Functional Observer-Based T–S Fuzzy Systems for Quadratic Stability of Power System Synchronous Generator

This paper presents the functional observer-based Takagi–Sugeno fuzzy controller to enhance the dynamic response of the synchronous generator infinite bus power system under low-frequency oscillations. The unmeasurable states of the synchronous generator are estimated by using minimum order functional observer. The T–S fuzzy controller rules are a function of the estimated states in which the functional observer based on T–S fuzzy conditions presented in rank equality form. The Lyapunov theory in the form of linear matrix inequalities (LMIs) represented here in this paper to synthesis the functional observer stability. Small disturbances are taken to simulate the synchronous generator oscillations. The results clearly show that our scheme is a better response when compared with the full observer-based T–S fuzzy system.

[1]  Muhammad Shamrooz Aslam,et al.  Observer-based dissipative output feedback control for network T–S fuzzy systems under time delays with mismatch premise , 2019, Nonlinear Dynamics.

[2]  Xiangpeng Xie,et al.  Observer-Based Non-PDC Control for Networked T–S Fuzzy Systems With an Event-Triggered Communication , 2017, IEEE Transactions on Cybernetics.

[3]  Jinde Cao,et al.  Static output feedback control of switched systems with quantization: A nonhomogeneous sojourn probability approach , 2019, International Journal of Robust and Nonlinear Control.

[4]  Begnini Mauricio,et al.  PRACTICAL IMPLEMENTATION OF A SIMPLE AND EFFECTIVE ROBUST ADAPTIVE FUZZY VARIABLE STRUCTURE TRAJECTORY TRACKING CONTROL FOR DIFFERENTIAL WHEELED MOBILE ROBOTS , 2017 .

[5]  Robert Shorten,et al.  On the interpretation and identification of dynamic Takagi-Sugeno fuzzy models , 2000, IEEE Trans. Fuzzy Syst..

[6]  Tyrone Fernando,et al.  Existence Conditions for Functional Observability From an Eigenspace Perspective , 2011, IEEE Transactions on Automatic Control.

[7]  Peng Shi,et al.  Functional observer-based fuzzy controller design for continuous nonlinear systems , 2018, Int. J. Syst. Sci..

[8]  H. Trinh,et al.  Functional Observers for Dynamical Systems , 2011 .

[9]  Zengqi Sun,et al.  Analysis and design of fuzzy reduced-dimensional observer and fuzzy functional observer , 2001, Fuzzy Sets Syst..

[10]  Hamid Reza Karimi,et al.  State estimation on positive Markovian jump systems with time-varying delay and uncertain transition probabilities , 2016, Inf. Sci..

[11]  Chian-Song Chiu,et al.  Robust Maximum Power Tracking Control of Uncertain Photovoltaic Systems: A Unified T-S Fuzzy Model-Based Approach , 2011, IEEE Transactions on Control Systems Technology.

[12]  K. Wong,et al.  A novel quasi-decentralized functional observer approach to LFC of interconnected power systems , 2016, 2016 IEEE Power and Energy Society General Meeting (PESGM).

[13]  Guang-Hong Yang,et al.  Nonfragile $H_{\infty}$ Filter Design for T–S Fuzzy Systems in Standard Form , 2014, IEEE Transactions on Industrial Electronics.

[14]  M. Sami Fadali Fuzzy Functional Observers for Dynamic TSK Systems , 2005, The 14th IEEE International Conference on Fuzzy Systems, 2005. FUZZ '05..

[15]  Hamid Reza Karimi,et al.  Mixed L - / L 1 fault detection filter design for fuzzy positive linear systems with time-varying delays , 2014 .

[16]  Peng Shi,et al.  A Novel Observer-Based Output Feedback Controller Design for Discrete-Time Fuzzy Systems , 2015, IEEE Transactions on Fuzzy Systems.

[17]  H. Trinh,et al.  On the Existence and Design of Functional Observers for Linear Systems , 2007, 2007 International Conference on Mechatronics and Automation.

[18]  Peng Shi,et al.  Mixed H-Infinity and Passive Filtering for Discrete Fuzzy Neural Networks With Stochastic Jumps and Time Delays , 2016, IEEE Transactions on Neural Networks and Learning Systems.

[19]  A. Rachid,et al.  Quadratic stability of synchronous machine via Takagi-Sugeno fuzzy control , 2012, 2012 International Conference on Multimedia Computing and Systems.

[20]  Peng Shi,et al.  Fault Estimation Observer Design for Discrete-Time Takagi–Sugeno Fuzzy Systems Based on Piecewise Lyapunov Functions , 2012, IEEE Transactions on Fuzzy Systems.

[21]  Hieu Minh Trinh,et al.  Partial state and unknown input estimation for time-delay systems , 2012, Int. J. Syst. Sci..

[22]  Kazuo Tanaka,et al.  Fuzzy regulators and fuzzy observers: relaxed stability conditions and LMI-based designs , 1998, IEEE Trans. Fuzzy Syst..

[23]  Guang-Hong Yang,et al.  Event-triggered fuzzy control for nonlinear networked control systems , 2017, Fuzzy Sets Syst..

[24]  Wenhai Qi,et al.  Finite-time stabilization of T-S fuzzy semi-Markov switching systems: A coupling memory sampled-data control approach , 2020, J. Frankl. Inst..

[25]  D. Luenberger An introduction to observers , 1971 .

[26]  Guang-Hong Yang,et al.  Nonfragile $H_{\infty}$ Filtering of Continuous-Time Fuzzy Systems , 2011, IEEE Transactions on Signal Processing.

[27]  Hak-Keung Lam,et al.  Asynchronous Piecewise Output-Feedback Control for Large-Scale Fuzzy Systems via Distributed Event-Triggering Schemes , 2018, IEEE Transactions on Fuzzy Systems.

[28]  Jinde Cao,et al.  Hidden Markov Model-Based Nonfragile State Estimation of Switched Neural Network With Probabilistic Quantized Outputs , 2020, IEEE Transactions on Cybernetics.

[29]  Guang-Hong Yang,et al.  A descriptor representation approach to observer-based Hinfinity control synthesis for discrete-time fuzzy systems , 2011, Fuzzy Sets Syst..

[30]  Mohamed Darouach Existence and design of functional observers for linear systems , 2000, IEEE Trans. Autom. Control..

[31]  Kazuo Tanaka,et al.  Fuzzy Control Systems Design and Analysis: A Linear Matrix Inequality Approach , 2008 .