Adaptive neural dynamic surface control for flexible joint manipulator with prescribed performance

2017 ◽  
Author(s):  
Min Wang ◽  
Huiping Ye
Keyword(s):  
Dynamic Surface Control ◽  
Neural Dynamic ◽  
Dynamic Surface ◽  
Flexible Joint ◽  
Prescribed Performance ◽  
Surface Control ◽  
Flexible Joint Manipulator

scholarly journals Spiking-Free HGO-Based Dynamic Surface Control for Flexible Joint Manipulator with Unmeasurable States

2020 ◽  
Author(s):  
Dezhi Kong ◽  
Wendong Wang ◽  
Yikai Shi
Keyword(s):  
High Gain ◽  
Dynamic Surface Control ◽  
Lyapunov Theory ◽  
System Stability ◽  
Dynamic Surface ◽  
Flexible Joint ◽  
Surface Control ◽  
Estimation Of Uncertainties ◽  
Flexible Joint Manipulator ◽  
Manipulator Control

Abstract For the flexible joint manipulator control system (FJMCS) with unmeasurable states, a novel partial states feedback control (PSFC) is proposed. Firstly, the unmeasurable states and the uncertainties are observed by a high-gain observer (HGO) simultaneously. Then, a dynamic surface controller is proposed based on the output of the HGO. The newly proposed controller has several advantages over existing methods. First, the proposed controller not only uses the estimate states to avoid using unmeasurable states, but also uses the estimation of uncertainties to enhance the robustness of FJMCS. Second, a novel spike suppression function (SSF) is developed to avoid the estimation spike problem in the existing HGO-based controllers. The closed-loop system stability is proved by the Lyapunov theory. Simulation results demonstrate the effectiveness of the proposed controller.

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