A neural networks controller for a single-link flexible manipulator based on the inverse dynamics structure

Author(s):  
Z. Su ◽  
K. Khorasani
Author(s):  
Jamil M. Renno

This paper presents a novel method for an inverse dynamics based fuzzy logic controller (FLC) of a single-link flexible manipulator. The control action is distributed between two FLCs: a joint angle controller and a tip controller. A method for varying the ranges of the variables of the two controllers as a function of the motion parameters and the inverse dynamics of the system is presented. Simulation results show that the joint trajectory tracking is accomplished and the residual vibration of the flexible link is suppressed.


2019 ◽  
Vol 41 (13) ◽  
pp. 3612-3625 ◽  
Author(s):  
Wang Qian ◽  
Wang Qiangde ◽  
Wei Chunling ◽  
Zhang Zhengqiang

The paper solves the problem of a decentralized adaptive state-feedback neural tracking control for a class of stochastic nonlinear high-order interconnected systems. Under the assumptions that the inverse dynamics of the subsystems are stochastic input-to-state stable (SISS) and for the controller design, Radial basis function (RBF) neural networks (NN) are used to cope with the packaged unknown system dynamics and stochastic uncertainties. Besides, the appropriate Lyapunov-Krosovskii functions and parameters are constructed for a class of large-scale high-order stochastic nonlinear strong interconnected systems with inverse dynamics. It has been proved that the actual controller can be designed so as to guarantee that all the signals in the closed-loop systems remain semi-globally uniformly ultimately bounded, and the tracking errors eventually converge in the small neighborhood of origin. Simulation example has been proposed to show the effectiveness of our results.


Author(s):  
Kerem Gurses ◽  
Bradley J. Buckman ◽  
Edward J. Park

This paper presents a novel feedback sensing approach for actively suppressing vibrations of a single-link flexible manipulator. Slewing of the flexible link by a rotating hub induces vibrations in the link that persist long after the hub stops rotating. These vibrations are suppressed through a combined scheme of PD-based hub motion control and proposed piezoelectric (PZT) actuator control, which is a composite linear and velocity feedback controller. Lyapunov approach was used to synthesize the controller based on a finite element model of the system. Its realization was possible due to the availability of both linear and angular velocity feedback provided by a unique, commercially-available fiber optic curvature sensor array, called ShapeTape™. It is comprised of an array of fiber optic curvature sensors, laminated on a long, thin ribbon tape, geometrically arranged in such a way that, when it is embedded into the flexible link, the bend and twist of the link’s centerline can be measured. Experimental results show the effectiveness of the proposed approach.


2021 ◽  
Vol 162 ◽  
pp. 104347
Author(s):  
Lewei Tang ◽  
Marc Gouttefarde ◽  
Haining Sun ◽  
Lairong Yin ◽  
Changjiang Zhou

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