LMI based design of constrained fuzzy predictive control
Predictive control of nonlinear systems subject to output and input constraints is considered. A fuzzy model is used to predict the future behavior. Two new ideas are proposed here. First, an added constraint on the applied control action is used to ensure the decrease of a quadratic Lyapunov functi...
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| Published in | Fuzzy sets and systems Vol. 161; no. 6; pp. 893 - 918 |
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| Main Authors | , , |
| Format | Journal Article |
| Language | English |
| Published |
Kidlington
Elsevier B.V
16.03.2010
Elsevier |
| Subjects | |
| Online Access | Get full text |
| ISSN | 0165-0114 1872-6801 |
| DOI | 10.1016/j.fss.2009.10.020 |
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| Abstract | Predictive control of nonlinear systems subject to output and input constraints is considered. A fuzzy model is used to predict the future behavior. Two new ideas are proposed here. First, an added constraint on the applied control action is used to ensure the decrease of a quadratic Lyapunov function, and so guarantee Lyapunov exponential stability of the closed-loop system. Second, the feasibility of the finite-horizon optimization problem with the added constraints is ensured based on an off-line solution of a set of LMIs. The novel stability method is compared to the existing methods, such as the techniques based on the end-point constraints (terminal constraint set), and the robust stability techniques based on the small gain theory. The proposed method ensures Lyapunov exponential stability, does not need an auxiliary controller and can be used with any feasible controller parameters. Illustrative examples including the predictive control of a highly nonlinear chemical reactor (CSTR) are discussed. |
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| AbstractList | Predictive control of nonlinear systems subject to output and input constraints is considered. A fuzzy model is used to predict the future behavior. Two new ideas are proposed here. First, an added constraint on the applied control action is used to ensure the decrease of a quadratic Lyapunov function, and so guarantee Lyapunov exponential stability of the closed-loop system. Second, the feasibility of the finite-horizon optimization problem with the added constraints is ensured based on an off-line solution of a set of LMIs. The novel stability method is compared to the existing methods, such as the techniques based on the end-point constraints (terminal constraint set), and the robust stability techniques based on the small gain theory. The proposed method ensures Lyapunov exponential stability, does not need an auxiliary controller and can be used with any feasible controller parameters. Illustrative examples including the predictive control of a highly nonlinear chemical reactor (CSTR) are discussed. |
| Author | Khairy, M. Elshafei, A.L. Emara, Hassan M. |
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| CitedBy_id | crossref_primary_10_1007_s40815_019_00665_3 crossref_primary_10_1016_j_isatra_2016_04_019 crossref_primary_10_1016_j_jprocont_2016_11_012 crossref_primary_10_1007_s40815_021_01153_3 crossref_primary_10_1080_00207721_2018_1536234 crossref_primary_10_1109_TAC_2012_2190199 crossref_primary_10_1155_2014_587510 crossref_primary_10_1016_j_fss_2012_06_002 crossref_primary_10_1016_j_fss_2013_12_008 crossref_primary_10_1080_23311916_2018_1457206 crossref_primary_10_1007_s12530_014_9113_1 crossref_primary_10_1155_2015_437943 crossref_primary_10_1109_ACCESS_2021_3107282 crossref_primary_10_1002_asjc_1603 crossref_primary_10_1016_j_fss_2014_04_003 |
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| Keywords | LMI T–S fuzzy model Model-based predictive control Receding-horizon control Fuzzy system T-S fuzzy model Control system Optimization method Lyapunov method Fuzzy set Non linear system Fuzzy control Information processing Lyapunov stability Numerical stability Lyapunov function |
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| Snippet | Predictive control of nonlinear systems subject to output and input constraints is considered. A fuzzy model is used to predict the future behavior. Two new... |
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| SubjectTerms | Applied sciences Circuit properties Combinatorics Combinatorics. Ordered structures Computer science; control theory; systems Designs and configurations Digital circuits Electric, optical and optoelectronic circuits Electronic circuits Electronics Exact sciences and technology Information, signal and communications theory LMI Mathematical methods Mathematics Miscellaneous Model-based predictive control Receding-horizon control Sciences and techniques of general use Telecommunications and information theory Theoretical computing T–S fuzzy model |
| Title | LMI based design of constrained fuzzy predictive control |
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