Combined Neural Network Feedforward and RISE Feedback Control Structure for a 5 DOF Upper-limb Exoskeleton Robot with Asymptotic Tracking
Publish place: Journal of Advances in Computer Research، Vol: 6، Issue: 1
Publish Year: 1393
نوع سند: مقاله ژورنالی
زبان: English
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شناسه ملی سند علمی:
JR_JACR-6-1_005
تاریخ نمایه سازی: 16 شهریور 1395
Abstract:
Control of robotic systems is an interesting subject due to their wide spectrum applications in medicine, aerospace and other industries. This paper proposes a novel continuous control mechanism for tracking problem of a 5-DOF upper-limb exoskeleton robot. The proposed method is a combination of a recently developed robust integral of the sign of the error (RISE) feedback and neural network (NN) feed-forward terms. The feed-forward NN learns nonlinear dynamics of the system and compensates for uncertainties while the NN approximation error and nonlinear bounded disturbances are overcome by the RISE term. Typical NN-based controllers generally result in uniformly ultimately bounded (UUB) stability due to the NN reconstruction error. In this paper to eliminate this error and achieve asymptotic tracking, the RISE feedback term is integrated into the NN compensator. Finally, a comparative study on the system performance is conducted between the proposed control strategy and two other conventional control methods. Simulation results illustrate the effectiveness of the proposed method.
Keywords:
Robust integral of the sign of the error (RISE) feedback , Neural network (NN) , Feed-forward compensation , 5-DOF upper-limb exoskeleton robot , Asymptotic tracking
Authors
Marzieh Yazdanzad
Department of Electrical and Computer Engineering, Noshirvani Univ. of Technology, Babol, Iran
Alireza Khosravi
Department of Electrical and Computer Engineering, Noshirvani Univ. of Technology, Babol, Iran
Reza Ghaderi
Department of Control Engineering, Shahid Beheshti Univ., Tehran, Iran
Pouria Sarhadi
Department of Electrical and Computer Engineering, Noshirvani Univ. of Technology, Babol, Iran