• Journal of the Korean Institute of Telematics and Electronics C
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• v.36C no.7
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• pp.56-64
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• 1999

In this paper, a novel approach to the stability analysis of the continuous affine Takagi-Sugeno fuzzy control systems is proposed. The suggested analysis method is easily implemented by the recently spotlighted convex optimization techniques called Linear Matrix Inequalities (LMI). First, it derives the stability condition under which the affine Takagi-Sugeno fuzzy system is stable in the large. Next, the derived condition is recast in the formulation of LMI and numerically addressed. Finally, the applicability of the suggested methodology is highlighted via computer simulations.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.9
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• pp.1364-1372
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• 2017

In this paper, a problem of event-triggered model predictive control is investigated for continuous-time Takagi-Sugeno (T-S) fuzzy systems with input quantization. To efficiently utilize network resources, event-trigger is employed, which transmits limited signals satisfying the condition that the measurement of errors is over the ratio of a certain level. Considering sampling and quantization, continuous Takagi-Sugeno (T-S) fuzzy systems are regarded as a sector bounded continuous-time T-S fuzzy systems with input delay. Then, a model predictive controller (MPC) based on parallel distributed compensation (PDC) is designed to optimally stabilize the closed loop systems. The proposed MPC optimize the objective function over infinite horizon, which can be easily calculated and implemented solving linear matrix inequalities (LMIs) for every event-triggered time. The validity and effectiveness are shown that the event triggered MPC can stabilize well the systems with even smaller average sampling rate and limited actuator signal guaranteeing optimal performances through the numerical example.

• Journal of Electrical Engineering and Technology
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• v.11 no.1
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• pp.200-214
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• 2016

This paper investigates the problem of stability analysis and robust H_∞ controller for time-delayed systems with parameter uncertainties and stochastic disturbances. It is assumed parameter uncertainties are norm bounded and mean and variance for disturbances of them are known. Firstly, by constructing a newly augmented Lyapunov-Krasovskii functional, a stability criterion for nominal systems with time-varying delays is derived in terms of linear matrix inequalities (LMIs). Secondly, based on the result of stability analysis, a new controller design method is proposed for the nominal form of the systems. Finally, the proposed method is extended to the problem of robust H_∞ controller design for a time-delayed system with parameter uncertainties and stochastic disturbances. To show the validity and effectiveness of the presented criteria, three examples are included.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.36 no.11
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• pp.1311-1318
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• 2012

Vehicle systems are frequently exposed to parameter uncertainties such as vehicle speed and height of center of gravity. If a controller is designed to be robust against these parameter uncertainties, the rollover prevention capability can be considerably enhanced. In this study, robust controllers $H_2$ and $H_{\infty}$ are designed by using LMI for vehicle rollover prevention control in the discrete time domain. Some simulations using CarSim, a reliable simulation tool, are performed to validate the proposed controllers.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.37 no.6
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• pp.15-24
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• 2000

This paper presents an output feedback robust H$\infty$ control problem for a class of uncertain nonlinear systems, which can be represented by an fuzzy dynamic model. The nonlinear system is represented by Takagi-Sugeno fuzzy model, and the control design is carried out on the basis of the fuzzy model. Using a single quadratic Lyapunov function, the globally exponential stability and disturance attenuation of the closed-loop fuzzy control system are discussed. Sufficient conditions for the existence of robust H$\infty$ controllers are given in terms of linear matrix inequalities(LMIs). Constructive algorithm for design of robust H$\infty$ controller is also developed. The resulting controller is nonlinear and automatically tuned based on fuzzy operation.

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.1
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• pp.94-99
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• 2012

This paper discusses a decentralized sampled-data control problem for large-scale nonlinear systems. The system is represented in Takagi-Sugeno's form. Next, we design a decentralized analog controller based on the overlapping decomposition technique. The final step is to apply the intelligent digital redesign scheme for converting the analog controller into the sampled-data one. Design condition is represented in terms of linear matrix inequalities. A simulation result is provided for the effectiveness of the proposed design method.

• Journal of the Korean Institute of Intelligent Systems
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• v.23 no.1
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• pp.65-71
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• 2013

In this paper, we address fault detection observer design problem of T-S fuzzy systems with sensor fault. To detect fault, T-S fuzzy model-based observer is used. By introducing $\mathfrak{H}$_ performance index, an observer is designed as sensitive to fault as possible. The fault is then detected by a fault decision logic. The design conditions are derived in terms of linear matrix inequalities. An illustrative example is provided to verify the effectiveness of the proposed fault detection technique.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.38 no.4
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• pp.1-10
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• 2001

In this paper, we propose the stability analysis and design methodology for the discrete-time affine Type III fuzzy system via the convex optimization technique. First, the stability condition is derived under which the discrete-time affine Type III fuzzy system is quadratically stable in the large. Next, the derived condition is reformulated into the convex optimization problem called Linear Matrix Inequalities (LMI) and numerically addressed. Finally, the effectiveness and the feasibility of the proposed analysis and design methodology is highlighted via an example and its computer simulation result.

• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.1
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• pp.15-20
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• 2010

In this paper, we discuss a decentralized observer design problem for the fault detection in the large-scale continuous-time T-S (Takagi-Sugeno) fuzzy system. Since the fault detection residual is desired to be as sensitive as possible, on the fault, we use $\mathfrak{H}_-$ index performance criterion. Sufficient conditions for the existence of such a observer is presented in terms of linear matrix inequalities. Simulation results show the effectiveness of the proposed method.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.05a
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• pp.321-324
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• 2003

This paper discusses a robust stochastic stabilization of uncertain Takagi-Sugeno (T-S) fuzzy system with Markovian input delay. The finite Markovian process is adopted to model the input delay of the overall control system. It is assumed that the zero and hold devices are used for control input. The continuous-time T-S fuzzy system with the Markovian input delay is discretized for easy handling delay, accordingly, the discretixzd T-S fuzzy system is represented by a uncertain discrete-time T-S fuzy system with jumping parameters. The robust stochastic stabilizibility of the uncertain jump T-S fuzzy system is derived and formulated in terms of linear matrix inequalities (LMIs).