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Radial basis function neural network based adaptive fast nonsingular terminal sliding mode controller for piezo positioning stage
This paper presents an adaptive fast nonsingular terminal sliding mode control base on a neural network based approximation technique to control the position of a piezo positioning stage (PSS). The proposed terminal sliding mode control can provide faster convergence and higher precision control whi...
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| Published in: | International journal of control, automation, and systems 2017, Automation, and Systems, 15(6), , pp.2892-2905 |
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| cites | cdi_FETCH-LOGICAL-c350t-2698ff550f7a2685f72b87d9f6e5bcc80efa78b82fd34f583ea052fc2d73c4763 |
| container_end_page | 2905 |
| container_issue | 6 |
| container_start_page | 2892 |
| container_title | International journal of control, automation, and systems |
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| creator | Dinh, To Xuan Ahn, Kyoung Kwan |
| description | This paper presents an adaptive fast nonsingular terminal sliding mode control base on a neural network based approximation technique to control the position of a piezo positioning stage (PSS). The proposed terminal sliding mode control can provide faster convergence and higher precision control while maintain its robustness to uncertainties. In the proposed control scheme, the combination of the fast-nonsingular terminal sliding mode control and neural network, which can precisely estimate the uncertainties in dynamic of the PSS system by employing an online tuning scheme, is a promising control approach for actuator systems. In addition, the robust control term is adopted to compensate the modeling error and ensure the robustness corresponding to a bounded disturbance. Stability of the closed loop system is analyzed and proved by using special Lyapunov functions. Experiment results strongly confirm the effectiveness of the proposed control method. |
| doi_str_mv | 10.1007/s12555-016-0650-1 |
| format | article |
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The proposed terminal sliding mode control can provide faster convergence and higher precision control while maintain its robustness to uncertainties. In the proposed control scheme, the combination of the fast-nonsingular terminal sliding mode control and neural network, which can precisely estimate the uncertainties in dynamic of the PSS system by employing an online tuning scheme, is a promising control approach for actuator systems. In addition, the robust control term is adopted to compensate the modeling error and ensure the robustness corresponding to a bounded disturbance. Stability of the closed loop system is analyzed and proved by using special Lyapunov functions. Experiment results strongly confirm the effectiveness of the proposed control method.</description><identifier>ISSN: 1598-6446</identifier><identifier>EISSN: 2005-4092</identifier><identifier>DOI: 10.1007/s12555-016-0650-1</identifier><language>eng</language><publisher>Bucheon / Seoul: Institute of Control, Robotics and Systems and The Korean Institute of Electrical Engineers</publisher><subject>Adaptive control ; Basis functions ; Control ; Controllers ; Engineering ; Intelligent Control and Applications ; Liapunov functions ; Mechatronics ; Neural networks ; On-line systems ; Radial basis function ; Robotics ; Robust control ; Sliding mode control ; Stability analysis ; Uncertainty ; 제어계측공학</subject><ispartof>International Journal of Control, 2017, Automation, and Systems, 15(6), , pp.2892-2905</ispartof><rights>Institute of Control, Robotics and Systems and The Korean Institute of Electrical Engineers and Springer-Verlag GmbH Germany 2017</rights><rights>Copyright Springer Science & Business Media Dec 2017</rights><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c350t-2698ff550f7a2685f72b87d9f6e5bcc80efa78b82fd34f583ea052fc2d73c4763</citedby><cites>FETCH-LOGICAL-c350t-2698ff550f7a2685f72b87d9f6e5bcc80efa78b82fd34f583ea052fc2d73c4763</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://www.proquest.com/docview/1975522650?pq-origsite=primo$$EHTML$$P50$$Gproquest$$H</linktohtml><link.rule.ids>314,776,780,11667,27901,27902,36037,44339</link.rule.ids><backlink>$$Uhttps://www.kci.go.kr/kciportal/ci/sereArticleSearch/ciSereArtiView.kci?sereArticleSearchBean.artiId=ART002290000$$DAccess content in National Research Foundation of Korea (NRF)$$Hfree_for_read</backlink></links><search><creatorcontrib>Dinh, To Xuan</creatorcontrib><creatorcontrib>Ahn, Kyoung Kwan</creatorcontrib><title>Radial basis function neural network based adaptive fast nonsingular terminal sliding mode controller for piezo positioning stage</title><title>International journal of control, automation, and systems</title><addtitle>Int. J. Control Autom. Syst</addtitle><description>This paper presents an adaptive fast nonsingular terminal sliding mode control base on a neural network based approximation technique to control the position of a piezo positioning stage (PSS). The proposed terminal sliding mode control can provide faster convergence and higher precision control while maintain its robustness to uncertainties. In the proposed control scheme, the combination of the fast-nonsingular terminal sliding mode control and neural network, which can precisely estimate the uncertainties in dynamic of the PSS system by employing an online tuning scheme, is a promising control approach for actuator systems. In addition, the robust control term is adopted to compensate the modeling error and ensure the robustness corresponding to a bounded disturbance. Stability of the closed loop system is analyzed and proved by using special Lyapunov functions. 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| ispartof | International Journal of Control, 2017, Automation, and Systems, 15(6), , pp.2892-2905 |
| issn | 1598-6446 2005-4092 |
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| source | ABI/INFORM Global; Springer Link |
| subjects | Adaptive control Basis functions Control Controllers Engineering Intelligent Control and Applications Liapunov functions Mechatronics Neural networks On-line systems Radial basis function Robotics Robust control Sliding mode control Stability analysis Uncertainty 제어계측공학 |
| title | Radial basis function neural network based adaptive fast nonsingular terminal sliding mode controller for piezo positioning stage |
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