Multiple Model Adaptive Tracking Control Based on Adaptive Dynamic Programming
Adaptive dynamic programming (ADP) has been tested as an effective method for optimal control of nonlinear system. However, as the structure of ADP requires control input to satisfy the initial admissible control condition, the control performance may be deteriorated due to abrupt parameter change o...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2016-01-01
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| Series: | Discrete Dynamics in Nature and Society |
| Online Access: | http://dx.doi.org/10.1155/2016/6023892 |
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| _version_ | 1832562291187384320 |
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| author | Kang Wang Xiaoli Li Yang Li |
| author_facet | Kang Wang Xiaoli Li Yang Li |
| author_sort | Kang Wang |
| collection | DOAJ |
| description | Adaptive dynamic programming (ADP) has been tested as an effective method for optimal control of nonlinear system. However, as the structure of ADP requires control input to satisfy the initial admissible control condition, the control performance may be deteriorated due to abrupt parameter change or system failure. In this paper, we introduce the multiple models idea into ADP, multiple subcontrollers run in parallel to supply multiple initial conditions for different environments, and a switching index is set up to decide the appropriate initial conditions for current system. By taking this strategy, the proposed multiple model ADP achieves optimal control for system with jumping parameters. The convergence of multiple model adaptive control based on ADP is proved and the simulation shows that the proposed method can improve the transient response of system effectively. |
| format | Article |
| id | doaj-art-d6c7e76ecdb24586a463f2d02010f338 |
| institution | Kabale University |
| issn | 1026-0226 1607-887X |
| language | English |
| publishDate | 2016-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Discrete Dynamics in Nature and Society |
| spelling | doaj-art-d6c7e76ecdb24586a463f2d02010f3382025-02-03T01:23:06ZengWileyDiscrete Dynamics in Nature and Society1026-02261607-887X2016-01-01201610.1155/2016/60238926023892Multiple Model Adaptive Tracking Control Based on Adaptive Dynamic ProgrammingKang Wang0Xiaoli Li1Yang Li2School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing 100083, ChinaCollege of Electronic Information and Control Engineering, Beijing University of Technology, Beijing 100124, ChinaSchool of International Studies, Communication University of China (CUC), Beijing 100024, ChinaAdaptive dynamic programming (ADP) has been tested as an effective method for optimal control of nonlinear system. However, as the structure of ADP requires control input to satisfy the initial admissible control condition, the control performance may be deteriorated due to abrupt parameter change or system failure. In this paper, we introduce the multiple models idea into ADP, multiple subcontrollers run in parallel to supply multiple initial conditions for different environments, and a switching index is set up to decide the appropriate initial conditions for current system. By taking this strategy, the proposed multiple model ADP achieves optimal control for system with jumping parameters. The convergence of multiple model adaptive control based on ADP is proved and the simulation shows that the proposed method can improve the transient response of system effectively.http://dx.doi.org/10.1155/2016/6023892 |
| spellingShingle | Kang Wang Xiaoli Li Yang Li Multiple Model Adaptive Tracking Control Based on Adaptive Dynamic Programming Discrete Dynamics in Nature and Society |
| title | Multiple Model Adaptive Tracking Control Based on Adaptive Dynamic Programming |
| title_full | Multiple Model Adaptive Tracking Control Based on Adaptive Dynamic Programming |
| title_fullStr | Multiple Model Adaptive Tracking Control Based on Adaptive Dynamic Programming |
| title_full_unstemmed | Multiple Model Adaptive Tracking Control Based on Adaptive Dynamic Programming |
| title_short | Multiple Model Adaptive Tracking Control Based on Adaptive Dynamic Programming |
| title_sort | multiple model adaptive tracking control based on adaptive dynamic programming |
| url | http://dx.doi.org/10.1155/2016/6023892 |
| work_keys_str_mv | AT kangwang multiplemodeladaptivetrackingcontrolbasedonadaptivedynamicprogramming AT xiaolili multiplemodeladaptivetrackingcontrolbasedonadaptivedynamicprogramming AT yangli multiplemodeladaptivetrackingcontrolbasedonadaptivedynamicprogramming |