Observer-based dynamic surface control for flexible-joint manipulator system with input saturation and unknown disturbance using type-2 fuzzy neural network

In this paper, the nonlinear disturbance observer (NDO) based dynamic surface control (DSC) with interval type-2 fuzzy neural network (IT2FNN) approximator is proposed for flexible-joint manipulator with the input saturation and unknown nonlinear disturbance. The DSC technique has tremendous advanta...

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Vydané v:Neurocomputing (Amsterdam) Ročník 436; s. 162 - 173
Hlavní autori: Hu, Yi, Dian, Songyi, Guo, Rui, Li, Shengchuan, Zhao, Tao
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Elsevier B.V 14.05.2021
Predmet:
Dynamic surface control
Flexible-joint manipulator
Interval type-2 fuzzy system
Neural network
Nonlinear disturbance observer
Interval type-2 fuzzy system
Neural network
Dynamic surface control
Flexible-joint manipulator
Nonlinear disturbance observer
ISSN:0925-2312, 1872-8286
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Popis
Shrnutí:In this paper, the nonlinear disturbance observer (NDO) based dynamic surface control (DSC) with interval type-2 fuzzy neural network (IT2FNN) approximator is proposed for flexible-joint manipulator with the input saturation and unknown nonlinear disturbance. The DSC technique has tremendous advantages in eliminating the ’explosion of complexity’ problem. The IT2FNN approximator is used to deal with parameter uncertainties. The NDO is applied to estimate the unknown external disturbance and compensate the saturation constrain. From Lyapunov stability analysis, it is proved that with the proposed control scheme, all signals of the closed-loop system are semiglobally uniformly ultimately bounded. Simulation results are carried out to demonstrate the effectiveness of the proposed scheme. Compared with the adaptive DSC with neural network (NN) approximator and type-1 fuzzy (T1F) approximator, the tracking error of the proposed control scheme converges to a sufficiently small value.
ISSN:0925-2312
1872-8286
DOI:10.1016/j.neucom.2020.12.121