scholarly journals Research on a LADRC Strategy for Trajectory Tracking Control of Delta High-Speed Parallel Robots

2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
Cheng Liu ◽  
Yanming Cheng ◽  
Dejun Liu ◽  
Guohua Cao ◽  
Ilkyoo Lee
Keyword(s):  
Trajectory Tracking ◽  
High Speed ◽  
External Disturbance ◽  
Parallel Robot ◽  
Parallel Robots ◽  
System Stability ◽  
External Disturbances ◽  
Trajectory Tracking Control ◽  
Disturbance Rejection Control ◽  
Control Scheme

In order to better track the planned trajectory of Delta high-speed parallel robot, this paper proposes a dynamics control strategy for Delta high-speed parallel robots based on the linear active disturbance rejection control (LADRC) strategy which realizes decoupling control through observing and compensating the coupling and internal and external disturbances between the three joints. Firstly, the structure and dynamics model of the Delta high-speed parallel robot are analyzed, respectively. Secondly, the control scheme of the Delta high-speed parallel robot dynamic LADRC strategy is constructed, and then, the system stability is analyzed. Taking a representative 8-shaped space helical variance trajectory as a given input of the system and a triangular wave as an external disturbance as given disturbance input of the system, simulations are carried out to demonstrate the effectiveness of the proposed LADRC strategy; results indicate that the system with the LADRC strategy has a good quick and precise real-time trajectory tracking and strong robustness.

Optimal Trajectory Tracking Control With a 5R Parallel Robot

2011 ◽  
Author(s):  
Gianmarc Coppola ◽  
Dan Zhang
Keyword(s):  
Trajectory Tracking ◽  
Feedforward Neural Networks ◽  
Parameter Tuning ◽  
Parallel Robot ◽  
Parallel Robots ◽  
Automatic Tuning ◽  
Trajectory Tracking Control ◽  
Model Reference Control ◽  
Control Scheme ◽  
Optimal Trajectory Tracking Control

This work examines the control characteristics of a 5R parallel robotic manipulator subjected to two control studies. Firstly, fundamental aspects of dynamics are presented. Then a brief review of Particle Swarm Optimization (PSO) and feedforward Neural Networks (NN) is undertaken. Subsequently, to tackle the challenging problem of controller parameter tuning for parallel robots in trajectory tracking scenarios, a multi objective optimization problem is formulated for automatic tuning using PSO. This offline method is comparatively evaluated to the Nelder-Mead (NM) sequential simplex optimization scheme. Several results are attained illustrating the strengths and weaknesses of this method for parallel robot control. Then, an adaptive NN model reference control scheme using PSO is proposed. This scheme is proposed as one possible way to take advantage of the strong properties of the PSO online. The scheme is tested and several observations are outlined.

scholarly journals Fixed-Time Trajectory Tracking Control of Autonomous Surface Vehicle with Model Uncertainties and Disturbances

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-10
Author(s):  
Jiawen Cui ◽  
Haibin Sun
Keyword(s):  
Trajectory Tracking ◽  
Tracking Control ◽  
Sliding Mode ◽  
Fixed Time ◽  
Convergence Time ◽  
Model Uncertainties ◽  
External Disturbances ◽  
Trajectory Tracking Control ◽  
Integral Sliding Mode ◽  
Control Scheme

The issue of fixed-time trajectory tracking control for the autonomous surface vehicles (ASVs) system with model uncertainties and external disturbances is investigated in this paper. Particularly, convergence time does not depend on initial conditions. The major contributions include the following: (1) An integral sliding mode controller (ISMC) via integral sliding mode surface is first proposed, which can ensure that the system states can follow the desired trajectory within a fixed time. (2) Unknown external disturbances are absolutely estimated by means of designing a fixed-time disturbance observer (FTDO). By combining the FTDO and ISMC techniques, a new control scheme (FTDO-ISMC) is developed, which can achieve both disturbance compensation and chattering-free condition. (3) Aiming at reconstructing the unknown nonlinear dynamics and external disturbances, a fixed-time unknown observer (FTUO) is proposed, thus providing the FTUO-ISMC scheme that finally achieves trajectory tracking of ASVs with unknown parameters. Finally, simulation tests and detailed comparisons indicate the effectiveness of the proposed control scheme.

Vibration Suppression for Large-Scale Flexible Structures Using Deep Reinforcement Learning Based on Cable-Driven Parallel Robots

2020 ◽  
Author(s):  
Haining Sun ◽  
Xiaoqiang Tang ◽  
Jinhao Wei
Keyword(s):  
Reinforcement Learning ◽  
Large Scale ◽  
Vibration Suppression ◽  
External Disturbance ◽  
Flexible Structures ◽  
Parallel Robot ◽  
Parallel Robots ◽  
Gradient Algorithm ◽  
Normal Operation ◽  
Control Scheme

Abstract Specific satellites with ultra-long wings play a crucial role in many fields. However, external disturbance and self-rotation could result in undesired vibrations of flexible wings, which affects the normal operation of the satellites. In severe cases, the satellites will be damaged. Therefore, it is imperative to conduct vibration suppression for these flexible structures. Utilizing deep reinforcement learning (DRL), an active control scheme is presented in this paper to rapidly suppress the vibration of flexible structures with quite small controllable force based on a cable-driven parallel robot (CDPR). To verify the controller’s effectiveness, three groups of simulation with different initial disturbance are implemented. Besides, to enhance the contrast, a passive pre-tightening scheme is also tested. First, the dynamic model of the CDPR that is comprised of four cables and a flexible structure is established using the finite element method. Then, the dynamic behavior of the model under the controllable cable force is analyzed by Newmark-ß method. Furthermore, the agent of DRL is trained by the deep deterministic policy gradient algorithm (DDPG). Finally, the control scheme is conducted on Simulink environment to evaluate its performance, and the results are satisfactory, which validates the controller’s ability to suppress vibrations.

Trajectory tracking control of delta parallel robot based on disturbance observer

2020 ◽  
pp. 095965182097482
Author(s):  
Mingkun Wu ◽  
Jiangping Mei ◽  
Jinlu Ni ◽  
Weizhong Hu
Keyword(s):  
Dynamic Model ◽  
Trajectory Tracking ◽  
Disturbance Observer ◽  
High Speed ◽  
Parallel Robot ◽  
Tracking Accuracy ◽  
Trajectory Tracking Control ◽  
Uncertain Dynamics ◽  
High Acceleration ◽  
Highly Nonlinear

Delta parallel robot is widely used in the manufacturing process of food, medicine, electronics and military industries, which is a highly nonlinear system with strongly uncertain dynamics. Therefore, there are many difficulties in the controller design of delta robot. Based on the simplified dynamic model, a nonlinear PD+ controller with nonlinear disturbance observer is proposed for Delta parallel robot in this article, which can realize high-precision trajectory tracking in high-speed and high-acceleration motion. Then, the asymptotic stability of the closed-loop system’s equilibrium point is proven by utilizing Lyapunov techniques and LaSalle’s invariance theorem. It is obvious that the proposed controller is significantly less dependent on the accuracy of the dynamic model. Besides, a disturbance observer based on the generalized momentum is constructed, which can effectively observe and compensate the disturbances. What’s more, the constructed disturbance observer avoids the calculation of the inverse of inertia matrix, which will greatly improve the response speed of the controller. The simulation results show that the proposed controller can assure better trajectory tracking accuracy in high-speed and high-acceleration motion. And the disturbance observer can effectively estimate the disturbance. The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article:This work was supported by the National Natural Science Foundation of China (grant number51474320).

scholarly journals ADP based trajectory-tracking control via backstepping method for underactuated AUV with unknown dynamics

2021 ◽  
Author(s):  
Gaofeng Che ◽  
Zhen Yu
Keyword(s):  
Neural Network ◽  
Control Problem ◽  
Dynamic Model ◽  
Trajectory Tracking ◽  
Tracking Control ◽  
Autonomous Underwater Vehicles ◽  
System Stability ◽  
Trajectory Tracking Control ◽  
Control Scheme ◽  
Underactuated Auv

Abstract This paper investigates trajectory-tacking control problem for underactuated autonomous underwater vehicles (AUV) with unknown dynamics. Different from existing adaptive dynamic programming (ADP) schemes, our proposed control scheme can achieve high-level system stability and tracking control accuracy. Firstly, the backstepping approach is introduced into the kinematic model of underactuated AUV and produces a virtual velocity control which is taken as the desired velocity input of the dynamic model of underactuated AUV. Secondly, the error tracking system is constructed according to the dynamic model of underactuated AUV. Thirdly, the critic neural network and the action neural network are employed to transform the trajectory-tracking control problem into optimal control problem based on policy iteration algorithm. At last simulation results are given to verify the effectiveness of the control scheme proposed in this paper.

scholarly journals Integral Backstepping Control of Induction Machine

2021 ◽  
Vol 23 (4) ◽  
pp. 345-351
Author(s):  
Abdelhak Benheniche ◽  
Farid Berrezzek
Keyword(s):  
High Speed ◽  
Induction Machine ◽  
Lyapunov Theory ◽  
System Stability ◽  
External Disturbances ◽  
Control Approach ◽  
Integral Action ◽  
Resistance Variation ◽  
Control Scheme ◽  
Rotor Flux

The goal of this work is to propose a latest design of a rotor speed and rotor flux modulus control approach for an induction machine using a Backstepping corrector with an integral action. The advantage of the Backstepping Strategy is the ability to manage a nonlinear system. The Lyapunov theory has been used to ensure the system stability. To improve the controller robustness proprieties the integral action is used, despite the system uncertainties and the existence of external disturbances. The unavailable rotor flux is recovered by estimation of the rotor flux of the machine based on the integration of the stator voltage expressions. The simulation results illustrate the effectiveness of the proposed control scheme under load disturbances, rotor resistance variation and low and high speed.

scholarly journals Trajectory tracking control of a quadrotor UAV based on sliding mode active disturbance rejection control

2019 ◽  
Vol 24 (4) ◽  
Author(s):  
Yong Zhang ◽  
Zengqiang Chen ◽  
Mingwei Sun ◽  
Xinghui Zhang
Keyword(s):  
Trajectory Tracking ◽  
Disturbance Rejection ◽  
Tracking Control ◽  
Sliding Mode ◽  
Reference Trajectory ◽  
Active Disturbance Rejection Control ◽  
Trajectory Tracking Control ◽  
Active Disturbance Rejection ◽  
Disturbance Rejection Control ◽  
Control Scheme

This paper proposes a sliding mode active disturbance rejection control scheme to deal with trajectory tracking control problems for the quadrotor unmanned aerial vehicle (UAV). Firstly, the differential signal of the reference trajectory can be obtained directly by using the tracking differentiator (TD), then the design processes of the controller can be simplified. Secondly, the estimated values of the UAV's velocities, angular velocities, total disturbance can be acquired by using extended state observer (ESO), and the total disturbance of the system can be compensated in the controller in real time, then the robustness and anti-interference capability of the system can be improved. Finally, the sliding mode controller based on TD and ESO is designed, the stability of the closed-loop system is proved by Lyapunov method. Simulation results show that the control scheme proposed in this paper can make the quadrotor track the desired trajectory quickly and accurately.

Robust finite-time trajectory tracking control for a space manipulator with parametric uncertainties and external disturbances

2021 ◽  
pp. 095441002110147
Author(s):  
Qijia Yao
Keyword(s):  
Trajectory Tracking ◽  
Finite Time ◽  
Tracking Control ◽  
Disturbance Observer ◽  
Control Method ◽  
Parametric Uncertainties ◽  
External Disturbances ◽  
Trajectory Tracking Control ◽  
Space Manipulator ◽  
Tracking Controller

Space manipulator is considered as one of the most promising technologies for future space activities owing to its important role in various on-orbit serving missions. In this study, a robust finite-time tracking control method is proposed for the rapid and accurate trajectory tracking control of an attitude-controlled free-flying space manipulator in the presence of parametric uncertainties and external disturbances. First, a baseline finite-time tracking controller is designed to track the desired position of the space manipulator based on the homogeneous method. Then, a finite-time disturbance observer is designed to accurately estimate the lumped uncertainties. Finally, a robust finite-time tracking controller is developed by integrating the baseline finite-time tracking controller with the finite-time disturbance observer. Rigorous theoretical analysis for the global finite-time stability of the whole closed-loop system is provided. The proposed robust finite-time tracking controller has a relatively simple structure and can guarantee the position and velocity tracking errors converge to zero in finite time even subject to lumped uncertainties. To the best of the authors’ knowledge, there are really limited existing controllers can achieve such excellent performance under the same conditions. Numerical simulations illustrate the effectiveness and superiority of the proposed control method.

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