• Proceedings of the IEEK Conference
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• 2009.05a
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• pp.390-392
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• 2009

This paper is concerned with the stabilization problem of nonlinear networked control systems with time-delay via Takagi-Sugeno(T-S) fuzzy control approach. The T-S fuzzy models are employed to represent nonlinear systems with Markovian jump parameters and time-delay. The purpose of this paper is to design a fuzzy controller such that the closed-loop Markovian jump fuzzy system is stochastically stable. Based on a stocastic Lyapunov function, stabilization sufficient conditions using a mode-independent fuzzy controller are derived for the Markovian jump fuzzy system in terms of Linear Matrix Inequalities(LMIs). Finally, a simulation example is presented to illustrate the effectiveness of the proposed method.

• Proceedings of the IEEK Conference
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• 2009.05a
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• pp.329-331
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• 2009

This paper is concerned with the stabilization problem of nonlinear networked control systems with time-delay via Takagi-Sugeno(T-S) fuzzy control approach. The T-S fuzzy models are employed to represent nonlinear systems with Markovian jump parameters and time-delay. The purpose of this paper is to design a fuzzy controller such that the closed-loop Markovian jump fuzzy system is stochastically stable. Based on a stocastic Lyapunov function, stabilization sufficient conditions using a mode-independent fuzzy controller are derived for the Markovian jump fuzzy system in terms of Linear Matrix Inequalities(LMIs). Finally, a simulation example is presented to illustrate the effectiveness of the proposed method.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.1
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• pp.159-164
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• 2017

In this paper, we propose a method of designing the sampled-data tracking controller for nonlinear systems expressed by the Takagi-Sugeno (T-S) fuzzy model. A sufficient condition that asymptotically stabilizes the state error between the linear reference model and the T-S fuzzy model is derived in terms of linear matrix inequalities. To this end, error dynamics are constructed, and the exact discretization method and the Lyapunov stability theory are employed in this paper. Finally, we validate the proposed method through the simulation example.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.9
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• pp.679-685
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• 2016

This paper addresses an observer-based output-feedback sampled-data controller design problem for nonlinear systems in Takagi-Sugeno (T-S) form including singular perturbations. The design condition is represented in terms of linear matrix inequalities. The separation principle is also investigated.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1996.10a
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• pp.310-312
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• 1996

In this paper, we propose a design method for nonlinear SISO system using Takagi-Sugeno fuzzy model and Genetic Algorithm. Our method can reduce the number of design parameters and has advantage of small search space of Genetic Algorithm. The proposed nonlinear controller, which can be implemented by fuzzy controller and simple nonlinear controller, cancels the original nonlinear dynamics and gives the optimal nonlinear dynamics. We illustrated the performance of the proposed controller by simple simulation example.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1997.11a
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• pp.77-80
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• 1997

In this paper, we propose a new fitnesness function of GA for slowly time-varying plant. Previous Takgi-Sugeno model based controller is used as basic control scheme and Controller parameters are tuned by GA with the proposed fitness function includes the information of model parameter variation and has better performance robustness than the previous ones. We illustrate the effectiveness of the proposed fitness function by simple simulation example.

• 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 the Korean Institute of Intelligent Systems
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• v.19 no.1
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• pp.40-47
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• 2009

Recently, dynamic proxy caching has been proposed on the distributed environment so that media objects by user's requests can be served directly from the proxy without contacting the server. However, it makes caching challenging due to multimedia large sizes, low latency and continuous streaming demands of media objects. To solve the problems caused by streaming demands of media objects, this paper has been proposed the grouping scheme with fuzzy filtering based on partition and mapping. For partition and mapping, this paper divides media block segments into fixed partition reference block(R$_f$P) and variable partition reference block(R$_v$P). For semantic relationship, it makes fuzzy relationship to performs according to the fixed partition temporal synchronization(T$_f$) and variable partition temporal synchronization(T$_v$). Simulation results show that the proposed scheme makes streaming service efficiently with a high average request response time rate and cache hit rate and with a low delayed startup ratio compared with other schemes.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.44 no.12
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• pp.1043-1053
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• 2016

In this paper, the application of Parallel Distributed Compensation (PDC) controller for fixed pitch rotary wing system was studied. For nonlinear modeling, T-S fuzzy model was utilized to advance system control including the tilt type UAV. PDC controller was designed through the Linear Matrix Inequality (LMI). Experiments for determining the applicability and feasibility of PDC were performed using the 1 axis attitude control equipment and simulation. To verify the performance and characteristics of the controller, Mathworks Co. Simulink was used. After then, the PDC controller performance was verified and the results with developed controller using a 1 axis attitude control equipment were compared. Verification of the feasibility of PDC controller for the fixed pitch rotary wing system and identification of the overall performance and improvement analysis was conducted based on the experimental results.

• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.1
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• pp.58-63
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• 2014

Most of light duty AGVs(AGCs) using tape of magnetic for the guide path have digital guidance magnetic sensor. Digital guidance magnetic sensor using magnet-tape is on/off type and has positioning error of magnet-tape as 10~50 mm. AGC using this sensor doesn't induce accurate position of magnet-line which is magnet-tape because of magnetic field which motor in AGC creates, outer magnetic field, earth's magnetic field, etc. AGC when driving wobbles due to this error and this error can cause path deviation. In this paper, we propose fuzzy inference system for improvement of bipolar analog magnetic guidance sensor performance. Fuzzy is suitable in term of fault tolerance, uncertainty tolerance, real-time operation, and Nonlinearity as compared with other algorithms. In previous research, we produced bipolar magnetic guidance sensor and we set the threshold in order to calculate digital values of magnet position. Fuzzy inference system is designed using outputs of Analog hall sensors. Magnet position calculated by digital method is improved by outputs of this system. In result, proposed method was verified by improving performance of magnetic guidance sensor.