scholarly journals A Q-Learning-Based Parameters Adaptive Algorithm for Formation Tracking Control of Multi-Mobile Robot Systems

Complexity ◽  
2022 ◽  
Vol 2022 ◽  
pp. 1-19
Author(s):  
Chen Zhang ◽  
Wen Qin ◽  
Ming-Can Fan ◽  
Ting Wang ◽  
Mou-Quan Shen

This paper proposes an adaptive formation tracking control algorithm optimized by Q-learning scheme for multiple mobile robots. In order to handle the model uncertainties and external disturbances, a desired linear extended state observer is designed to develop an adaptive formation tracking control strategy. Then an adaptive method of sliding mode control parameters optimized by Q-learning scheme is employed, which can avoid the complex parameter tuning process. Furthermore, the stability of the closed-loop control system is rigorously proved by means of matrix properties of graph theory and Lyapunov theory, and the formation tracking errors can be guaranteed to be uniformly ultimately bounded. Finally, simulations are presented to show the proposed algorithm has the advantages of faster convergence rate, higher tracking accuracy, and better steady-state performance.

2018 ◽  
Vol 2018 ◽  
pp. 1-13 ◽  
Author(s):  
Yaoyao Wang ◽  
Kangwu Zhu ◽  
Bai Chen ◽  
Hongtao Wu

In this paper, we propose a novel model-free trajectory tracking control for robot manipulators under complex disturbances. The proposed method utilizes time delay control (TDC) as its control framework to ensure a model-free scheme and uses adaptive nonsingular terminal sliding mode (ANTSM) to obtain high control accuracy and fast dynamic response under lumped disturbance. Thanks to the application of adaptive law, the proposed method can ensure high tracking accuracy and effective suppression of noise effect simultaneously. Stability of the closed-loop control system is proved using Lyapunov method. Finally, the effectiveness and advantages of the newly proposed TDC scheme with ANTSM dynamics are verified through several comparative simulations.


Sensors ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1416
Author(s):  
Guang-Hui Xu ◽  
Meng Li ◽  
Jie Chen ◽  
Qiang Lai ◽  
Xiao-Wen Zhao

This paper investigates formation tracking control for multi-agent networks with fixed time convergence. The control task is that the follower agents are required to form a prescribed formation within a fixed time and the geometric center of the formation moves in sync with the leader. First, an error system is designed by using the information of adjacent agents and a new control protocol is designed based on the error system and terminal sliding mode control (TSMC). Then, via employing the Lyapunov stability theorem and the fixed time stability theorem, the control task is proved to be possible within a fixed time and the convergence time can be calculated by parameters. Finally, numerical results illustrate the feasibility of the proposed control protocol.


2020 ◽  
Vol 17 (5) ◽  
pp. 172988142093854
Author(s):  
Di Wu ◽  
Lichao Hao ◽  
Xiujun Xu ◽  
Hongjian Wang ◽  
Jiajia Zhou

Cooperative tracking control problem of multiple water–land amphibious robots is discussed in this article with consideration of unknown nonlinear dynamics. Firstly, the amphibious robot dynamic model is formulated as an uncoupled nonlinear one in horizontal plane through eliminating relatively small sway velocity of the platform. Then cooperative tracking control algorithm is proposed with a two-stage strategy including dynamic control stage and kinematic control stage. In dynamic control stage, adaptive consensus control algorithm is obtained with estimating nonlinear properties of amphibious robots and velocities of the leader by neural network with unreliable communication links which is always the case in underwater applications. After that, kinematic cooperative controller is presented to guarantee formation stability of multiple water–land amphibious robots system in kinematic control stage. As a result, with the implementation of graph theory and Lyapunov theory, the stability of the formation tracking of multiple water–land amphibious robots system is proved with consideration of jointly connected communication graph. At last, simulations are carried out to prove the effectiveness of the proposed approaches.


2020 ◽  
pp. 002029402095245 ◽  
Author(s):  
Jing He ◽  
Xingxing Yang ◽  
Changfan Zhang ◽  
Jianhua Liu ◽  
Qian Zhang ◽  
...  

To address the tracking control problem of heavy-haul trains (HHTs) with input saturation during operation, an anti-saturation sliding mode (SMES) control method based on dynamic auxiliary compensator (DAC) is presented. Firstly, an HHT model with nonlinear coupling and uncertain disturbances is built. Secondly, a new type of DAC is introduced to overcome the difficulty of traditional dynamic auxiliary compensator (TDAC) with a large upper bound on the compensation signal. Finally, an anti-saturation SMES control algorithm is designed to reduce the influence of input saturation on the tracking accuracy of each carriage. Simulation results verify the effectiveness of the algorithm in terms of tracking accuracy, anti-interference, and anti-saturation.


Electronics ◽  
2020 ◽  
Vol 9 (4) ◽  
pp. 657 ◽  
Author(s):  
Uyen Tu Thi Hoang ◽  
Hai Xuan Le ◽  
Nguyen Huu Thai ◽  
Hung Van Pham ◽  
Linh Nguyen

The paper addresses the problem of effectively and robustly controlling a 3D overhead crane under the payload mass uncertainty, where the control performance is shown to be consistent. It is proposed to employ the sliding mode control technique to design the closed-loop controller due to its robustness, regardless of the uncertainties and nonlinearities of the under-actuated crane system. The radial basis function neural network has been exploited to construct an adaptive mechanism for estimating the unknown dynamics. More importantly, the adaptation methods have been derived from the Lyapunov theory to not only guarantee stability of the closed-loop control system, but also approximate the unknown and uncertain payload mass and weight matrix, which maintains the consistency of the control performance, although the cargo mass can be varied. Furthermore, the results obtained by implementing the proposed algorithm in the simulations show the effectiveness of the proposed approach and the consistency of the control performance, although the payload mass is uncertain.


Robotica ◽  
1991 ◽  
Vol 9 (1) ◽  
pp. 53-62 ◽  
Author(s):  
Zoran R. Novaković ◽  
Leon Z˘lajpah

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.


2021 ◽  
Vol 2021 ◽  
pp. 1-22
Author(s):  
Guangli Zhou ◽  
Yongming Yao ◽  
Huiying Liu ◽  
Xupeng Bai ◽  
Jianbo Liu

In this paper, we presented a strategy for accurate trajectory tracking control of a quadrotor with unknown disturbances. To guarantee that the tracking errors of all system state variables converge to zero in finite time and eliminate the chattering phenomenon caused by the switching control action, a control strategy that combines linear prediction model of disturbances and fuzzy sliding mode control (SMC) based on logical framework with side conditions (LFSC) was designed. LFSC was applied for both position and attitude tracking of the quadrotor. Firstly, a linear prediction method was devised to minimize the effects of external disturbances. Secondly, a new fuzzy law was implemented to eliminate the chattering phenomenon. In addition, the stabilities of position and attitude were demonstrated by using Lyapunov theory, respectively. Simulation results and comprehensive comparisons demonstrated the superior performance and robustness of the proposed LFSC scheme in the case of external disturbances.


2018 ◽  
Vol 8 (12) ◽  
pp. 2562 ◽  
Author(s):  
Anh Tuan Vo ◽  
Hee-Jun Kang

In this study, a robust control strategy is suggested for industrial robotic manipulators. First, to minimize the effects of disturbances and dynamic uncertainties, while achieving faster response times and removing the singularity problem, a nonsingular fast terminal sliding function is proposed. Second, to achieve the proposed tracking trajectory and chattering phenomenon elimination, a robust control strategy is designed for the robotic manipulator based on the proposed sliding function and a continuous adaptive control law. Furthermore, the dynamical model of the robotic system is estimated by applying a radial basis function neural network. Thanks to those techniques, the proposed system can operate free of an exact robotic model. The suggested system provides high tracking accuracy, robustness, and fast response with minimal positional errors compared to other control strategies. Proof of the robustness and stability of the suggested system has been verified by the Lyapunov theory. In simulation analyses, the simulated results present the effectiveness of the suggested strategy for the joint position tracking control of a 3-degree of freedom (3-DOF) PUMA560 robot.


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