Distributed optimal integrated tracking control for separate kinematic and dynamic uncertain non-holonomic mobile mechanical multi-agent systems
This study addres,ses a distributed optimal integrated tracking control method with disturbance rejection for separate kinematic and dynamic uncertain non-holonomic mobile mechanical multi-agent ($\mathbf{NM^3}$NM3) systems. Initially, based on the graph theory, the overall tracking systems of agent...
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| Published in: | IET control theory & applications Vol. 11; no. 18; pp. 3249 - 3260 |
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| Format: | Journal Article |
| Language: | English |
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The Institution of Engineering and Technology
15.12.2017
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| ISSN: | 1751-8644, 1751-8652 |
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| Abstract | This study addres,ses a distributed optimal integrated tracking control method with disturbance rejection for separate kinematic and dynamic uncertain non-holonomic mobile mechanical multi-agent ($\mathbf{NM^3}$NM3) systems. Initially, based on the graph theory, the overall tracking systems of agents are defined and the distributed optimal tracking problem of separate kinematics and dynamics is transformed into an equivalent distributed optimal regulation problem of the integrated affine system. Then, neural network (NN)-based adaptive dynamic programming and cooperative differential game theory is utilised for control, in which only one NN is required for each agent. The NN weight-tuning law and the online algorithm is developed to approximate the value function, and synchronously update both optimal control and worst disturbance laws in only one iterative loop. The tracking errors and function approximation errors are proven to be uniformly ultimately bounded using Lyapunov theory. Finally, as applications of the proposed method, control of the wheeled mobile multi-robot system is discussed. The effectiveness of the method is demonstrated by the results of the comparative numerical simulation. |
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| AbstractList | This study addres,ses a distributed optimal integrated tracking control method with disturbance rejection for separate kinematic and dynamic uncertain non‐holonomic mobile mechanical multi‐agent (NM 3) systems. Initially, based on the graph theory, the overall tracking systems of agents are defined and the distributed optimal tracking problem of separate kinematics and dynamics is transformed into an equivalent distributed optimal regulation problem of the integrated affine system. Then, neural network (NN)‐based adaptive dynamic programming and cooperative differential game theory is utilised for control, in which only one NN is required for each agent. The NN weight‐tuning law and the online algorithm is developed to approximate the value function, and synchronously update both optimal control and worst disturbance laws in only one iterative loop. The tracking errors and function approximation errors are proven to be uniformly ultimately bounded using Lyapunov theory. Finally, as applications of the proposed method, control of the wheeled mobile multi‐robot system is discussed. The effectiveness of the method is demonstrated by the results of the comparative numerical simulation. This study addres,ses a distributed optimal integrated tracking control method with disturbance rejection for separate kinematic and dynamic uncertain non-holonomic mobile mechanical multi-agent ($\mathbf{NM^3}$NM3) systems. Initially, based on the graph theory, the overall tracking systems of agents are defined and the distributed optimal tracking problem of separate kinematics and dynamics is transformed into an equivalent distributed optimal regulation problem of the integrated affine system. Then, neural network (NN)-based adaptive dynamic programming and cooperative differential game theory is utilised for control, in which only one NN is required for each agent. The NN weight-tuning law and the online algorithm is developed to approximate the value function, and synchronously update both optimal control and worst disturbance laws in only one iterative loop. The tracking errors and function approximation errors are proven to be uniformly ultimately bounded using Lyapunov theory. Finally, as applications of the proposed method, control of the wheeled mobile multi-robot system is discussed. The effectiveness of the method is demonstrated by the results of the comparative numerical simulation. This study addres,ses a distributed optimal integrated tracking control method with disturbance rejection for separate kinematic and dynamic uncertain non‐holonomic mobile mechanical multi‐agent ( ) systems. Initially, based on the graph theory, the overall tracking systems of agents are defined and the distributed optimal tracking problem of separate kinematics and dynamics is transformed into an equivalent distributed optimal regulation problem of the integrated affine system. Then, neural network (NN)‐based adaptive dynamic programming and cooperative differential game theory is utilised for control, in which only one NN is required for each agent. The NN weight‐tuning law and the online algorithm is developed to approximate the value function, and synchronously update both optimal control and worst disturbance laws in only one iterative loop. The tracking errors and function approximation errors are proven to be uniformly ultimately bounded using Lyapunov theory. Finally, as applications of the proposed method, control of the wheeled mobile multi‐robot system is discussed. The effectiveness of the method is demonstrated by the results of the comparative numerical simulation. |
| Author | Tan, Luy Nguyen |
| Author_xml | – sequence: 1 givenname: Luy Nguyen surname: Tan fullname: Tan, Luy Nguyen email: nguyentanluy@iuh.edu.vn organization: Industrial University, Ho Chi Minh City, Vietnam |
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| CitedBy_id | crossref_primary_10_1007_s11071_018_4228_8 crossref_primary_10_1109_TNSE_2018_2876262 crossref_primary_10_1049_iet_cta_2018_6026 crossref_primary_10_1109_TIV_2024_3399231 crossref_primary_10_1049_iet_cta_2018_5832 crossref_primary_10_1016_j_neunet_2018_06_007 |
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| Keywords | equivalent distributed optimal regulation problem NN weight-tuning law disturbance rejection graph theory tracking systems multi-robot systems mobile robots neural network NN-based adaptive dynamic programming wheeled mobile multirobot system iterative loop iterative learning control neurocontrollers function approximation errors numerical simulation online algorithm dynamic programming tracking errors optimal control integrated affine system Lyapunov theory cooperative differential game theory distributed optimal integrated tracking control dynamic uncertain nonholonomic mobile mechanical multiagent systems differential games kinematic uncertain nonholonomic mobile mechanical multiagent systems worst disturbance laws Lyapunov methods |
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| SubjectTerms | cooperative differential game theory differential games distributed optimal integrated tracking control disturbance rejection dynamic programming dynamic uncertain nonholonomic mobile mechanical multiagent systems equivalent distributed optimal regulation problem function approximation errors graph theory integrated affine system iterative learning control iterative loop kinematic uncertain nonholonomic mobile mechanical multiagent systems Lyapunov methods Lyapunov theory mobile robots multi‐robot systems neural network neurocontrollers NN weight‐tuning law NN‐based adaptive dynamic programming numerical simulation online algorithm optimal control Research Article tracking errors tracking systems wheeled mobile multirobot system worst disturbance laws |
| Title | Distributed optimal integrated tracking control for separate kinematic and dynamic uncertain non-holonomic mobile mechanical multi-agent systems |
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