Model-Based ILC with a Modified Q-Filter for Complex Motion Systems: Practical Considerations and Experimental Verification on a Wafer Stage
Iterative learning control (ILC) is one of the most popular tracking control methods for systems that repeatedly execute the same task. A system model is usually used in the analysis and design of ILC. Model-based ILC results in general in fast convergence and good performance. However, the model un...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2018-01-01
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| Series: | Complexity |
| Online Access: | http://dx.doi.org/10.1155/2018/5406035 |
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| author | Fazhi Song Yang Liu Jun Cao Li Li Jiubin Tan |
| author_facet | Fazhi Song Yang Liu Jun Cao Li Li Jiubin Tan |
| author_sort | Fazhi Song |
| collection | DOAJ |
| description | Iterative learning control (ILC) is one of the most popular tracking control methods for systems that repeatedly execute the same task. A system model is usually used in the analysis and design of ILC. Model-based ILC results in general in fast convergence and good performance. However, the model uncertainties and nonrepetitive disturbances hamper its practical applications. One of the commonly used solutions is the introduction of a low-pass filter, namely, the Q-filter. However, it is indicated in this paper that the existing Q-filter configurations compromise the servo performance, although improving the robustness. Motivated by the combination of performance and robustness, a novel Q-filter configuration in ILC is presented in this paper. Some practical considerations, such as the configuration of ILC in a feedback control system, the time delay compensation, and the learning coefficient, are provided in the implementation of the proposed ILC algorithm. The effectiveness and superiority of the proposed ILC versus existing Q-filter ILC are demonstrated by both theoretical analysis and experimental verification on a wafer stage. |
| format | Article |
| id | doaj-art-57df3c1640ac4c9c9772a16fe07e89b2 |
| institution | Kabale University |
| issn | 1076-2787 1099-0526 |
| language | English |
| publishDate | 2018-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Complexity |
| spelling | doaj-art-57df3c1640ac4c9c9772a16fe07e89b22025-02-03T01:31:44ZengWileyComplexity1076-27871099-05262018-01-01201810.1155/2018/54060355406035Model-Based ILC with a Modified Q-Filter for Complex Motion Systems: Practical Considerations and Experimental Verification on a Wafer StageFazhi Song0Yang Liu1Jun Cao2Li Li3Jiubin Tan4Ultra-Precision Optoelectronic Instrumentation Engineering Center, Harbin Institute of Technology, Harbin, ChinaUltra-Precision Optoelectronic Instrumentation Engineering Center, Harbin Institute of Technology, Harbin, ChinaSchool of Automation, Harbin Engineering University, Harbin, ChinaUltra-Precision Optoelectronic Instrumentation Engineering Center, Harbin Institute of Technology, Harbin, ChinaUltra-Precision Optoelectronic Instrumentation Engineering Center, Harbin Institute of Technology, Harbin, ChinaIterative learning control (ILC) is one of the most popular tracking control methods for systems that repeatedly execute the same task. A system model is usually used in the analysis and design of ILC. Model-based ILC results in general in fast convergence and good performance. However, the model uncertainties and nonrepetitive disturbances hamper its practical applications. One of the commonly used solutions is the introduction of a low-pass filter, namely, the Q-filter. However, it is indicated in this paper that the existing Q-filter configurations compromise the servo performance, although improving the robustness. Motivated by the combination of performance and robustness, a novel Q-filter configuration in ILC is presented in this paper. Some practical considerations, such as the configuration of ILC in a feedback control system, the time delay compensation, and the learning coefficient, are provided in the implementation of the proposed ILC algorithm. The effectiveness and superiority of the proposed ILC versus existing Q-filter ILC are demonstrated by both theoretical analysis and experimental verification on a wafer stage.http://dx.doi.org/10.1155/2018/5406035 |
| spellingShingle | Fazhi Song Yang Liu Jun Cao Li Li Jiubin Tan Model-Based ILC with a Modified Q-Filter for Complex Motion Systems: Practical Considerations and Experimental Verification on a Wafer Stage Complexity |
| title | Model-Based ILC with a Modified Q-Filter for Complex Motion Systems: Practical Considerations and Experimental Verification on a Wafer Stage |
| title_full | Model-Based ILC with a Modified Q-Filter for Complex Motion Systems: Practical Considerations and Experimental Verification on a Wafer Stage |
| title_fullStr | Model-Based ILC with a Modified Q-Filter for Complex Motion Systems: Practical Considerations and Experimental Verification on a Wafer Stage |
| title_full_unstemmed | Model-Based ILC with a Modified Q-Filter for Complex Motion Systems: Practical Considerations and Experimental Verification on a Wafer Stage |
| title_short | Model-Based ILC with a Modified Q-Filter for Complex Motion Systems: Practical Considerations and Experimental Verification on a Wafer Stage |
| title_sort | model based ilc with a modified q filter for complex motion systems practical considerations and experimental verification on a wafer stage |
| url | http://dx.doi.org/10.1155/2018/5406035 |
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