Enhanced Stabilization of Discrete-Time Takagi–Sugeno Fuzzy Systems Based on a Comprehensive Real-Time Scheduling Model

The problem of enhanced stabilization of discrete-time Takagi–Sugeno fuzzy system is investigated in depth via proposing a new way to employ much more information implied in various time-varying differences of multi-instant normalized fuzzy weighting functions. Benefit from the given comprehensive real-time scheduling model, these time-varying differences on time vertical dimension and two different transverse dimensions are for the first time integrated into fuzzy stabilization and two key alterable weights are also introduced. Consequently, much considerable freedom can be produced and, thus, it brings much less conservative results than the reported ones in recent literature. More importantly, a very simple workable way has been provided to online recognize the specific enabled mode at each sampling instant so that those existing time-consuming online operations in referred literature can be avoided to ease online implementation costs. Indeed, this feature is very beneficial to the practical application of our theoretical results. Finally, the superiority of our developed method over previous ones is validated adequately via two benchmark simulations.

[1]  Yue Wu,et al.  Local Stabilization of Continuous-Time T–S Fuzzy Systems With Partly Measurable Premise Variables and Time-Varying Delay , 2021, IEEE Transactions on Systems, Man, and Cybernetics: Systems.

[2]  Ying Wu,et al.  Adaptive Fault-Tolerant Tracking Control for Discrete-Time Multiagent Systems via Reinforcement Learning Algorithm , 2020, IEEE Transactions on Cybernetics.

[3]  Dong Yue,et al.  Stabilization of Networked Control Systems With Hybrid-Driven Mechanism and Probabilistic Cyber Attacks , 2019, IEEE Transactions on Systems, Man, and Cybernetics: Systems.

[4]  Renquan Lu,et al.  Adaptive Neural Network Tracking Control for Robotic Manipulators With Dead Zone , 2019, IEEE Transactions on Neural Networks and Learning Systems.

[5]  Xiangpeng Xie,et al.  Dissipativity-Preserving Model Reduction for Takagi–Sugeno Fuzzy Systems , 2019, IEEE Transactions on Fuzzy Systems.

[6]  Qing-Long Han,et al.  A Threshold-Parameter-Dependent Approach to Designing Distributed Event-Triggered $H_{\infty}$ Consensus Filters Over Sensor Networks , 2019, IEEE Transactions on Cybernetics.

[7]  Yuanqing Xia,et al.  Exponential Stabilization of Takagi–Sugeno Fuzzy Systems With Aperiodic Sampling: An Aperiodic Adaptive Event-Triggered Method , 2019, IEEE Transactions on Systems, Man, and Cybernetics: Systems.

[8]  Lei Zou,et al.  Probabilistic‐constrained filtering for a class of nonlinear systems with improved static event‐triggered communication , 2018, International Journal of Robust and Nonlinear Control.

[9]  Dong Yue,et al.  Relaxed Control Design of Discrete-Time Takagi–Sugeno Fuzzy Systems: An Event-Triggered Real-Time Scheduling Approach , 2018, IEEE Transactions on Systems, Man, and Cybernetics: Systems.

[10]  Shaocheng Tong,et al.  Fuzzy Adaptive Control Design Strategy of Nonlinear Switched Large-Scale Systems , 2018, IEEE Transactions on Systems, Man, and Cybernetics: Systems.

[11]  Qing-Long Han,et al.  A Novel Finite-Sum Inequality-Based Method for Robust $H_\infty$ Control of Uncertain Discrete-Time Takagi–Sugeno Fuzzy Systems With Interval-Like Time-Varying Delays , 2018, IEEE Transactions on Cybernetics.

[12]  Hak-Keung Lam,et al.  A New Approach to Stability and Stabilization Analysis for Continuous-Time Takagi–Sugeno Fuzzy Systems With Time Delay , 2018, IEEE Transactions on Fuzzy Systems.

[13]  Ju H. Park,et al.  Event-Based Reliable Dissipative Filtering for T–S Fuzzy Systems With Asynchronous Constraints , 2018, IEEE Transactions on Fuzzy Systems.

[14]  Guang-Hong Yang,et al.  Decentralized Fault Detection for Affine T–S Fuzzy Large-Scale Systems With Quantized Measurements , 2018, IEEE Transactions on Fuzzy Systems.

[15]  Sing Kiong Nguang,et al.  Distributed Filtering for Discrete-Time T–S Fuzzy Systems With Incomplete Measurements , 2018, IEEE Transactions on Fuzzy Systems.

[16]  Hamid Reza Karimi,et al.  Dissipativity-Based Fuzzy Integral Sliding Mode Control of Continuous-Time T-S Fuzzy Systems , 2018, IEEE Transactions on Fuzzy Systems.

[17]  Ding Zhai,et al.  Switched Adaptive Fuzzy Tracking Control for a Class of Switched Nonlinear Systems Under Arbitrary Switching , 2018, IEEE Transactions on Fuzzy Systems.

[18]  Xiangpeng Xie,et al.  Event-Triggered Predictive Control for Networked Nonlinear Systems With Imperfect Premise Matching , 2018, IEEE Transactions on Fuzzy Systems.

[19]  Shaocheng Tong,et al.  Adaptive Fuzzy Output Feedback Control for a Class of Nonlinear Systems With Full State Constraints , 2018, IEEE Transactions on Fuzzy Systems.

[20]  Ju H. Park,et al.  Fuzzy Resilient Energy-to-Peak Filtering for Continuous-Time Nonlinear Systems , 2017, IEEE Transactions on Fuzzy Systems.

[21]  Guang-Hong Yang,et al.  Finite Frequency $L_{2}{-}L_{\infty }$ Filtering of T-S Fuzzy Systems With Unknown Membership Functions , 2017, IEEE Transactions on Systems, Man, and Cybernetics: Systems.

[22]  Changyin Sun,et al.  Model Identification and Control Design for a Humanoid Robot , 2017, IEEE Transactions on Systems, Man, and Cybernetics: Systems.

[23]  Zhigang Zeng,et al.  Aperiodic Sampled-Data Sliding-Mode Control of Fuzzy Systems With Communication Delays Via the Event-Triggered Method , 2016, IEEE Transactions on Fuzzy Systems.

[24]  Hak-Keung Lam,et al.  Observer-Based Fault Detection for Nonlinear Systems With Sensor Fault and Limited Communication Capacity , 2016, IEEE Transactions on Automatic Control.

[25]  Dong Yue,et al.  Control Synthesis of Discrete-Time T–S Fuzzy Systems via a Multi-Instant Homogenous Polynomial Approach , 2016, IEEE Transactions on Cybernetics.

[26]  C. L. Philip Chen,et al.  Fuzzy Adaptive Quantized Control for a Class of Stochastic Nonlinear Uncertain Systems , 2016, IEEE Transactions on Cybernetics.

[27]  Ligang Wu,et al.  Model Approximation for Fuzzy Switched Systems With Stochastic Perturbation , 2015, IEEE Transactions on Fuzzy Systems.

[28]  Xiangpeng Xie,et al.  An efficient approach for reducing the conservatism of LMI-based stability conditions for continuous-time T-S fuzzy systems , 2015, Fuzzy Sets Syst..

[29]  Thierry-Marie Guerra,et al.  Controller Design for TS Models Using Delayed Nonquadratic Lyapunov Functions , 2015, IEEE Transactions on Cybernetics.

[30]  Guang-Hong Yang,et al.  Fault Detection and Isolation for a Class of Uncertain State-Feedback Fuzzy Control Systems , 2015, IEEE Transactions on Fuzzy Systems.

[31]  Péter Baranyi,et al.  The Generalized TP Model Transformation for T–S Fuzzy Model Manipulation and Generalized Stability Verification , 2014, IEEE Transactions on Fuzzy Systems.

[32]  Young Hoon Joo,et al.  On the Generalized Local Stability and Local Stabilization Conditions for Discrete-Time Takagi–Sugeno Fuzzy Systems , 2014, IEEE Transactions on Fuzzy Systems.

[33]  Xiangpeng Xie,et al.  Control Synthesis of Discrete-Time T–S Fuzzy Systems Based on a Novel Non-PDC Control Scheme , 2013, IEEE Transactions on Fuzzy Systems.

[34]  J. Lauber,et al.  An Efficient Lyapunov Function for Discrete T–S Models: Observer Design , 2012, IEEE Transactions on Fuzzy Systems.

[35]  Xiangpeng Xie,et al.  Relaxed Stability Conditions for Continuous-Time T–S Fuzzy-Control Systems Via Augmented Multi-Indexed Matrix Approach , 2011, IEEE Transactions on Fuzzy Systems.

[36]  Radu-Emil Precup,et al.  A survey on industrial applications of fuzzy control , 2011, Comput. Ind..

[37]  Baocang Ding,et al.  Homogeneous Polynomially Nonquadratic Stabilization of Discrete-Time Takagi–Sugeno Systems via Nonparallel Distributed Compensation Law , 2010, IEEE Transactions on Fuzzy Systems.

[38]  Jin Bae Park,et al.  Improvement on Nonquadratic Stabilization of Discrete-Time Takagi–Sugeno Fuzzy Systems: Multiple-Parameterization Approach , 2010, IEEE Transactions on Fuzzy Systems.

[39]  Baocang Ding,et al.  Stabilization of Takagi–Sugeno Model via Nonparallel Distributed Compensation Law , 2008, IEEE Transactions on Fuzzy Systems.

[40]  Jun Yang,et al.  T-S Fuzzy-Model-Based Robust $H_{\infty}$ Design for Networked Control Systems With Uncertainties , 2007, IEEE Transactions on Industrial Informatics.

[41]  Ricardo C. L. F. Oliveira,et al.  Parameter-Dependent LMIs in Robust Analysis: Characterization of Homogeneous Polynomially Parameter-Dependent Solutions Via LMI Relaxations , 2007, IEEE Transactions on Automatic Control.

[42]  Thierry-Marie Guerra,et al.  LMI-based relaxed nonquadratic stabilization conditions for nonlinear systems in the Takagi-Sugeno's form , 2004, Autom..

[43]  Michio Sugeno,et al.  Fuzzy identification of systems and its applications to modeling and control , 1985, IEEE Transactions on Systems, Man, and Cybernetics.