• Journal of the Korean Institute of Intelligent Systems
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• v.10 no.2
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• pp.152-160
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• 2000

This paper addresses the analysis and design of fuzzy-model-based controller for nonlinear systems using extended PDC and optimal pole-placement schemes. In the design procedure, we represent the nonlinear system using a Takagi-Sugeno fkzy model and formulate the controller rules by using the extended parallel distributed compensator (EPDC) and construct an overall fuzzy logic controller by blending all local state feedback controllers with an optimal pole-placement scheme. Unlike the commonly used parallel distributed compensation technique, by blending a newly extended parallel distributed compensator and the optimal poleplacement schemes, we can design not only a local stable k z y controller but also an overall stable fuzzy controller to perform the tacking control objective. Furthermore, a stability analysis is carried out not only for the fuzzy model but also for a real nonlinear system. Finally. the effectiveness and feasibility of the proposed fizzy model-based controller design method has been shown through a simulation example.

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.1
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• pp.28-35
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• 2012

This paper presents the method for $H_{\infty}$ fuzzy controller design of discrete-time fuzzy Markovian jump systems with state and input time delays. The Takagi and Sugeno fuzzy model is employed to represent a delayed nonlinear system that possesses Markovian jump parameters. A stochastic mode dependent Lyapunov function is employed to analyze the stability and $H_{\infty}$ disturbance attenuation performance of the fuzzy Markovian jump systems with state and input time delays. A sufficient condition for the existence of fuzzy $H_{\infty}$ controller is given in terms of matrix inequalities. Also numerical example is presented to illustrate the efficiency of the proposed design method.

• The Transactions of the Korean Institute of Power Electronics
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• v.15 no.5
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• pp.343-351
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• 2010

This paper proposes a new fuzzy speed controller based on the Takagi-Sugeno fuzzy method to achieve a robust speed control of a permanent magnet synchronous motor (PMSM). The proposed controller requires the information of the load torque, so the second-order load torque observer is used to estimate it. The LMI condition is derived for the existence of the proposed fuzzy speed controller, and the gains of the controller are provided. It is proven that the augmented control system including the fuzzy speed controller and the load torque observer is exponentially stable. To evaluate the performance of the proposed fuzzy speed controller, the simulation and experimental results are presented under motor parameter variations. Finally, it is clearly verified that the proposed control method can accurately control the speed of a permanent magnet synchronous motor.

• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.3
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• pp.323-328
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• 2009

In this paper, a decentralized fuzzy output feedback controller for the nonlinear networked control system is proposed for wireless sensor network. Especially, it is assumed that the networked control system has the output packet loss and the input transmission failure. For the fuzzy control of the nonlinear subsystem, it presents Takagi-Sugeno (T-S) fuzzy model of each subsystem and it designs the decentralized fuzzy output feedback controller. The stability condition of the closed-loop system with the proposed controller is obtained by Lyapunov functional. The obtained stability condition is represented to the linear matrix inequality (LMI) form, and the control gain is obtained by LMI. An example is given to show the verification discussed throughout the paper.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.42 no.1
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• pp.13-21
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• 2005

This paper presents a fuzzy model-based approach for synchronization of time-delay chaotic system with input saturation. Time-delay chaotic drive and response system is respectively represented by Takagi-Sugeno (T-S) fuzzy model. Specially, the response system contains input saturation. Using the unidirectional linear error feedback and the parallel distributed compensation (PDC) scheme, we design fuzzy chaotic synchronization system and analyze local stability for synchronization error dynamics. Since time-delay in the transmission channel always exists, we also take it into consideration. The sufficient condition for the local stability of the fuzzy synchronization system with input saturation and time-delay is derived by applying Lyapunov-Krasovskii theory and solving linear matrix inequalities (LMI's) problem. A numerical example is given to demonstrate the validity of the proposed approach.

• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.2
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• pp.185-190
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• 2009

In this paper, an observer-based intelligent controller for the nonlinear networked control systems with packet loss is proposed for wireless sensor network. For the intelligent control of the nonlinear system, it uses the fuzzy system with Takagi-Sugeno (T-S) fuzzy model. The observer is designed for the fuzzy networked control system, and the output feedback controller is proposed for the stability of estimates and errors. The stability condition of the closed-loop system with the proposed controller is represented to the linear matrix inequality (LMI) form, and the observer and control gain are obtained by LMI. An example is given to show the verification discussed throughout the paper.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.39 no.1
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• pp.48-59
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• 2002

TSK(Takagi-Sugeno-Kang) fuzzy models with linear equations consequents, which represent complex nonlinear systems very well with a few rules, can be easily identified systematically by using input-output data. Many algorithms designing TSK fuzzy controllers based on TSK fuzzy models, which guarantees the stability of the closed system, have been suggested. On the contrary, singleton fuzzy models with singleton consequents can be easily understood and adjusted. In this paper, in order to utilize the merits of TSK fuzzy systems and singleton fuzzy systems, an algorithm transforming a TSK fuzzy model into a singleton fuzzy model having the same input-output relation is suggested. The suggested algorithm is applied to a fuzzy modelling example and a fuzzy controller design example.

• Journal of the Korean Institute of Intelligent Systems
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• v.16 no.2
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• pp.138-143
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• 2006

This paper presents intelligent digital redesign method for hybrid state space fuzzy-model-based controllers. For effectiveness and stabilization of continuous-time uncertain nonlinear systems under discrete-time controller, Takagi-Sugeno(TS) fuzzy model is used to represent the complex system. And global approach design problems viewed as a convex optimization problem that we minimize the error of the norm bounds between nonlinearly interpolated linear operators to be matched. Also, by using the bilinear and inverse bilinear approximation method, we analyzed nonlinear system's uncertain parts more precisely. When a sampling period is sufficiently small, the conversion of a continuous-time structured uncertain nonlinear system to an equivalent discrete-time system have proper reason. Sufficiently conditions for the global state-matching of the digitally controlled system are formulated in terms of linear matrix inequalities (LMIs). Finally, a TS fuzzy model for the chaotic Lorentz system is used as an . example to guarantee the stability and effectiveness of the proposed method.

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.3
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• pp.267-272
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• 2012

This paper propose the implementation of robust fuzzy controller for controlling an active magnetic bearing (AMB) system with 6 degree of freedom (DOF). A basic model with 6 DOF rotor dynamics and electromagnetic force equations for conical magnetic bearings is proposed. The developed model has severe nonlinearity and uncertainty so that it is not easy to obtain the control objective. For solving this problem, we use the Takagi-Sugeno (T-S) fuzzy model which is suitable for designing fuzzy controller. The control object in the AMB system enables the rotor to rotate without any phsical contact by using magnetic force. In this paper, we analyze the nonlinearity of the active magnetic bearing system by using fuzzy control algorithm and desing the robust control algorithm for solving the parameter variation. Simulation results for AMB are demonstrated to visualize the feasibility of the proposed method.

• Journal of the Korean Institute of Intelligent Systems
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• v.12 no.3
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• pp.239-245
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• 2002

In this Paper, we present a method for designing fuzzy $H_2/H_{\infty}$ controllers of delayed nonlinear systems with saturating input. Takagi-Sugeno fuzzy model is employed to represent delayed nonlinear systems with saturating input. The fuzzy control systems utilize the concept of the so-called parallel distributed compensation(PDC). Using a single quadratic Lyapunov function, the globally exponential stability and $H_2/H_{\infty}$ performance problem are discussed. And a sufficient condition for the existence of fuzzy $H_2/H_{\infty}$ controllers is given in terms of linear matrix inequalities(LMIs). The designing fuzzy $H_2/H_{\infty}$ controllers minimize an upper bound on a linear quadratic performance measure. Finally, a design example of fuzzy $H_2/H_{\infty}$ controller for uncertain delayed nonlinear systems with saturating input.