Robust Adaptive Repetitive Control of Robotic Manipulators

2020 ◽  
Author(s):  
Sheng Zhu ◽  
Mingxuan Sun
Keyword(s):  
Repetitive Control ◽  
Robotic Manipulators ◽  
Robust Adaptive

scholarly journals A Tutorial on Robust Control, Adaptive Control and Robust Adaptive Control—Application to Robotic Manipulators

Inventions ◽  
2019 ◽  
Vol 4 (3) ◽  
pp. 49
Author(s):  
Bin Wei
Keyword(s):  
Adaptive Control ◽  
Robust Control ◽  
Robotic Manipulators ◽  
Joint Space ◽  
Robust Adaptive Control ◽  
Control Techniques ◽  
Operational Space ◽  
Advanced Control ◽  
Robust Adaptive ◽  
Control Application

A tutorial on robust control, adaptive control, robust adaptive control and adaptive control of robotic manipulators is presented in a systematic manner. Some limitations of the above methods are also illustrated. The relationships between the robust control, adaptive control and robust adaptive control are demonstrated. Basic information on the joint space control, operational space control and force control is also given. This tutorial summarizes the most advanced control techniques currently in use in a very simple manner, and applies to robotic manipulators, which can provide an informative guideline for students who have little knowledge of controls or who want to understand the adaptive control of robotics in a systematic way.

BELBIC-Sliding Mode Control of Robotic Manipulators With Uncertainties and Switching Constraints

2016 ◽  
Author(s):  
Sophie Klecker ◽  
Peter Plapper
Keyword(s):  
Sliding Mode Control ◽  
Sliding Mode ◽  
Robotic Manipulators ◽  
Adaptive Controller ◽  
Mode Control ◽  
System A ◽  
Switched Nonlinear System ◽  
Robust Adaptive ◽  
Prior Experiences ◽  
Brain Emotional Learning

This paper addresses the control problem for trajectory tracking of a class of robotic manipulators presenting uncertainties and switching constraints using a biomimetic approach. Uncertainties, system-inherent as well as environmental disturbances deteriorate the performance of the system. A change in constraints between the robot’s end-effector and the environment resulting in a switched nonlinear system, undermines the stable system performance. In this work, a robust adaptive controller combining sliding mode control and BELBIC (Brain Emotional Learning-Based Intelligent Control) is suggested to remediate the expected impacts on the overall system tracking performance and stability. The controller is based on an interplay of inputs relating to environmental information through error-signals of position and sliding surfaces and of emotional signals regulating the learning rate and adapting the future behaviour based on prior experiences. The proposed control algorithm is designed to be applicable to discontinuous freeform geometries. Its stability is proven theoretically and a simulation, performed on a two-link manipulator verifies its efficacy.

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