Improving transient performance of discrete‐time model reference adaptive control architectures
Summary Discrete‐time adaptive control algorithms can be executed directly in embedded code unlike their continuous‐time counterparts, which require discretization. However, their designs predicated on quadratic Lyapunov‐based frameworks are quite intricate due to the resulting complexity in the Lya...
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| Veröffentlicht in: | International journal of adaptive control and signal processing Jg. 34; H. 7; S. 901 - 918 |
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| Sprache: | Englisch |
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Bognor Regis
Wiley Subscription Services, Inc
01.07.2020
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| Abstract | Summary
Discrete‐time adaptive control algorithms can be executed directly in embedded code unlike their continuous‐time counterparts, which require discretization. However, their designs predicated on quadratic Lyapunov‐based frameworks are quite intricate due to the resulting complexity in the Lyapunov difference expressions. Therefore, a wide array of available continuous‐time results addressing transient performance issues using adaptive control algorithms cannot be applied or readily extended to the discrete‐time case. In this article, we present a new model reference adaptive control architecture for discrete‐time uncertain dynamical systems. Specifically, the proposed architecture consists of a command governor mechanism that adjusts the trajectory of a given command during the closed‐loop transient response. It is shown that this mechanism is effective in improving transient performance of discrete‐time model reference adaptive control architectures. Using a logarithmic Lyapunov function, we prove Lyapunov stability of the closed‐loop system as well as asymptotic convergence of the system error states involving the difference between the states of the uncertain dynamical system and the states of the reference model, as well as driving the command governor signal to zero. |
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| AbstractList | Summary
Discrete‐time adaptive control algorithms can be executed directly in embedded code unlike their continuous‐time counterparts, which require discretization. However, their designs predicated on quadratic Lyapunov‐based frameworks are quite intricate due to the resulting complexity in the Lyapunov difference expressions. Therefore, a wide array of available continuous‐time results addressing transient performance issues using adaptive control algorithms cannot be applied or readily extended to the discrete‐time case. In this article, we present a new model reference adaptive control architecture for discrete‐time uncertain dynamical systems. Specifically, the proposed architecture consists of a command governor mechanism that adjusts the trajectory of a given command during the closed‐loop transient response. It is shown that this mechanism is effective in improving transient performance of discrete‐time model reference adaptive control architectures. Using a logarithmic Lyapunov function, we prove Lyapunov stability of the closed‐loop system as well as asymptotic convergence of the system error states involving the difference between the states of the uncertain dynamical system and the states of the reference model, as well as driving the command governor signal to zero. Discrete‐time adaptive control algorithms can be executed directly in embedded code unlike their continuous‐time counterparts, which require discretization. However, their designs predicated on quadratic Lyapunov‐based frameworks are quite intricate due to the resulting complexity in the Lyapunov difference expressions. Therefore, a wide array of available continuous‐time results addressing transient performance issues using adaptive control algorithms cannot be applied or readily extended to the discrete‐time case. In this article, we present a new model reference adaptive control architecture for discrete‐time uncertain dynamical systems. Specifically, the proposed architecture consists of a command governor mechanism that adjusts the trajectory of a given command during the closed‐loop transient response. It is shown that this mechanism is effective in improving transient performance of discrete‐time model reference adaptive control architectures. Using a logarithmic Lyapunov function, we prove Lyapunov stability of the closed‐loop system as well as asymptotic convergence of the system error states involving the difference between the states of the uncertain dynamical system and the states of the reference model, as well as driving the command governor signal to zero. |
| Author | Muse, Jonathan A. Haddad, Wassim M. Dogan, K. Merve Yucelen, Tansel |
| Author_xml | – sequence: 1 givenname: K. Merve surname: Dogan fullname: Dogan, K. Merve organization: University of South Florida – sequence: 2 givenname: Tansel orcidid: 0000-0003-1156-1877 surname: Yucelen fullname: Yucelen, Tansel email: yucelen@usf.edu organization: University of South Florida – sequence: 3 givenname: Wassim M. orcidid: 0000-0002-4362-3043 surname: Haddad fullname: Haddad, Wassim M. organization: Georgia Institute of Technology – sequence: 4 givenname: Jonathan A. surname: Muse fullname: Muse, Jonathan A. organization: U.S. Air Force Research Laboratory |
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| Cites_doi | 10.3390/machines5010009 10.1109/TAC.1980.1102363 10.1109/TMECH.2012.2193592 10.1109/ACC.1994.751866 10.1137/1.9780898719376 10.1002/acs.4480030206 10.1002/047134608X.W1022.pub2 10.1109/CDC.1999.832826 10.1109/TAC.2012.2218667 10.1109/TAC.2008.920234 10.1109/ACC.2002.1023823 10.1080/00207170310001649900 10.2514/1.55756 10.2514/6.2010-8017 10.1002/acs.2376 10.1007/978-1-4471-4396-3 10.1080/00207178908953402 10.2514/6.2012-4775 10.2514/1.46741 10.1016/S0005-1098(01)00028-0 10.1002/acs.733 10.1515/9781400841042 10.1080/00207170410001699021 10.2514/6.2008-7283 10.1080/00207179.2015.1041001 10.2514/6.2011-6200 10.2514/1.55711 |
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Discrete‐time adaptive control algorithms can be executed directly in embedded code unlike their continuous‐time counterparts, which require... Discrete‐time adaptive control algorithms can be executed directly in embedded code unlike their continuous‐time counterparts, which require discretization.... |
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| SubjectTerms | Adaptive algorithms Architecture Control algorithms Control stability discrete‐time uncertain dynamical systems Dynamical systems Liapunov functions Model reference adaptive control stability analysis Transient performance transient performance improvement Transient response |
| Title | Improving transient performance of discrete‐time model reference adaptive control architectures |
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