Predictive Control for Interval Type-2 Fuzzy System with Event-Triggered Scheme
In this paper, a synthesis approach of model predictive control (MPC) is proposed for interval type-2 (IT2) Takagi-Sugeno (T-S) fuzzy system with quantization error, bounded disturbance, and data loss. The novelty lies in the following technical improvements. In order to reduce the redundant data tr...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2019-01-01
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| Series: | Advances in Fuzzy Systems |
| Online Access: | http://dx.doi.org/10.1155/2019/9365767 |
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| author | Siyao Wang Xiaoming Tang Li Deng Hongchun Qu Linfeng Tian Cheng Tan |
| author_facet | Siyao Wang Xiaoming Tang Li Deng Hongchun Qu Linfeng Tian Cheng Tan |
| author_sort | Siyao Wang |
| collection | DOAJ |
| description | In this paper, a synthesis approach of model predictive control (MPC) is proposed for interval type-2 (IT2) Takagi-Sugeno (T-S) fuzzy system with quantization error, bounded disturbance, and data loss. The novelty lies in the following technical improvements. In order to reduce the redundant data transmission, an event-triggered communication scheme is applied to determine whether the control law should be transmitted into the communication network or not. The IT2 T-S fuzzy model is utilized to address the nonlinearity of plant with parameter uncertainties, which can be captured by the lower and upper membership functions. Furthermore, the phenomena of data loss and quantization error between the controller and the actuator are expressed as Markovian chain and sector-bound uncertainties. The synthesis approach of MPC is provided by solving an MPC optimization problem over an infinite horizon objective function which explicitly considers the input constraints. By applying the quadratic boundedness (QB) technique, the recursive feasibility and quadratic stability of closed-loop system can be guaranteed. A numerical simulation and comparison studies are proposed to illustrate the effectiveness of this approach. |
| format | Article |
| id | doaj-art-39eab9aaab054160b93787f56cf9ea0a |
| institution | Kabale University |
| issn | 1687-7101 1687-711X |
| language | English |
| publishDate | 2019-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Advances in Fuzzy Systems |
| spelling | doaj-art-39eab9aaab054160b93787f56cf9ea0a2025-02-03T05:45:33ZengWileyAdvances in Fuzzy Systems1687-71011687-711X2019-01-01201910.1155/2019/93657679365767Predictive Control for Interval Type-2 Fuzzy System with Event-Triggered SchemeSiyao Wang0Xiaoming Tang1Li Deng2Hongchun Qu3Linfeng Tian4Cheng Tan5Chongqing University of Posts and Telecommunications, College of Automation, Chongqing 400035, ChinaChongqing University of Posts and Telecommunications, College of Automation, Chongqing 400035, ChinaChongqing University of Posts and Telecommunications, College of Automation, Chongqing 400035, ChinaChongqing University of Posts and Telecommunications, College of Automation, Chongqing 400035, ChinaChongqing College of Electronic Engineering, Engineer of Network Center, Chongqing 400037, ChinaChina Coal Technology and Engineering Group Chongqing Research Institute, Chongqing 400037, ChinaIn this paper, a synthesis approach of model predictive control (MPC) is proposed for interval type-2 (IT2) Takagi-Sugeno (T-S) fuzzy system with quantization error, bounded disturbance, and data loss. The novelty lies in the following technical improvements. In order to reduce the redundant data transmission, an event-triggered communication scheme is applied to determine whether the control law should be transmitted into the communication network or not. The IT2 T-S fuzzy model is utilized to address the nonlinearity of plant with parameter uncertainties, which can be captured by the lower and upper membership functions. Furthermore, the phenomena of data loss and quantization error between the controller and the actuator are expressed as Markovian chain and sector-bound uncertainties. The synthesis approach of MPC is provided by solving an MPC optimization problem over an infinite horizon objective function which explicitly considers the input constraints. By applying the quadratic boundedness (QB) technique, the recursive feasibility and quadratic stability of closed-loop system can be guaranteed. A numerical simulation and comparison studies are proposed to illustrate the effectiveness of this approach.http://dx.doi.org/10.1155/2019/9365767 |
| spellingShingle | Siyao Wang Xiaoming Tang Li Deng Hongchun Qu Linfeng Tian Cheng Tan Predictive Control for Interval Type-2 Fuzzy System with Event-Triggered Scheme Advances in Fuzzy Systems |
| title | Predictive Control for Interval Type-2 Fuzzy System with Event-Triggered Scheme |
| title_full | Predictive Control for Interval Type-2 Fuzzy System with Event-Triggered Scheme |
| title_fullStr | Predictive Control for Interval Type-2 Fuzzy System with Event-Triggered Scheme |
| title_full_unstemmed | Predictive Control for Interval Type-2 Fuzzy System with Event-Triggered Scheme |
| title_short | Predictive Control for Interval Type-2 Fuzzy System with Event-Triggered Scheme |
| title_sort | predictive control for interval type 2 fuzzy system with event triggered scheme |
| url | http://dx.doi.org/10.1155/2019/9365767 |
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