• International Journal of Control, Automation, and Systems
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• v.4 no.2
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• pp.172-177
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• 2006

In the networked control system (NCS), the uncertain network-induced delay and nonlinear controlled object are the main problems, because they can degrade the performance of the control system and even destabilize it. In this paper, a class of uncertain and nonlinear networked control systems is discussed and its sufficient condition for the robust asymptotic stability is presented. Further, the maximum network-induced delay that insures the system stability is obtained. The Lyapunov and LMI theorems are employed to investigate the problem. The result of an illustrative example shows that the robust stability analysis is sufficient.

• 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.

• Journal of Institute of Control, Robotics and Systems
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• v.15 no.9
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• pp.929-938
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• 2009

This paper presents a novel control methodology for communication network based nonlinear systems with time delay nature. We construct a nominal nonlinear control law for representing a linear model and a reset control system which is aimed for corrective control strategy to compensate system error due to uncertain time delay through wireless communication network. Next, online neural control approach is proposed for overcoming nonstationary statistical nature in the network topology. Additionally, DBN (Dynamic Bayesian Network) technique is accomplished for modeling of its dynamics in terms of casuality, which is then utilized for estimating prediction of system output. We evaluate superiority and reliability of the proposed control approach through numerical simulation example in which a nonlinear inverted pendulum model is employed as a networked control system.

• 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 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.

• International Journal of Control, Automation, and Systems
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• v.6 no.3
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• pp.444-452
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• 2008

We propose an intelligent predictive control approach for a nonlinear networked control system (NCS) with time-varying delay and random observation. The control is given by the sum of a nominal control and a corrective control. The nominal control is determined analytically using a linearized system model with fixed time delay. The corrective control is generated online by a neural network optimizer. A Markov chain (MC) dynamic Bayesian network (DBN) predicts the dynamics of the stochastic system online to allow predictive control design. We apply our proposed method to a satellite attitude control system and evaluate its control performance through computer simulation.

• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.2
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• pp.174-179
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• 2009

We consider the stabilization problem for a class of networked control systems with neutral type of time delays. The neutral type of time-delays occur in controller-to-actuator and sensor-to-controller. The Takagi-Sugeno (T-S) fuzzy model is employed to represent a nonlinear system with neutral type of time-delays. The stabilization via state-feedback is first addressed, and delay-range-dependent stabilization conditions are proposed in terms of linear matrix inequalities (LMIs). Finally, an application example will be given to show the merits and design a procedure of the proposed approach.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.2
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• pp.139-144
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• 2011

We consider the stabilization problem for a class of networked control systems with random delays in the discrete-time domain. The controller-to-actuator and sensor-to-controller time-delays are modeled as two Markov chains, and the resulting closed-loop systems are Markovian jump nonlinear systems with two modes. The T-S (Takagi-Sugeno) fuzzy model is employed to represent a nonlinear system with Markovian jump parameters. The aim is to design a fuzzy controller such that the closed-loop Markovian jump fuzzy system is stochastically stable. The necessary and sufficient conditions on the existence of stabilizing fuzzy controllers are established in terms of LMIs (Linear Matrix Inequalities). It is shown that fuzzy controller gains are mode-dependent. Finally, a simulation example is presented to illustrate the effectiveness of the proposed design method.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.2
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• pp.151-156
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• 2008

This paper presents the stability analysis and design for a sampled-data fuzzy control system with neutral type of time delay, which is formed by a nonlinear plant and a sampled-data fuzzy controller connected in a closed loop. The sampling activity and neutral type of time delay will complicate the system dynamics and make the stability analysis much more difficult than that for a pure continuous-time fuzzy control system. Based on the fuzzy-model-based control approach, LMI(linear matrix inequality)-based stability conditions are derived to guarantee the nonlinear networked system stability. An application example will be given to show the merits and design a procedure of the proposed approach.