Robust visual tracking of robot manipulators with uncertain dynamics and uncalibrated camera

In this article, a robust adaptive tracking controller is developed for robot manipulators with uncertain dynamics using radial basis function neural network. The design of tracking control systems for robot manipulators is a highly challenging task due to external disturbance and the uncertainties in their dynamics. The improved radial basis function neural network is chosen to approximate the uncertain dynamics of robot manipulators and learn the upper bound of the uncertainty. The adaptive law based on the Lyapunov stability theory is used to solve the uniform final bounded problem of the radial basis function neural network weights, which guarantees the stability and the consistent bounded tracking error of the closed-loop system. Finally, the simulation results are provided to demonstrate the practicability and effectiveness of the proposed method.

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FUZZY LOGIC-BASED INVERSE DYNAMIC MODELLING OF ROBOT MANIPULATORS

Transactions of the Canadian Society for Mechanical Engineering ◽

10.1139/tcsme-2010-0009 ◽

2010 ◽

Vol 34 (1) ◽

pp. 137-150 ◽

Cited By ~ 1

Author(s):

Meysar Zeinali ◽

Leila Notash

Keyword(s):

Fuzzy Logic ◽

Dynamic Model ◽

Parallel Manipulator ◽

Inverse Dynamics ◽

Robot Manipulators ◽

Dynamic Modelling ◽

Inverse Dynamic ◽

Model Based ◽

Uncertain Dynamics ◽

Modelling Methodology

This paper presents the design and implementation of a systematic fuzzy modelling methodology for the inverse dynamic modelling of robot manipulators. The fuzzy logic modelling methodology is motivated in part by the difficulties encountered in the modelling of complex nonlinear uncertain systems, and by the objective of developing an efficient dynamic model for the real-time model-based control. The methodology is applied to build the fuzzy logic-based inverse dynamic model of a prototyped wire-actuated parallel manipulator with uncertain dynamics. The developed inverse dynamics has been used in a fuzzy model-based adaptive robust controller for the tracking control of the parallel manipulator.

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A Novel Fast Terminal Sliding Mode Tracking Control Methodology for Robot Manipulators

Applied Sciences ◽

10.3390/app10093010 ◽

2020 ◽

Vol 10 (9) ◽

pp. 3010 ◽

Cited By ~ 3

Author(s):

Quang Vinh Doan ◽

Anh Tuan Vo ◽

Tien Dung Le ◽

Hee-Jun Kang ◽

Ngoc Hoai An Nguyen

Keyword(s):

Tracking Control ◽

High Performance ◽

Control Method ◽

Sliding Mode ◽

Robot Manipulators ◽

Convergence Time ◽

Trajectory Tracking Control ◽

Terminal Sliding Mode ◽

Uncertain Dynamics ◽

Fast Terminal Sliding Mode

This paper comes up with a novel Fast Terminal Sliding Mode Control (FTSMC) for robot manipulators. First, to enhance the response, fast convergence time, against uncertainties, and accuracy of the tracking position, the novel Fast Terminal Sliding Mode Manifold (FTSMM) is developed. Then, a Supper-Twisting Control Law (STCL) is applied to combat the unknown nonlinear functions in the control system. By using this technique, the exterior disturbances and uncertain dynamics are compensated more rapidly and more correctly with the smooth control torque. Finally, the proposed controller is launched from the proposed sliding mode manifold and the STCL to provide the desired performance. Consequently, the stabilization and robustness criteria are guaranteed in the designed system with high-performance and limited chattering. The proposed controller runs without a precise dynamic model, even in the presence of uncertain components. The numerical examples are simulated to evaluate the effectiveness of the proposed control method for trajectory tracking control of a 3-Degrees of Freedom (DOF) robotic manipulator.

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Adaptive Fast Nonsingular Fixed-Time Tracking Control for Robot Manipulators

Complexity ◽

10.1155/2021/6629993 ◽

2021 ◽

Vol 2021 ◽

pp. 1-16

Author(s):

Huihui Pan ◽

Guangming Zhang

Keyword(s):

Trajectory Tracking ◽

Tracking Control ◽

Control Method ◽

Sliding Mode ◽

Robot Manipulators ◽

Fixed Time ◽

Convergence Time ◽

Trajectory Tracking Control ◽

Uncertain Dynamics ◽

Adaptive Technique

This paper studies the fixed-time trajectory tracking control problem of robot manipulators in the presence of uncertain dynamics and external disturbances. First, a novel nonsingular fixed-time sliding mode surface is presented, which can ensure that the convergence time of the suggested surface is bounded regardless of the initial states. Subsequently, a novel fast nonsingular fixed-time sliding mode control (NFNFSMC) is developed so that the closed-loop system is fixed-time convergent to the equilibrium. By applying the proposed NFNFSMC method and the adaptive technique, a novel adaptive nonsingular fixed-time control scheme is proposed, which can guarantee fast fixed-time convergence of the tracking errors to small regions around the origin. With the proposed control method, the lumped disturbance is compensated by the adaptive technique, whose prior information about the upper bound is not needed. The fixed-time stability of the trajectory tracking control under the proposed controller is proved by the Lyapunov stability theory. Finally, corresponding simulations are given to illustrate the validity and superiority of the proposed control approach.

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