Neural network-based adaptive controller design of robotic manipulators with an observer

2001 ◽  
Vol 12 (1) ◽  
pp. 54-67 ◽  
Author(s):  
Fuchun Sun ◽  
Zengqi Sun ◽  
Peng-Yung Woo
Keyword(s):  
Neural Network ◽  
Controller Design ◽  
Robotic Manipulators ◽  
Adaptive Controller

scholarly journals Fractional-order fuzzy adaptive controller design for uncertain robotic manipulators

2019 ◽  
Vol 16 (2) ◽  
pp. 172988141984022 ◽  
Author(s):  
Yanping Deng
Keyword(s):  
Fuzzy Control ◽  
Fractional Order ◽  
Controller Design ◽  
Sliding Mode ◽  
Main Idea ◽  
Robotic Manipulators ◽  
Adaptive Controller ◽  
Small Region ◽  
Trajectory Tracking Control ◽  
Integer Order

A sliding mode adaptive fractional fuzzy control is provided in this article to achieve the trajectory tracking control of uncertain robotic manipulators. By adaptive fractional fuzzy control, we mean that fuzzy parameters are updated through fractional-order adaptation laws. The main idea of this work consists in using fractional input to control complex integer-order nonlinear systems. An adaptive fractional fuzzy control that guarantees tracking errors tend to an arbitrary small region is established. To facilitate the stability analysis, fractional-order integral Lyapunov functions are proposed, and the integer-order Lyapunov stability criterion is used. Finally, simulation results are presented to show the effectiveness of the proposed method.

scholarly journals Adaptive backstepping controller design based on neural network for PMSM speed control

2021 ◽  
Vol 12 (3) ◽  
pp. 1940
Author(s):  
E. Sabouni ◽  
B. Merah ◽  
I. K. Bousserhane
Keyword(s):  
Neural Network ◽  
Control Algorithm ◽  
Controller Design ◽  
Classical Method ◽  
Permanent Magnet Synchronous Motor ◽  
Adaptive Controller ◽  
Nonlinear Controller ◽  
Adaptive Backstepping ◽  
Backstepping Controller ◽  
Adaptive Backstepping Controller

<span lang="EN-US">The aim of this research is the speed tracking of the permanent magnet synchronous motor (PMSM) using an intelligent Neural-Network based adapative backstepping control. First, the model of PMSM in the Park synchronous frame is derived. Then, the PMSM speed regulation is investigated using the classical method utilizing the field oriented control theory. Thereafter, a robust nonlinear controller employing an adaptive backstepping strategy is investigated in order to achieve a good performance tracking objective under motor parameters changing and external load torque application. In the final step, a neural network estimator is integrated with the adaptive controller to estimate the motor parameters values and the load disturbance value for enhancing the effectiveness of the adaptive backstepping controller. The robsutness of the presented control algorithm is demonstrated using simulation tests. The obtained results clearly demonstrate that the presented NN-adaptive control algorithm can provide good trackingperformances for the speed trackingin the presence of motor parameter variation and load application.</span>

Neural network adaptive control of nonlinear systems preceded by hysteresis

2020 ◽  
Vol 32 (1) ◽  
pp. 104-112
Author(s):  
Xinlong Zhao ◽  
Qiang Su ◽  
Shengxin Chen ◽  
Yonghong Tan
Keyword(s):  
Neural Network ◽  
Adaptive Control ◽  
Controller Design ◽  
Experimental Tests ◽  
Adaptive Controller ◽  
Auxiliary Variable ◽  
Proposed Model ◽  
And Control ◽  
Novel Model ◽  
Hysteresis Characteristics

Neural network adaptive control is proposed for a class of nonlinear system preceded by hysteresis. A novel model is developed to represent the hysteresis characteristics in explicit form. Furthermore, the auxiliary variable of the proposed model is proved to be bounded, which is essential for controller design. Then, neural network adaptive controller is directly applied to mitigate the influence of the hysteresis without constructing the hysteresis inverse. The updated law and control law of the controllers are derived from Lyapunov stability theorem, so that the boundedness of the close-loop system is guaranteed. Finally, the experimental tests are carried out to validate the effectiveness of the proposed approach.

Neural adaptive controller design of robotic manipulators with an observer

1999 ◽  
Vol 32 (2) ◽  
pp. 5485-5490
Author(s):  
Fuchun Sun ◽  
Zengqi Sun ◽  
PengYung Woo ◽  
Zhengdong Zhang
Keyword(s):  
Controller Design ◽  
Robotic Manipulators ◽  
Adaptive Controller
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