disturbances and fuzzy approximation errors. Under the proposed tracking controller, the boundedness of all involved signals is guaranteed, and the tracking errors satisfy the prescribed performance bounds all the time. Finally, simulation results show the efficacy of the proposed method.


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