scholarly journals Disturbance observer–based event-triggered tracking control of networked robot manipulator

2020 ◽  
Vol 53 (5-6) ◽  
pp. 892-898
Author(s):  
Wei Bu ◽  
Ting Li ◽  
Jun Yang ◽  
Yang Yi
Keyword(s):  
Tracking Control ◽  
Measurement Errors ◽  
Disturbance Observer ◽  
Robot Manipulator ◽  
External Disturbance ◽  
Tracking Error ◽  
Control Approach ◽  
Event Triggering ◽  
Small Set ◽  
Event Triggered

We investigate the event-triggered tracking control of networked manipulator in the presence of external disturbance and a variety of system uncertainties. The event-triggered controller is designed by the nonlinear disturbance observer–based control approach, which can dynamically compensate for both errors caused by disturbances and the undesirable effects caused by event-triggering rules. A rigorous Lyapunov stability analysis method is proposed to show that the boundedness of all the signals in the closed-loop system can be guaranteed while in the absence of the input-to-state stability assumption related to measurement errors, tracking error can be constrained to an arbitrarily small set without escaping. Finally, by some simulation results, the feasibility and effectiveness of the proposed control approach is demonstrated.

Fixed-time tracking control for two-link rigid manipulator based on disturbance observer

2021 ◽  
pp. 014233122098363
Author(s):  
Heli Gao ◽  
Mou Chen
Keyword(s):  
Numerical Simulations ◽  
Lyapunov Stability ◽  
Stability Theory ◽  
Tracking Control ◽  
Disturbance Observer ◽  
Inverse Dynamics ◽  
External Disturbance ◽  
Lyapunov Stability Theory ◽  
Fixed Time ◽  
Extended State

This paper studies the fixed-time disturbance estimate and tracking control for two-link manipulators subjected to external disturbance. A fixed-time extended-state disturbance observer (FxTESDO) is proposed by improving the extended state observer. Also, a fixed-time inverse dynamics tracking control (FxTIDTC) scheme based on the FxTESDO is given for two-link manipulators. The fixed-time convergence of the FxTESDO and FxTIDTC is proved by the Lyapunov stability theory and with the aid of the bi-limit homogeneous technique. Numerical simulations are employed to illustrate the effectiveness of the proposed FxTIDTC.

scholarly journals Sliding mode control of the automobile electro-coating conveying mechanism with a nonlinear disturbance observer

2018 ◽  
Vol 10 (9) ◽  
pp. 168781401879574 ◽  
Author(s):  
Wei Yuan ◽  
Guoqin Gao
Keyword(s):  
Sliding Mode Control ◽  
Disturbance Observer ◽  
High Performance ◽  
Sliding Mode ◽  
External Disturbance ◽  
Nonlinear Disturbance Observer ◽  
Control Approach ◽  
Mode Control ◽  
Highly Nonlinear ◽  
Nonlinear Disturbance

The trajectory-tracking performance of the automobile electro-coating conveying mechanism is severely interrupted by highly nonlinear crossing couplings, unmodeled dynamics, parameter variation, friction, and unknown external disturbance. In this article, a sliding mode control with a nonlinear disturbance observer is proposed for high-accuracy motion control of the conveying mechanism. The nonlinear disturbance observer is designed to estimate not only the internal/external disturbance but also the model uncertainties. Based on the output of the nonlinear disturbance observer, a sliding mode control approach is designed for the hybrid series–parallel mechanism. Then, the stability of the closed-loop system is proved by means of a Lyapunov analysis. Finally, simulations with typical desired trajectory are presented to demonstrate the high performance of the proposed composite control scheme.

Adaptive sliding tracking control for nonlinear uncertain robotic systems with unknown actuator nonlinearities

Robotica ◽  
2021 ◽  
pp. 1-20
Author(s):  
Shubo Liu ◽  
Guoquan Liu ◽  
Shengbiao Wu
Keyword(s):  
Control Problem ◽  
Prior Knowledge ◽  
Control Strategy ◽  
Tracking Control ◽  
Disturbance Observer ◽  
Tracking Error ◽  
Small Neighborhood ◽  
Robotic Systems ◽  
Actuator Nonlinearities ◽  
Simulation Results

Abstract This study is concerned with the tracking control problem for nonlinear uncertain robotic systems in the presence of unknown actuator nonlinearities. A novel adaptive sliding controller is designed based on a robust disturbance observer without any prior knowledge of actuator nonlinearities and system dynamics. The proposed control strategy can guarantee that the tracking error eventually converges to an arbitrarily small neighborhood of zero. Simulation results are included to demonstrate the effectiveness and superiority of the proposed strategy.

Adaptive multi-dimensional Taylor network tracking control for a class of switched nonlinear systems with input nonlinearity

2020 ◽  
Vol 42 (13) ◽  
pp. 2482-2491
Author(s):  
Shan-Liang Zhu ◽  
De-Yu Duan ◽  
Lei Chu ◽  
Ming-Xin Wang ◽  
Yu-Qun Han ◽  
...  
Keyword(s):  
Nonlinear Systems ◽  
Tracking Control ◽  
Low Cost ◽  
Tracking Error ◽  
Switched Nonlinear Systems ◽  
Nonlinear Functions ◽  
Input Nonlinearity ◽  
Control Approach ◽  
Adaptive Tracking Control ◽  
Control Scheme

In this paper, a multi-dimensional Taylor network (MTN)-based adaptive tracking control approach is proposed for a class of switched nonlinear systems with input nonlinearity. Firstly, the input nonlinearity is assumed to be bounded by a sector interval. Secondly, with the help of MTNs approximating the unknown nonlinear functions, a novel adaptive MTN control scheme has the advantages of low cost, simple structure and real time feature is developed via backstepping technique. It is shown that the tracking error finally converges to a small domain around the origin and all signals in the closed-loop system are bounded. Finally, two examples are given to demonstrate the effectiveness of the proposed control scheme.

scholarly journals Sliding Mode with Adaptive Control of Robot Manipulator Trajectory Tracking using Neural Network Approximation

2021 ◽  
Vol 10 (6) ◽  
pp. 120
Author(s):  
Monisha Pathak* ◽  
◽  
Dr. Mrinal Buragohain ◽  
Keyword(s):  
Neural Network ◽  
Adaptive Control ◽  
Trajectory Tracking ◽  
Tracking Control ◽  
Sliding Mode ◽  
Robot Manipulator ◽  
Robotic Manipulator ◽  
Adaptive Sliding Mode Control ◽  
Control Approach ◽  
Adaptive Sliding Mode

This paper briefly discusses about the Robust Controller based on Adaptive Sliding Mode Technique with RBF Neural Network (ASMCNN) for Robotic Manipulator tracking control in presence of uncertainities and disturbances. The aim is to design an effective trajectory tracking controller without any modelling information. The ASMCNN is designed to have robust trajectory tracking of Robot Manipulator, which combines Neural Network Estimation with Adaptive Sliding Mode Control. The RBF model is utilised to construct a Lyapunov function-based adaptive control approach. Simulation of the tracking control of a 2dof Robotic Manipulator in the presence of unpredictability and external disruption demonstrates the usefulness of the planned ASMCNN.

scholarly journals Observer-Based Decentralized Tracking Control with Preview Action for a Class of Nonlinear Interconnected Systems

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-18
Author(s):  
Xiao Yu
Keyword(s):  
Tracking Control ◽  
Controller Design ◽  
Tracking Error ◽  
State Feedback Control ◽  
Control Action ◽  
Linear Matrix ◽  
Reference Trajectory ◽  
Integral Control ◽  
Control Approach ◽  
Output Tracking Control

In this paper, for the first time, the observer-based decentralized output tracking control problem with preview action for a class of interconnected nonlinear systems is converted into a regulation problem for N augmented error subsystems composed of the tracking error dynamics, the difference equation of the state observer, and the available future reference trajectory dynamics associated with each individual subsystem. The developed innovative formulation of an observer-based decentralized preview tracking control scheme consists of the integral control action, the observer-based state feedback control action, and the preview action of the desired trajectory. The controller design feasibility conditions are formulated in terms of a linear matrix inequality (LMI) by using the Lyapunov function approach to ensure the existence of the suggested observer-based decentralized control strategy. Furthermore, both decentralized observer gain matrices and decentralized tracking controller gain matrices can be efficiently and simultaneously computed through a one-step LMI procedure. Stability analysis of the closed-loop augmented subsystem is carried out to illustrate that all tracking errors asymptotically converge toward zero. Finally, a numerical example is provided to demonstrate the effectiveness of the suggested control approach.

scholarly journals Improved neural network-based adaptive tracking control for manipulators with uncertain dynamics

2020 ◽  
Vol 17 (4) ◽  
pp. 172988142094756
Author(s):  
Dong-hui Wang ◽  
Shi-jie Zhang
Keyword(s):  
Neural Network ◽  
Radial Basis Function ◽  
Basis Function ◽  
Tracking Control ◽  
Robot Manipulators ◽  
External Disturbance ◽  
Tracking Error ◽  
Adaptive Tracking ◽  
Uncertain Dynamics ◽  
Radial Basis

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.

Adaptive Fractional-Order Fault-Tolerant Tracking Control for UAV Based on High-Gain Observer

2017 ◽  
Author(s):  
Ziquan Yu ◽  
Youmin Zhang ◽  
Yaohong Qu ◽  
Zhewen Xing
Keyword(s):  
Fractional Order ◽  
Tracking Control ◽  
Fault Tolerant ◽  
External Disturbance ◽  
Tracking Error ◽  
Small Region ◽  
High Gain ◽  
Actuator Fault ◽  
High Gain Observer ◽  
Flight Path Angle

This paper is concerned with the fractional-order fault-tolerant tracking control design for unmanned aerial vehicle (UAV) in the presence of external disturbance and actuator fault. Based on the functional decomposition, the dynamics of UAV is divided into velocity subsystem and altitude subsystem. Altitude, flight path angle, pitch angle and pitch rate are involved in the altitude subsystem. By using an adaptive mechanism, the fractional derivative of uncertainty including external disturbance and actuator fault is estimated. Moreover, in order to eliminate the problem of explosion of complexity in back-stepping approach, the high-gain observer is utilized to estimate the derivatives of virtual control signal. Furthermore, by using a fractional-order sliding surface involved with pitch dynamics, an adaptive fractional-order fault-tolerant control scheme is proposed for UAV. It is proved that all signals of the closed-loop system are bounded and the tracking error can converge to a small region containing zero via the Lyapunov analysis. Simulation results show that the proposed controller could achieve good tracking performance in the presence of actuator fault and external disturbance.

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