Dynamic Modeling of a Synchronous Generator Using T-S Fuzzy Approach

Similar documents
ENGI9496 Lecture Notes Multiport Models in Mechanics

On the Coordinated Control of Multiple HVDC Links: Modal Analysis Approach

Overview Electrical Machines and Drives

TORQUE-SPEED ADAPTIVE OBSERVER AND INERTIA IDENTIFICATION WITHOUT CURRENT TRANSDUCERS FOR CONTROL OF ELECTRIC DRIVES

Solutions to Practice Problems

Responsiveness Improvement of Idling Speed Control for Automotive Using SMC

Multirate Digital Control for Fuzzy Systems: LMI-Based Design and Stability Analysis

WHY NOT USE THE ENTROPY METHOD FOR WEIGHT ESTIMATION?

Physics 3A: Linear Momentum. Physics 3A: Linear Momentum. Physics 3A: Linear Momentum. Physics 3A: Linear Momentum

Design of dual-loop attitude controller for target missile based on fuzzy variable structure

A Particle Swarm approach for the Design of Variable Structure Stabilizer for a Nonlinear Model of SMIB System

Adaptive sliding mode reliable excitation control design for power systems

6.3.7 Example with Runga Kutta 4 th order method

IMPROVED TRAJECTORY CONTROL FOR AN INTERIOR PERMANENT MAGNET SYNCHRONOUS MOTOR DRIVE WITH EXTENDED OPERATING LIMIT

Week 11: Chapter 11. The Vector Product. The Vector Product Defined. The Vector Product and Torque. More About the Vector Product

Equivalent Circuit Analysis of Interior Permanent Magnet Synchronous Motor Considering Magnetic saturation

Scroll Generation with Inductorless Chua s Circuit and Wien Bridge Oscillator

Note 10. Modeling and Simulation of Dynamic Systems

Linearity. If kx is applied to the element, the output must be ky. kx ky. 2. additivity property. x 1 y 1, x 2 y 2

Application of Gravitational Search Algorithm for Optimal Reactive Power Dispatch Problem

THE EFFECT OF TORSIONAL RIGIDITY BETWEEN ELEMENTS ON FREE VIBRATIONS OF A TELESCOPIC HYDRAULIC CYLINDER SUBJECTED TO EULER S LOAD

Introduction. - The Second Lyapunov Method. - The First Lyapunov Method

Calculation of Coherent Synchrotron Radiation in General Particle Tracer

Variable Structure Control ~ Motor Control

Automatic PID Controller Tuning for Robots with Nonlinear Friction at the Joints

Parks Equations Generalised Machines. Represent ac machines in the simplest possible way.

Precision Tracking Control of a Piezoelectric-Actuated System

Modeling and Simulation of a Hexapod Machine Tool for the Dynamic Stability Analysis of Milling Processes. C. Henninger, P.

Design of Optimum Controllers for Gas Turbine Engines

p(z) = 1 a e z/a 1(z 0) yi a i x (1/a) exp y i a i x a i=1 n i=1 (y i a i x) inf 1 (y Ax) inf Ax y (1 ν) y if A (1 ν) = 0 otherwise

SAMPLE PAGES TO BE FOLLOWED EXACTLY IN PREPARING SCRIPTS. ADAPTIVE SPEED CONTROL OF PMSMs WITH UNKNOWN LOAD TORQUE

A NOVEL DESIGN APPROACH FOR MULTIVARIABLE QUANTITATIVE FEEDBACK DESIGN WITH TRACKING ERROR SPECIFICATIONS

Transfer Functions. Convenient representation of a linear, dynamic model. A transfer function (TF) relates one input and one output: ( ) system

ECE 522 Power Systems Analysis II 2 Power System Modeling

Irregular vibrations in multi-mass discrete-continuous systems torsionally deformed

The equation of motion of a dynamical system is given by a set of differential equations. That is (1)

829. An adaptive method for inertia force identification in cantilever under moving mass

Chapter 7: Conservation of Energy

Discrete time state feedback with setpoint control, actual state observer and load estimation for a tumor growth model

Output Feedback Robust Stabilization of the Decoupled Multiple Model

High-Order Hamilton s Principle and the Hamilton s Principle of High-Order Lagrangian Function

Parameter Estimation for Dynamic System using Unscented Kalman filter

Controller Design for Networked Control Systems in Multiple-packet Transmission with Random Delays

ADAPTIVE FUZZY SLIDING MODE CONTROL FOR X-Z INVERTED PENDULUM

ECE 422 Power System Operations & Planning 2 Synchronous Machine Modeling

COEFFICIENT DIAGRAM: A NOVEL TOOL IN POLYNOMIAL CONTROLLER DESIGN

Copyright 2004 by Oxford University Press, Inc.

( ) = : a torque vector composed of shoulder torque and elbow torque, corresponding to

Odd/Even Scroll Generation with Inductorless Chua s and Wien Bridge Oscillator Circuits

A Fuzzy-Neural Adaptive Iterative Learning Control for Freeway Traffic Flow Systems

Off-policy Reinforcement Learning for Robust Control of Discrete-time Uncertain Linear Systems

χ x B E (c) Figure 2.1.1: (a) a material particle in a body, (b) a place in space, (c) a configuration of the body

Spring 2002 Lecture #13

Wavelet chaotic neural networks and their application to continuous function optimization

Modeling and Control of Wind Energy Conversion Systems under High Wind Turbulence using Conventional, Fuzzy Logic and H-Infinity Controllers

Passive Bilateral Teleoperation with Constant Time Delays

The Study of Teaching-learning-based Optimization Algorithm

Chapter 6 Electrical Systems and Electromechanical Systems

Robust Fuzzy Control of Electrical Manipulators

Massachusetts Institute of Technology Department of Electrical Engineering and Computer Science Circuits and Electronics Spring 2001

Study on Active Micro-vibration Isolation System with Linear Motor Actuator. Gong-yu PAN, Wen-yan GU and Dong LI

APPLICATION OF A SLIDING MODE OBSERVER FOR SENSORLESS OPERATION OF SWITCHED RELUCTANCE MOTORS. Stefan Brock

Phys 331: Ch 7,.2 Unconstrained Lagrange s Equations 1

New Liu Estimators for the Poisson Regression Model: Method and Application

Time dependent weight functions for the Trajectory Piecewise-Linear approach?

Fundamental loop-current method using virtual voltage sources technique for special cases

Dual Proportional Integral Controller of Two-Area Load Frequency Control Based Gravitational Search Algorithm

Limit Cycle Generation for Multi-Modal and 2-Dimensional Piecewise Affine Control Systems

Observer Design for a Class of Discrete-Time Takagi-Sugeno Implicit Models Subject to Unknown Inputs

Advanced Mechanical Elements

Chapter - 2. Distribution System Power Flow Analysis

Clock-Gating and Its Application to Low Power Design of Sequential Circuits

Journal of Engineering Science and Technology Review 11 (4) (2018) Research Article

Finite Element Modelling of truss/cable structures

POTENTIAL ENERGY BASED STABILITY ANALYSIS OF FUZZY LINGUISTIC SYSTEMS. 1. Introduction

LATERAL AUTOPILOT DESIGN FOR A UAV USING COEFFICIENT DIAGRAM METHOD

Electrical Circuits 2.1 INTRODUCTION CHAPTER

Active Vibration Control Based on a 3-DOF Dual Compliant Parallel Robot Using LQR Algorithm

Chapter 2 Transformations and Expectations. , and define f

Pop-Click Noise Detection Using Inter-Frame Correlation for Improved Portable Auditory Sensing

Solving Fractional Nonlinear Fredholm Integro-differential Equations via Hybrid of Rationalized Haar Functions

K = 100 J. [kg (m/s) ] K = mv = (0.15)(36.5) !!! Lethal energies. m [kg ] J s (Joule) Kinetic Energy (energy of motion) E or KE.

Neuro-Adaptive Design - I:

Analysis of the Magnetomotive Force of a Three-Phase Winding with Concentrated Coils and Different Symmetry Features

Application of Linear Model Predictive Control and Input-Output Linearization to Constrained Control of 3D Cable Robots

A MODIFIED METHOD FOR SOLVING SYSTEM OF NONLINEAR EQUATIONS

Field and Wave Electromagnetic. Chapter.4

6th International Conference on Advanced Design and Manufacturing Engineering (ICADME 2016)

Part C Dynamics and Statics of Rigid Body. Chapter 5 Rotation of a Rigid Body About a Fixed Axis

Mechanics Physics 151

DESIGN OF STABLE TWO-DIMENSIONAL IIR NOTCH FILTER USING ROOT MAP

Power law and dimension of the maximum value for belief distribution with the max Deng entropy

A revised adaptive fuzzy sliding mode controller for robotic manipulators

The Analysis of Coriolis Effect on a Robot Manipulator

Boise State University Department of Electrical and Computer Engineering ECE 212L Circuit Analysis and Design Lab

Appendix B: Resampling Algorithms

Week 5: Neural Networks

1 GSW Iterative Techniques for y = Ax

Controller Design of High Order Nonholonomic System with Nonlinear Drifts

Robust Multi-Criteria Optimal Fuzzy Control of Continuous-Time Nonlinear Systems

Transcription:

e-issn : 0975-0 Hee-Jn Lee / Internatonal Journal of Engneerng an echnology (IJE) Dynamc oelng of a Synchronous Generator Usng -S Fuzzy Approach Hee-Jn Lee Department of Electronc Engneerng Kumoh Natonal Insttute of echnology, Gum-s, Gyeongbuk, Korea jnlee@kumoh.ac.kr Abstract he ynamc behavor of power systems s affecte by the nteractons between lnear an nonlnear components. o analyze those complcate power systems, the lnear approaches have been wely use so far. Especally, a synchronous generator has been esgne by usng lnear moels an tratonal technues. However, ue to ts we operatng range, comple ynamcs, transent performances, an ts nonlneartes, t cannot be accurately moele as lnear methos base on smallsgnal analyss. hs paper escrbes an applcaton of the akak-sugeno (-S) fuzzy metho to moel the synchronous generator n a sngle-machne nfnte bus (SIB) system. he -S fuzzy moel can prove a hghly nonlnear functonal relaton wth a comparatvely small number of fuzzy rules. he smulaton results show that the propose the -S fuzzy moelng captures all ynamc characterstcs for the synchronous generator, whch are eactly same as those by the conventonal nonlnear moelng methos. Keywors ynamc moelng; power system; synchronous generator; -S fuzzy. I. INRODUCION A synchronous generator n a power system s a nonlnear fast-actng multple-nput multple-output (IO) evce. Due to ts we operatng range, comple ynamcs, nonlnearty, an the changng system confguraton, the entre system cannot be accurately represente by a fe moel, whch s then use for the esgn of conventonal lnear system/controllers. Otherwse, by usng the IF-HEN rule, the akag-sugeno (-S) fuzzy moelng makes t possble to analyze a nonlnear system by appromatng the system as a lnear nput-output system n certan range []-[6]. hs range can be epane over the range efne by other lnearzaton technues wthout losng generalty when the system operates n we range of operatng ponts [7]. Also, the stablty of the system can be analyze by usng a lnear matr neualty (LI) metho base on the Lyapunov conton, whch can be formulate by the -S fuzzy moelng. It has two avantages; one s the convenence of analyss through lnearzaton, an the other s the accuracy of analyzng nonlnear systems. oreover, ths LI technue on the -S fuzzy moelng can prove the powerful capablty to esgn the robust controller of any nonlnear ynamc systems. In ths paper, the -S fuzzy moelng metho s frstly apple to moel an nverte penulum system. hen, t s use to moel the synchronous generator, whch can be escrbe by the fourth-orer nonlnear fferental euatons, n a sngle-machne nfnte bus (SIB) power system. By applyng the large (three-phase short crcut) an small (± 5% step changes n the reference voltage of ecter) sturbances to the SIB system, ts effectveness s evaluate to show the same ynamc behavors as gven n the eact nonlnear moel of the synchronous generator. II. -S FUZZY ODELING A. akag-sugeno Fuzzy oel here s neee new moel whch s fferent from lnear moel to analyze more accurate when large accents occur. In ths paper, the -S fuzzy metho s use to analyze nonlnear system. he -S fuzzy system can be represente accorng to Fg. structure. It s har to analyze nonlnear system whch has a lnear an a nonlnear part. he nonlnear system s converte to -S fuzzy moel to analyze easly. Fg.. Approach base on the -S fuzzy moelng p-issn : 39-863 Vol 8 No Apr-ay 06 97

e-issn : 0975-0 Hee-Jn Lee / Internatonal Journal of Engneerng an echnology (IJE) he th rule of the affne -S fuzzy moels are followng forms, where contnuous fuzzy system (CFS), respectvely. oel Rule IF z (t) s an an z p (t) s p, HEN A C,,,, r Here, j s the fuzzy set an r s the number of moel rules; (t) R n s the state vector, A R nn, C R nm ; z (t),, z p (t) are known premse varable that may be functons of the state varables, eternal sturbances, an/or tme. Each lnear euaton A C s represente n () [7]. Where n ( ) ( ), j j j r {A C } ( ){A C } () r r h h( ) ( ) r ( ) h ( ) 0, r h ( ) () B. Desgn Eample: Inverte Penulum In ths secton, an llustratve eample s prove to emonstrate the valty of the suggeste stablty analyss an synthess metho [8]. ass ( ) Control voltage DC motor 0 : Ø Ø Ø l Gear Pvot pont Fg.. Inverte penulum controlle by a DC motor L R I V v K K 0 b b m b Fg. 3. oel of an armature-controlle DC motor he plant to be controlle s an electro-mechancal system as shown n Fg.. otor s nerta s neglgble when compare wth that of penulum. he euvalent crcut of ths system s llustrate n Fg. 3. he torue s supple by motor, that s, m KmI. (3) the torue of penulum s elvere by gear (0:), that s, 0 0K I. () By usng Krchhoff s loop rule to get euaton p m m p-issn : 39-863 Vol 8 No Apr-ay 06 975

e-issn : 0975-0 Hee-Jn Lee / Internatonal Journal of Engneerng an echnology (IJE) V LI RI K 0 b. (5) he knetc torue apple penulum s sum of torue of knetc energy an torue of gravty. p l m lmg sn (6) where, (-) sgn means that the knetc torue s n opposton to torue of gravty. he ynamc euaton s gven by 3 ABu where the varable an the parameters are as follows [9]. [ ] [ I] 0 0 sn A K 0 K 0 K3 K g 0K K, m 0K K, b R K 3, K, K5 l lm L L L (, the angle measure wth respect to the vertcal as); (, the tme ervatve of ); u (the control voltage) = 0; m (the mass of the penulum) = kg; l (the stance of the center of mass m from the pvot pont) = m; g (gravtatonal constant) = 9.8 m/s ; R (euvalent resstance) = Ω; L (euvalent nuctance) = 00 mh; K b K m (constant value of generator) = 0. Vs/ra; (constant value of mass) = 0. Nm/A; 0 B 0 K 5 In ths paper, a controller oesn t be consere. So, the control nput u = 0. It s straghtforwar to compute sn the -S fuzzy system. In ths eample, the nonlnear term s only. he system matr A s separate nto matr. IF-HEN rules are follows, Inverte Penulum oel Rule IF () t s, HEN A IF () t s, HEN A 0 0 A K 0 K 0 K3 K 0 0 0 K3 K, A K 0 K Nonlnear system euaton (7) s the same as the -S fuzzy euaton (8) when t s satsfe follows by ()- (). Euaton (0) can be rewrtten by (8) an (9). hk hk K (7) (8) h( )A ha h A, h h (9) sn sn h ( h) p-issn : 39-863 Vol 8 No Apr-ay 06 976

e-issn : 0975-0 Hee-Jn Lee / Internatonal Journal of Engneerng an echnology (IJE) sn h( ) sn h Euaton (0) s always satsfe regarless of values of an. Here,, an 0 are assume. (0) 0 8 6 0 = 8.0 0 = 5.0 0 = 0.0 0 = -5.0 0 = -8.0 [ra] 0 - - -6 0 5 0 5 me [sec] 0 8 6 (a) 0 = 8.0 0 = 5.0 0 = 0.0 0 = -5.0 0 = -8.0 [ra] 0 - - -6 0 5 0 5 me [sec] (b) Fg.. Penulum poston (u=0, =.5, 3 =0) (a) Nonlnear moel (b) -S fuzzy moel Fg. shows the nverte penulum pvot angle as a tme an varous ntal angle spee ( 0 ). Fg. (a) s the nonlnear moel n (7) where the system has fferent stable ponts accorng to varous ntal angle spees. Fg. (b) s the -S fuzzy moel n (8), where ts trace s the same as nonlnear moel. hs eample proves the valty of the -S fuzzy moelng. III. SYNCHRONOUS ACHINE ODELING A. Synchronous oelng he SIB system s shown n Fg. 5. he system s one of the funamental systems an can be epane mult-machne system easly [0]. In ths paper, fourth-orer synchronous generator moel s escrbe by usng the -S fuzzy moelng metho. he state varables are -as voltage, -as voltage, rotor angle an rotor spee [], []. he synchronous generator can be epresse by usng - as n the phasor agram of Fg. 6 n steay state [3], []. p-issn : 39-863 Vol 8 No Apr-ay 06 977

e-issn : 0975-0 Hee-Jn Lee / Internatonal Journal of Engneerng an echnology (IJE) hese mathematcal moels are gven n ()-(3). Armature an transmsson resstance are neglgble compare wth reactance. Usng Park s transform, - as voltage euatons are follows. he rotor angle an rotor spee are escrbe by. E E ( ) I E t o f s t E o E ( ) I () t H E I E I ( ) II FW () t s Fg. 5. Sngle-machne nfnte bus system E as j I V t V b I ( / In () an (), (, / I, I as Fg. 6. Steay state phasor agram of the SIB system ) are the - as components of current n the armature wnngs, ) s the - as components of (steay, transent) reactance n the armature wnngs, the fel voltage, o an o are tme constants of - as transent. In (), s the rotor angle wth reference to the nfnte bus, s s the synchronous spee n steay state, m s turbne output shaft torue, FW s frctonal an wnage torue, an H s the polar moment of nerta. By usng voltage euaton n (), an swng euaton n (), the fourth-orer set of fferental euaton can be foun for the ynamc moel of the generator. he current euatons for the transmsson system (n Fg. 5) are gven n (3), whch are erve from the methos of crcut an Park s transformaton theory E Vb cos E Vbsn I, I (3) Where I an I are the - as components of transmsson current, E components of transent voltage, V b s the nfnte bus voltage, reactance. B. -S Fuzzy to the SIB System For the -S fuzzy moelng, euaton (), (5) are gven n below. AC, E E e an e E f s E are the - as e s the component of transmsson lne p-issn : 39-863 Vol 8 No Apr-ay 06 978

e-issn : 0975-0 Hee-Jn Lee / Internatonal Journal of Engneerng an echnology (IJE) Vb( ) cos ( ) 0 ( ) 0 o e o e Vb( ) sn 0 ( ) ( ) 0 A o e o e 0 0 0 s Vbsn s Vbcos ( ) ( ) 0 0 H e H e E C 0 f s m s o H he SIB system gven n () has nonlnear terms ( cos, sn, sn, cos ). atr A s ve nto 6 lnear matr by the -S fuzzy moelng. he nput-output form of the fuzzy system of () s represente as 6 () h( ){A C}, 0 h ( ), h ( ) (5) a an n values of nonlnear terms escrbe n able are nserte the poston of separate matr by the -S fuzzy rule. Each nonlnear terms have values an represente follow IF-HEN rule. 6 ABLE I. FUZZY ODEL PARAEERS OF HE SIB SYSE Nonlnear terms cos sn Inserte embershp functon values a n a n 0 0 cos sn sn 0 cos 0 3 sn cos 3 3 he SIB System oel Rule IF s a, s a, 3 s a an s a, HEN A C, IF s a, s a, 3 s a an s n, HEN A C, IF s n, s n, 3 s n an s n, HEN A6 C,... h 3 h 3 h 6 3 For eample, to fn A, nonlnear term cos / s replace by, sn / s replace by, sn s replace by, an cos s replace by. Vb( ) ( ) 0 ( ) 0 o e o e Vb( ) 0 ( ) ( ) 0 A o e o e 0 0 0 s Vb s V b ( ) ( ) 0 0 H e H e he 6 lnear matres can be foun above metho. Rotor angle ( ) of synchronous generator s boune 0 / by (5) to satsfy the -S fuzzy moelng metho. p-issn : 39-863 Vol 8 No Apr-ay 06 979

e-issn : 0975-0 Hee-Jn Lee / Internatonal Journal of Engneerng an echnology (IJE) C. Smulaton Results he -S fuzzy moel must have ynamc characterstcs the same as nonlnear moel, to confrm the valaton of the -S fuzzy moelng. Smulaton parameters are gven follows. f e s (funamental freuency) = 60 Hz; (steay state rotor spee) = 0 ra/s; (steay state -as reactance) =.8 Ω; (transent -as reactance) = 0.3 Ω; (steay state -as reactance) =.7 Ω; (transent -as reactance) = 0. Ω; e (transmsson lne reactance) = 0. Ω; o (transent -as tme constant) = 8; o (transent -as tme constant) = 0.; wo fferent types of sturbances, namely, a ± 5% step changes n the reference voltage of ecter an a 00 ms three-phase short crcut at the nfnte bus n Fg. 5, are carre out to evaluate the effectveness of the -S fuzzy moelng for the synchronous generator..05 -S fuzzy moel Nonlnear moel.0 ermnal Voltage [pu].03.0.0 0.99 0 5 0 5 0 5 30 35 0 5 me [sec]. (a) -S fuzzy moel Nonlnear moel 0.9 Rotor angle [ra] 0.8 0.7 0.6 0.5 0. 0 0.5.5.5 3 3.5.5 5 me [sec] (b) Fg. 7. Performance evaluaton of the -S fuzzy moelng: (a) ermnal voltage response when 5(%) step-change s apple to the ectaton system (b) Rotor angle response when 00 ms to the nfnte bus three-phase short crcut fault s apple Fg. 7 (a) shows termnal voltage response of synchronous generator when the etaton voltage changes. he termnal voltage ncreases as the etaton voltage ncreases at 5 sec. When the etaton voltage ecreases to ntal value at 5 sec, the termnal voltage ecreases, too. he sol lne whch ncates the nonlnear moel shows same pattern wth the otte lne that represents the -S fuzzy moel. Fg. 7 (b) shows the smulaton p-issn : 39-863 Vol 8 No Apr-ay 06 980

e-issn : 0975-0 Hee-Jn Lee / Internatonal Journal of Engneerng an echnology (IJE) result when three-phase short crcut fault occurs for 0. sec. he ampng effect can be observe because of system unstablty when accent occurs. In ths case, the same routnes are observe n both moels; nonlnear moel (sol lne) an the -S fuzzy moel (otte moel). he effectveness of the -S fuzzy moel can be checke through these smulaton. IV. CONCLUSIONS hs paper propose the new moelng of synchronous generator by applyng the -S fuzzy metho n orer to analyze stablty of the nonlnear SIB system. Conventonal lnear moel cannot represent the characterstcs of synchronous generator whch has we operatng range, complcate ynamc characterstcs, an nonlnearty. he -S fuzzy moel shows more accuracy than the lnear moel because t consers nonlnear characterstcs. It wll be more easy to analyzng system stablty an esgnng controller by usng the -S fuzzy moel because nonlnear terms can be gnore when applyng Lyapunov conton. Acknowlegment hs paper was supporte by Kumoh Natonal Insttute of echnology References [] K. anaka an. Sugeno, Stablty analyss an esgn of fuzzy control systems, Fuzzy Sets System, vol. 5, pp. 36-56, 99. [] K. anaka,. Ikea, an H. O. Wang, Fuzzy regulators an fuzzy observers: Relae Stablty Contons an LI-Base Desgns, IEEE ransactons on Fuzzy Systems, vol.6, no., pp. 50-65, 998. [3] E. Km an S. Km, Stablty analyss an synthess for an affne fuzzy system va LI an ILI: a contnuous case, IEEE ransactons on Fuzzy Systems, vol. 0, no. 3, pp. 39-00, 00. [] E. Km,. Park, an S. J, A new approach to fuzzy moelng, IEEE transactons on fuzzy systems, vol. 5, no. 3, pp. 38-337, 997. [5] F. Cuesta, F. Gorllo, J. Aracl, an A. Ollero, Stablty analyss of nonlnear multvarable akak-sugeno fuzzy control systems, IEEE ransactons on Fuzzy Systems, vol. 7, no. 5, pp. 508-50, 999. [6] C. W. Park, C. H. Hyun,. S. Park, C. H. Lee, J. Km, an. Park, Control of uncertan fleble jont manpulator usng aaptve akag-sugeno fuzzy moel base controller, Proc. Of the 00 IEEE Internatonal Conference on Robotcs & Automaton, Seoul, Korea, ay -6, 00, pp. 985-990. [7]. akag an. Sugeno, Fuzzy entfcaton of systems an ts applcatons to moelng an control, IEEE ransactons on Systems, an, an Cybernetcs, vol. 5, no., pp. 6-3, 985. [8] S. H. Zak an C. A. accarley, State-feeback control of nonlnear systems, Internatonal Journal of Control, vol. 3, no. 5, pp. 97-5, 986. [9] S. Kawamoto, Nonlnear control an rgorous stablty analyss base on fuzzy system for nverte penulum, Proc. of the Ffth IEEE Internatonal Conference, New Orleans, LA, USA, Sep. 8-, 996 pp. 7-3. [0] J. W. Park, G. K. Venayagamoorthy, an R. G. Harley, LP/RBF neural-networks-base onlne global moel entfcaton of synchronous generator, IEEE ransactons on Inustral Electroncs, vol. 5, no. 6, pp. 685-695, 005. [] P. Kunur, Power System Stablty an Control, cgraw-hll, 993. [] P. W. Sauer an. A. Pa, Power System Dynamcs an Stablty, Prentce-Hall, 998. [3] P.. Anerson an A. A. Foua, Power System Control an Stablty, IEEE Press, 99. [] Ha Saaat, Power System Analyss, cgraw-hll, 00. p-issn : 39-863 Vol 8 No Apr-ay 06 98