Robust observer design for Sugeno systems with incremental quadratic nonlinearity in the consequent

Moodi, Hoda; Farrokhi, Mohammad

doi:10.2478/amcs-2013-0053

Cited by 19 publications

(5 citation statements)

References 26 publications

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“…Due to the universal existence of inherent nonlinearities in industrial and commercial processes, nonlinear descriptor systems and their applications should be specifically considered. On the other hand, it is well recognized that the Takagi-Sugeno (T-S) fuzzy model can approximate a highly complicated nonlinear system using a family of fuzzy IF-THEN rules that represent the local linear state-space models [10], [11], [12]. Therefore, taking advantages of both descriptor and T-S formalisms in the field of modelling, it is significantly efficient for T-S Descriptor Systems (TSDS's) to describe many practical processes.…”

Section: Introductionmentioning

confidence: 99%

Fault Reconstruction and Fault-tolerant Control via Learning Observers in Takagi-Sugeno Fuzzy Descriptor Systems with Time Delays

Jia

Wen

Zhang³

et al. 2015

IEEE Trans. Ind. Electron.

117

121

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This paper addresses the problems of observerbased fault reconstruction and fault-tolerant control for TakagiSugeno fuzzy descriptor systems subject to time delays and external disturbances. A novel fuzzy descriptor learning observer is constructed to achieve simultaneous reconstruction of system states and actuator faults. Sufficient conditions for existence of the proposed observer are explicitly provided. Utilizing the reconstructed fault information, a reconfigurable fuzzy faulttolerant controller based on the separation property is designed to compensate for the impact of actuator faults on system performance by stabilizing the closed-loop system. In addition, the design of the fault reconstruction observer and the fault-tolerant controller is formulated in terms of linear matrix inequalities that can be conveniently solved using convex optimization techniques. At last, simulation results on a truck trailer system are presented to verify the effectiveness of the proposed approaches.

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Section: Introductionmentioning

confidence: 99%

Fault Reconstruction and Fault-tolerant Control via Learning Observers in Takagi-Sugeno Fuzzy Descriptor Systems with Time Delays

Jia

Wen

Zhang³

et al. 2015

IEEE Trans. Ind. Electron.

117

121

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“…Rarely may one find comprehensive works on nonlinear consequent parts in fuzzy systems; however, some of the studies in this arena are shortly surveyed in the following. A reduction in the number of rules was carried out by Moodi in a fuzzy system using the TSK fuzzy model accompanied by a nonlinear consequent part [38]. The result of a rule is supposed to comprise a linear term and a nonlinear one.…”

Section: Introductionmentioning

confidence: 99%

Modeling Renewable Energy Systems by a Self-Evolving Nonlinear Consequent Part Recurrent Type-2 Fuzzy System for Power Prediction

et al. 2021

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A novel Nonlinear Consequent Part Recurrent Type-2 Fuzzy System (NCPRT2FS) is presented for the modeling of renewable energy systems. Not only does this paper present a new architecture of the type-2 fuzzy system (T2FS) for identification and behavior prognostication of an experimental solar cell set and a wind turbine, but also, it introduces an exquisite technique to acquire an optimal number of membership functions (MFs) and their corresponding rules. Using nonlinear functions in the “Then” part of fuzzy rules, introducing a new mechanism in structure learning, using an adaptive learning rate and performing convergence analysis of the learning algorithm are the innovations of this paper. Another novel innovation is using optimization techniques (including pruning fuzzy rules, initial adjustment of MFs). Next, a solar photovoltaic cell and a wind turbine are deemed as case studies. The experimental data are exploited and the consequent yields emerge as convincing. The root-mean-square-error (RMSE) is less than 0.006 and the number of fuzzy rules is equal to or less than four rules, which indicates the very good performance of the presented fuzzy neural network. Finally, the obtained model is used for the first time for a geographical area to examine the feasibility of renewable energies.

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“…Rarely may one find comprehensive works on nonlinear consequent part in fuzzy systems; however, some of the studies on the arena are shortly surveyed in following. Reduction of the number of rules was carried out by Moodi in a fuzzy system using TSK fuzzy model accompanied by nonlinear consequent part [38]. The resultant of a rule is supposed to comprise a linear term and a nonlinear one.…”

Section: Introductionmentioning

confidence: 99%

Modeling of Renewable Energy Systems by a Self-Evolving Nonlinear Consequent Part Recurrent Type-2 Fuzzy System (NCPRT2FS) for Power Prediction

Tavoosi¹,

Suratgar²,

Menhaj³

et al. 2021

Preprint

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Not only does this paper present a novel type-2 fuzzy system for identification and behavior prognostication of an experimental solar cell set and a wind turbine, but also it brings forward an exquisite technique to acquire an optimal number of membership functions and the corresponding rules. It proposes a seven-layered NCPRT2FS. For fuzzification in the first two layers, Gaussian type-2 fuzzy membership functions with uncertainty in the mean, are exploited. The third layer comprises rule definition and the forth one embeds fulfillment of type reduction. The three last remained layers are the ones in which resultant left–right firing points, two end-points and output all get assessed correspondingly. It should not be neglected off the nutshell that recurrent feedback at the fifth layer exerts delayed outputs ameliorating efficiency of the suggested NCPRT2FS. Later in the paper, a modern structural learning, established on type-2 fuzzy clustering, is held forth. An adaptively rated learning back-propagation algorithm is extended to adjust the parameters ensuring the convergence as well. Eventually, solar cell photo-voltaic and wind turbine are deemed as case studies. The experimental data are exploited and the consequent yields emerge so persuasive.

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Robust observer design for Sugeno systems with incremental quadratic nonlinearity in the consequent

Cited by 19 publications

References 26 publications

Fault Reconstruction and Fault-tolerant Control via Learning Observers in Takagi-Sugeno Fuzzy Descriptor Systems with Time Delays

Fault Reconstruction and Fault-tolerant Control via Learning Observers in Takagi-Sugeno Fuzzy Descriptor Systems with Time Delays

Modeling Renewable Energy Systems by a Self-Evolving Nonlinear Consequent Part Recurrent Type-2 Fuzzy System for Power Prediction

Modeling of Renewable Energy Systems by a Self-Evolving Nonlinear Consequent Part Recurrent Type-2 Fuzzy System (NCPRT2FS) for Power Prediction

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