Control of Complex Nonlinear Dynamic Rational Systems
Nonlinear rational systems/models, also known as total nonlinear dynamic systems/models, in an expression of a ratio of two polynomials, have roots in describing general engineering plants and chemical reaction processes. The major challenge issue in the control of such a system is the control input...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2018-01-01
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| Series: | Complexity |
| Online Access: | http://dx.doi.org/10.1155/2018/8953035 |
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| _version_ | 1850218447823175680 |
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| author | Quanmin Zhu Li Liu Weicun Zhang Shaoyuan Li |
| author_facet | Quanmin Zhu Li Liu Weicun Zhang Shaoyuan Li |
| author_sort | Quanmin Zhu |
| collection | DOAJ |
| description | Nonlinear rational systems/models, also known as total nonlinear dynamic systems/models, in an expression of a ratio of two polynomials, have roots in describing general engineering plants and chemical reaction processes. The major challenge issue in the control of such a system is the control input embedded in its denominator polynomials. With extensive searching, it could not find any systematic approach in designing this class of control systems directly from its model structure. This study expands the U-model-based approach to establish a platform for the first layer of feedback control and the second layer of adaptive control of the nonlinear rational systems, which, in principle, separates control system design (without involving a plant model) and controller output determination (with solving inversion of the plant U-model). This procedure makes it possible to achieve closed-loop control of nonlinear systems with linear performance (transient response and steady-state accuracy). For the conditions using the approach, this study presents the associated stability and convergence analyses. Simulation studies are performed to show off the characteristics of the developed procedure in numerical tests and to give the general guidelines for applications. |
| format | Article |
| id | doaj-art-36f375fd805f4bcb8e557ab9dcf2b0c2 |
| institution | OA Journals |
| issn | 1076-2787 1099-0526 |
| language | English |
| publishDate | 2018-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Complexity |
| spelling | doaj-art-36f375fd805f4bcb8e557ab9dcf2b0c22025-08-20T02:07:45ZengWileyComplexity1076-27871099-05262018-01-01201810.1155/2018/89530358953035Control of Complex Nonlinear Dynamic Rational SystemsQuanmin Zhu0Li Liu1Weicun Zhang2Shaoyuan Li3School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing 100083, ChinaSchool of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing 100083, ChinaSchool of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing 100083, ChinaDepartment of Automation, Shanghai Jiao Tong University, 800 Dongchuan Rd., Minhang, Shanghai 200240, ChinaNonlinear rational systems/models, also known as total nonlinear dynamic systems/models, in an expression of a ratio of two polynomials, have roots in describing general engineering plants and chemical reaction processes. The major challenge issue in the control of such a system is the control input embedded in its denominator polynomials. With extensive searching, it could not find any systematic approach in designing this class of control systems directly from its model structure. This study expands the U-model-based approach to establish a platform for the first layer of feedback control and the second layer of adaptive control of the nonlinear rational systems, which, in principle, separates control system design (without involving a plant model) and controller output determination (with solving inversion of the plant U-model). This procedure makes it possible to achieve closed-loop control of nonlinear systems with linear performance (transient response and steady-state accuracy). For the conditions using the approach, this study presents the associated stability and convergence analyses. Simulation studies are performed to show off the characteristics of the developed procedure in numerical tests and to give the general guidelines for applications.http://dx.doi.org/10.1155/2018/8953035 |
| spellingShingle | Quanmin Zhu Li Liu Weicun Zhang Shaoyuan Li Control of Complex Nonlinear Dynamic Rational Systems Complexity |
| title | Control of Complex Nonlinear Dynamic Rational Systems |
| title_full | Control of Complex Nonlinear Dynamic Rational Systems |
| title_fullStr | Control of Complex Nonlinear Dynamic Rational Systems |
| title_full_unstemmed | Control of Complex Nonlinear Dynamic Rational Systems |
| title_short | Control of Complex Nonlinear Dynamic Rational Systems |
| title_sort | control of complex nonlinear dynamic rational systems |
| url | http://dx.doi.org/10.1155/2018/8953035 |
| work_keys_str_mv | AT quanminzhu controlofcomplexnonlineardynamicrationalsystems AT liliu controlofcomplexnonlineardynamicrationalsystems AT weicunzhang controlofcomplexnonlineardynamicrationalsystems AT shaoyuanli controlofcomplexnonlineardynamicrationalsystems |