| Event-Based Robust Control for Uncertain Nonlinear Systems Using Adaptive Dynamic Programming | |
Zhang, Qichao1 ; Zhao, Dongbin1,2; Wang, Ding1,3
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| Source Publication | IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
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| 2018 | |
| Volume | 29Issue:1Pages:37-50 |
| Subtype | Article |
| Abstract | In this paper, the robust control problem for a class of continuous-time nonlinear system with unmatched uncertainties is investigated using an event-based control method. First, the robust control problem is transformed into a corresponding optimal control problem with an augmented control and an appropriate cost function. Under the event-based mechanism, we prove that the solution of the optimal control problem can asymptotically stabilize the uncertain system with an adaptive triggering condition. That is, the designed event-based controller is robust to the original uncertain system. Note that the event-based controller is updated only when the triggering condition is satisfied, which can save the communication resources between the plant and the controller. Then, a single network adaptive dynamic programming structure with experience replay technique is constructed to approach the optimal control policies. The stability of the closed-loop system with the event-based control policy and the augmented control policy is analyzed using the Lyapunov approach. Furthermore, we prove that the minimal intersample time is bounded by a nonzero positive constant, which excludes Zeno behavior during the learning process. Finally, two simulation examples are provided to demonstrate the effectiveness of the proposed control scheme. |
| Keyword | Adaptive Dynamic Programming (Adp) Event-based Control Neural Network (Nn) Robust Control Unmatched Uncertainties |
| WOS Headings | Science & Technology ; Technology |
| DOI | 10.1109/TNNLS.2016.2614002 |
| WOS Keyword | TRIGGERED CONTROL ; CONTROL DESIGN ; NETWORKS ; SYNCHRONIZATION ; ALGORITHM ; CONSENSUS ; STRATEGY |
| Indexed By | SCI |
| Language | 英语 |
| Funding Organization | National Natural Science Foundation of China(61273136 ; National Key Research and Development Plan(2016YFB0101000) ; Beijing Natural Science Foundation(4162065) ; Research Fund of Tianjin Key Laboratory of Process Measurement and Control(TKLPMC-201612) ; 61573353 ; 61533017 ; 61304086 ; 61603382 ; U1501251) |
| WOS Research Area | Computer Science ; Engineering |
| WOS Subject | Computer Science, Artificial Intelligence ; Computer Science, Hardware & Architecture ; Computer Science, Theory & Methods ; Engineering, Electrical & Electronic |
| WOS ID | WOS:000419558900004 |
| Citation statistics | |
| Document Type | 期刊论文 |
| Identifier | http://ir.ia.ac.cn/handle/173211/14334 |
| Collection | 复杂系统管理与控制国家重点实验室_深度强化学习 |
| Corresponding Author | Zhao, Dongbin |
| Affiliation | 1.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China 2.Univ Chinese Acad Sci, Beijing 100049, Peoples R China 3.Tianjin Univ, Sch Elect Engn & Automat, Tianjin Key Lab Proc Measurement & Control, Tianjin 300072, Peoples R China |
| First Author Affilication | Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China |
| Corresponding Author Affilication | Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China |
| Recommended Citation GB/T 7714 | Zhang, Qichao,Zhao, Dongbin,Wang, Ding. Event-Based Robust Control for Uncertain Nonlinear Systems Using Adaptive Dynamic Programming[J]. IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS,2018,29(1):37-50. |
| APA | Zhang, Qichao,Zhao, Dongbin,&Wang, Ding.(2018).Event-Based Robust Control for Uncertain Nonlinear Systems Using Adaptive Dynamic Programming.IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS,29(1),37-50. |
| MLA | Zhang, Qichao,et al."Event-Based Robust Control for Uncertain Nonlinear Systems Using Adaptive Dynamic Programming".IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS 29.1(2018):37-50. |
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| TNNLS-EADP.pdf（2233KB） | 期刊论文 | 作者接受稿 | 开放获取 | CC BY-NC-SA | View Download | |
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