scholarly journals Optimal Fuzzy Impedance Control for a Robot Gripper Using Gradient Descent Iterative Learning Control in Fuzzy Rule Base Design

2020 ◽  
Vol 10 (11) ◽  
pp. 3821 ◽  
Author(s):  
Ba-Phuc Huynh ◽  
Yong-Lin Kuo
Keyword(s):  
Real Time ◽  
Iterative Learning Control ◽  
Control Method ◽  
Impedance Control ◽  
Learning Control ◽  
Iterative Learning ◽  
Rule Base ◽  
Control Approach ◽  
Robot Gripper ◽  
Gripping Force

This paper proposes a novel control approach for a robot gripper in which the impedance control, fuzzy logic control, and iterative learning control are combined in the same control schema. The impedance control is used to keep the gripping force at the desired value. The fuzzy impedance controller is designed to estimate the best impedance parameters in real time when gripping unknown objects. The iterative learning control process is employed to optimize the sample dataset for designing the rule base to enhance the effectiveness of the fuzzy impedance controller. Besides, the real-time gripping force estimator is designed to keep an unknown object from sliding down when picking it up. The simulation and experiment are implemented to verify the proposed method. The comparison with another control method is also made by repeating the experiments under equivalent conditions. The results show the feasibility and superiority of the proposed method.

scholarly journals An adaptive iterative learning control approach based on disturbance estimation for manipulator system

2019 ◽  
Vol 16 (3) ◽  
pp. 172988141985219
Author(s):  
Keping Liu ◽  
Yuanyuan Chai ◽  
Zhongbo Sun ◽  
Yan Li
Keyword(s):  
Trajectory Tracking ◽  
Iterative Learning Control ◽  
Control Method ◽  
Learning Control ◽  
Iterative Learning ◽  
Uncertain Parameters ◽  
External Disturbances ◽  
Adaptive Iterative Learning Control ◽  
Control Approach ◽  
Disturbance Estimation

An adaptive iterative learning control approach based on disturbance estimation has been developed for trajectory tracking of manipulators with uncertain parameters and external disturbances. The external disturbances are estimated by the feedback iterative learning method, whereas the uncertain parameters are compensated by adaptive control. This approach which is based on the disturbance estimation technique provides a rapid convergence of trajectory tracking errors. According to the Lyapunov theory, the sufficient condition of the asymptotic stability has been developed for the 2-degrees of freedom (DOFs) manipulator system. The numerical results show that the adaptive iterative learning control approach based on disturbance estimation is feasible and effective for the 2-DOFs manipulator. A comparison of the adaptive iterative learning control method and the iterative learning control method is completed, which shows that the adaptive iterative learning control method performs a faster convergence of the disturbance to the steady state.

Eliminating Structural Error in Real-Time Adjustable Four-Bar Path Generators Using Iterative Learning Control

2004 ◽  
Author(s):  
Hong-Jen Chen ◽  
Richard W. Longman ◽  
Meng-Sang Chew
Keyword(s):  
Control Systems ◽  
Real Time ◽  
Iterative Learning Control ◽  
Learning Control ◽  
Iterative Learning ◽  
Path Generation ◽  
Structural Error ◽  
Four Bar Linkage

Fundamental concepts of Iterative Learning Control (ILC) are applied to path generating problems in mechanisms. As an illustration to such class of problems, an adjustable four-bar linkage is used. The coupler point of a four-bar traces a coupler curve that will in general deviate from the desired coupler path. Except at the precision points, the coupler curve will exhibit some structural error, which is the deviation from the specified curve. The structural error will repeat itself every cycle at exactly the same points over the range of interest. Since ILC is a methodology that was developed to handle similar repetitive errors in control systems, it is believed that it will be well served to apply it to this class of problems. Results show that ILC can be simple to implement, and it is found to be very well suited for such path generation problems.

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