Adaptive Extended Computed Torque Control of 3 DOF Planar Parallel Manipulators Using Neural Network and Error Compensator

Le, Quang Dan; Kang, Hee-Jun; Le, Tien Dung

doi:10.1007/978-3-319-42297-8_41

Cited by 5 publications

(2 citation statements)

References 13 publications

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“…Adaptive control, a robotic control method that differs from conventional control methods presents that the controller's parameters change over time. Moreover, they are calibrated based on the feedback signals in the closed loop [7][8][9]. This control method is also proper as the dynamic parameters of the robot are incorrect [5].…”

Section: Introductionmentioning

confidence: 99%

Designing Hedge Algebraic Controller and Optimizing by Genetic Algorithm for Serial Robots Adhering Trajectories

Duy

Vuong²

2020

JCC

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In recent years, the application of hedge algebras in the field of control has been studied. The results show that this approach has many advantages. In additions, industrial robots are being well-developed and extensively used, especially in the industrial revolution 4.0. Accurate control of industrial robots is a class of problems that many scientists are interested in. In this paper, we design a controller based on hedge algebra for serial robots. The control rule is given by linguistic rule base system. The goal is to accurately control the moving robot arm which adheres given trajectories. Optimization of fuzzy parameters for the controller is done by genetic algorithms. The system has been simulated on the Matlab-Simulink software. The simulation results show that the orbital deviation is very small. Moreover, the controller worked well with correct control quality. This result once presents the simplicity and efficiency of the hedge algebras approach to control.

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Section: Introductionmentioning

confidence: 99%

Designing Hedge Algebraic Controller and Optimizing by Genetic Algorithm for Serial Robots Adhering Trajectories

Duy

Vuong²

2020

JCC

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“…Adaptive methods based on intelligent techniques using neural network for robot manipulator have been proposed by many researchers [9][10]. Most researches are based on feed forward neural network which has some drawbacks such local minimum, slow convergence and the difficulty of choosing learning rate and initial weight values.…”

Section: Introductionmentioning

confidence: 99%

An Adaptive Controller with An Orthogonal Neural Network and A Third Order Sliding Mode Observer for Robot Manipulators

Le¹,

Kang²,

Le³

2016

IJMERR

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In this paper, An adaptive controller with an orthogonal neural network (ONN) and a third order sliding mode(TOSM) observer for robot manipulators is proposed. Firstly, the TOSM observer is designed to observe joint velocities. Then, the ONN is designed to compensate robot dynamic uncertainties on line inside a computed torque control structure. Therefore, the proposed controller allows only position measurements due to the TOSM observer and achieve highly accurate trajectory tracking performance due to the ONN's uncertainty compensation. Finally, computer simulation for a 2-DOF manipulator is performed to show verify the effectiveness of the proposed controller.  Index Terms-orthogonal neural network, third order sliding mode observers, on line dynamic compensation

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Control Parallel Robots Driven by DC Motors Using Fuzzy Sliding Mode Controller and Optimizing Parameters by Genetic Algorithm

Vuong

Hoang

Duy

2019

Advances in Engineering Research and Application

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Adaptive Extended Computed Torque Control of 3 DOF Planar Parallel Manipulators Using Neural Network and Error Compensator

Cited by 5 publications

References 13 publications

Designing Hedge Algebraic Controller and Optimizing by Genetic Algorithm for Serial Robots Adhering Trajectories

Designing Hedge Algebraic Controller and Optimizing by Genetic Algorithm for Serial Robots Adhering Trajectories

An Adaptive Controller with An Orthogonal Neural Network and A Third Order Sliding Mode Observer for Robot Manipulators

Control Parallel Robots Driven by DC Motors Using Fuzzy Sliding Mode Controller and Optimizing Parameters by Genetic Algorithm

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