scholarly journals Discrete-Time Sliding Mode Control Coupled with Asynchronous Sensor Fusion for Rigid-Link Flexible-Joint Manipulators

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Guangyue Xue ◽  
Xuemei Ren ◽  
Kexin Xing ◽  
Qiang Chen
Keyword(s):  
Sensor Fusion ◽  
Discrete Time ◽  
Tracking Control ◽  
Sliding Mode ◽  
Estimation Error ◽  
Tracking Error ◽  
Sampling Rate ◽  
Experimental Studies ◽  
Flexible Joint ◽  
Rigid Link

This paper proposes a novel discrete-time terminal sliding mode controller (DTSMC) coupled with an asynchronous multirate sensor fusion estimator for rigid-link flexible-joint (RLFJ) manipulator tracking control. A camera is employed as external sensors to observe the RLFJ manipulator’s state which cannot be directly obtained from the encoders since gear mechanisms or flexible joints exist. The extended Kalman filter- (EKF-) based asynchronous multirate sensor fusion method deals with the slow sampling rate and the latency of camera by using motor encoders to cover the missing information between two visual samples. In the proposed control scheme, a novel sliding mode surface is presented by taking advantage of both the estimation error and tracking error. It is proved that the proposed controller achieves convergence results for tracking control in the theoretical derivation. Simulation and experimental studies are included to validate the effectiveness of the proposed approach.

scholarly journals Adaptive Finite-Time Disturbance Observer Based Sliding Mode Control for Dual-Motor Driving System

Complexity ◽  
2018 ◽  
Vol 2018 ◽  
pp. 1-9
Author(s):  
Tianyi Zeng ◽  
Xuemei Ren ◽  
Yao Zhang
Keyword(s):  
Finite Time ◽  
Tracking Control ◽  
Disturbance Observer ◽  
Control Method ◽  
Sliding Mode ◽  
Estimation Error ◽  
Tracking Error ◽  
Sliding Mode Controller ◽  
Driving System ◽  
Surface Technique

This paper investigates a precise tracking control method based on an adaptive disturbance observer for the dual-motor driving system. The unknown matched disturbance is fully considered and estimated in this paper, and the estimation error is proven to be finite-time convergent. A sliding mode controller based on the multiple sliding surface technique is proposed in which the disturbance is compensated. The overall system containing both the observer and the controller is proven to be stable. The tracking error is within the neighbourhood of the origin before the observer completes its convergence and converges to zero thereafter. Simulation results verify the effectiveness of the disturbance observer and the sliding mode controller.

scholarly journals Adaptive Neural Tracking Control of Robotic Manipulators with Guaranteed NN Weight Convergence

Complexity ◽  
2018 ◽  
Vol 2018 ◽  
pp. 1-11 ◽  
Author(s):  
Jun Yang ◽  
Jing Na ◽  
Guanbin Gao ◽  
Chao Zhang
Keyword(s):  
Adaptive Control ◽  
Tracking Control ◽  
Estimation Error ◽  
Tracking Error ◽  
Robotic Manipulators ◽  
Adaptive Laws ◽  
Filter Operation ◽  
Control Response ◽  
Unknown Nonlinear Dynamics ◽  
Acceleration Signals

Although adaptive control for robotic manipulators has been widely studied, most of them require the acceleration signals of the joints, which are usually difficult to measure directly. Although neural networks (NNs) have been used to approximate the unknown nonlinear dynamics in the robotic systems, the conventional adaptive laws for updating the NN weights cannot guarantee that the obtained NN weights converge to their ideal values, which could degrade the tracking control response. To address these two issues, a new adaptive algorithm with the extracted NN weights error is incorporated into adaptive control, where a novel leakage term is superimposed on the gradient method. By using the Lyapunov approach, the convergence of both the tracking error and the estimation error can be guaranteed simultaneously. In addition, two auxiliary functions are introduced to reformulate the robotic model for designing the adaptive law, and a filter operation is used to avoid measuring the acceleration signals. Comparisons to other well-recognized adaptive laws are given, and extensive simulations based on a 2-DOF SCARA robotic system are given to verify the effectiveness of the proposed control strategy.

Fuzzy Sliding-Mode Control of a Variable Geometry Manipulator: Experimental Investigation

2000 ◽  
Author(s):  
J. Choi ◽  
C. W. de Silva ◽  
V. J. Modi ◽  
A. K. Misra
Keyword(s):  
Fuzzy Logic ◽  
Sliding Mode Control ◽  
Sliding Mode ◽  
Tracking Error ◽  
Experimental Studies ◽  
Sliding Mode Controller ◽  
Fuzzy Sliding Mode Control ◽  
Mode Control ◽  
Knowledge Based ◽  
Fuzzy Sliding Mode

Abstract This paper focuses a robust and knowledge-based control approach for multi-link robot manipulator systems. Based on the concepts of sliding-mode control and fuzzy logic control (FLC), a fuzzy sliding-mode controller has been developed in previous work. This controller possesses good robustness properties of sliding-mode control and the flexibility and ‘intelligent’ capabilities of knowledge-based control through the use of fuzzy logic. This paper presents experimental studies with fuzzy sliding-mode control as well as conventional sliding-mode control. The results show that the tracking error is guaranteed to converge to a specification in the presence of uncertainties. The performance of the fuzzy sliding-mode controller is found to be somewhat better than that of the conventional sliding-mode controller.

Discrete-Time Terminal Sliding-Mode Tracking Control With Alleviated Chattering

2019 ◽  
Vol 24 (4) ◽  
pp. 1808-1817 ◽  
Author(s):  
Huazhou Hou ◽  
Xinghuo Yu ◽  
Long Xu ◽  
Raymond Chuei ◽  
Zhenwei Cao
Keyword(s):  
Discrete Time ◽  
Tracking Control ◽  
Sliding Mode ◽  
Terminal Sliding Mode ◽  
Mode Tracking

Design of adaptive fuzzy backstepping sliding mode control for MIMO uncertain discrete-time nonlinear systems based on noisy measurements

2016 ◽  
Vol 24 (2) ◽  
pp. 393-406 ◽  
Author(s):  
Toshio Yoshimura
Keyword(s):  
Nonlinear Systems ◽  
Sliding Mode Control ◽  
Discrete Time ◽  
Sliding Mode ◽  
Weighted Least Squares ◽  
Tracking Error ◽  
Design Parameters ◽  
Adaptive Fuzzy ◽  
Mode Control ◽  
Backstepping Sliding Mode Control

This paper presents an adaptive fuzzy backstepping sliding mode control for multi-input and multi-output uncertain nonlinear systems in semi-strict feedback form. The systems are described by a discrete-time state equation with uncertainties viewed as the modeling errors and the unknown external disturbances, and the observation of the states is taken with independent measurement noises. Combining the adaptive fuzzy backstepping control with the sliding mode control approach for the comprehensive improvement in the stability and the robustness, the adaptive fuzzy backstepping sliding mode control is approximately designed where the design parameters are selected using an appropriate Lyapunov function. The uncertainities are approximated as fuzzy logic systems using the fuzzy inference approach based on the extended single input rule modules to reduce the number of the fuzzy IF-THEN rules. The estimates for the un-measurable states and the adjustable parameters are taken by the proposed simplified weighted least squares estimator. It is proved that the trajectory of the tracking error and the sliding surface is uniformly ultimately bounded. The effectiveness of the proposed approach is indicated through the simulation experiment of a simple numerical system.

An Algorithm for Robust Tracking Control of Robots

Robotica ◽  
1991 ◽  
Vol 9 (1) ◽  
pp. 53-62 ◽  
Author(s):  
Zoran R. Novaković ◽  
Leon Z˘lajpah
Keyword(s):  
Tracking Control ◽  
Error Control ◽  
Sliding Mode ◽  
Tracking Error ◽  
Lyapunov Theory ◽  
Control Synthesis ◽  
Robust Tracking ◽  
Robust Tracking Control ◽  
Time Simulation ◽  
Inverse Kinematics Problem

SUMMARYBased on the Lyapunov theory, a new principle was developed for synthesizing robot tracking control in the presence of model uncertainties. First, a general Lyapunov-like robust tracking concept is presented. It is then used as a basis for the control algorithm derived via a quadratic Lyapunov function constructed using a sliding mode function (based on the output error). Control synthesis is made in task-space, without any need for solving the inverse kinematics problem, i.e. one does not need to inver the Jacobian matrix. It is also shown that the tracking error becomes close to zero in a settling time which is less than a prescribed finite time. Simulation results are incorporated.

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