• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.2949-2952
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• 2000

A new neural networks and learning algorithm are proposed in order to measure nonlinear heights of complexed road environments in realtime without pre-information. This new neural networks is Error Self Recurrent Neural Networks(ESRN), The structure of it is similar to recurrent neural networks: a delayed output as the input and a delayed error between the output of plant and neural networks as a bias input. In addition, we compute the desired value of hidden layer by an optimal method instead of transfering desired values by back-propagation and each weights are updated by RLS(Recursive Least Square). Consequently. this neural networks are not sensitive to initial weights and a learning rate, and have a faster convergence rate than conventional neural networks. We can estimate nonlinear models in realtime by ESRN and learning algorithm and control nonlinear models. To show the performance of this one. we control 7 degree of freedom full car model with several control method. From this simulation. this estimation and controller were proved to be effective to the measurements of nonlinear road environment systems.

• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.6
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• pp.779-786
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• 2009

This paper deals with $H_{\infty}$ fuzzy control problem of discrete-time nonlinear Markovian jump systems with time delay. The Takgi 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 Markovian jump fuzzy system with time delay. Stochastic Lyapunov function is dependent on the operation modes of the system. A sufficient condition for the existence of fuzzy $H_{\infty}$ controller are given in terms of matrix inequalities. Also numerical example is presented to illustrate the efficient of the proposed design methods.

• 제어로봇시스템학회:학술대회논문집
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• 1986.10a
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• pp.571-575
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• 1986

The squirrel-cage induction motor can be characterized as a nonlinear and multi-input, multi-output system, and has the unmeasurable states which are the rotor currents. In this paper, the time-delayed output feedback method is applied to the speed control of induction motor driven by the current-controlled PWM inverter and its performance is investigated by using the computer simulation.

• Journal of Institute of Control, Robotics and Systems
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• v.4 no.1
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• pp.76-81
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• 1998

This paper presents an on-line scheme for parameter estimation of continuous-time systems, based on the model adjustment technique and the genetic algorithm technique. To deal with the initialisation and unmeasurable signal problems in on-line parameter estimation of continuous-time systems, a discrete-time model is obtained for the linear differential equation model and approximations of unmeasurable states with the observable output and its time-delayed values are obtained for the nonlinear state space model. Noisy observations may affect these approximation processes and degrade the estimation performance. A digital prefilter is therefore incorporated to avoid direct approximations of system derivatives from possible noisy observations. The parameters of both the model and the designed filter are adjusted on-line by a genetic algorithm, A set of simulation works for linear and nonlinear systems is carried out to demonstrate the effectiveness of the proposed method.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2005.04a
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• pp.149-152
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• 2005

In this paper, a robust $H\infty$ stabilization problem to a uncertain discrete-time fuzzy systems with time-varying delay via static output feedback is investigated. The Takagi -Sugeno (T-S) fuzzy model is employed to represent an uncertain nonlinear systems with time-varying delayed state. Using a single Lyapunov function, the globally asymptotic stability and disturbance 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.

• Proceedings of the KIEE Conference
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• 2005.07d
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• pp.2723-2725
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• 2005

In this paper, a robust $H{\infty}$ stabilization problem to a uncertain discrete-time nonlinear systems with time-delay via fuzzy static output feedback is investigated. The Takagi-Sugeno (T-S) fuzzy model is employed to represent an uncertain nonlinear systems with time-delayed state. Then parallel distributed compensation technique is used for designing of the robust fuzzy controller. Using a single Lyapunov function, the globally asymptotic stability and disturbance 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 via similarity transform and congruence transform technique.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1486-1491
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• 2005

In this paper, a robust H${\infty}$ stabilization problem to a uncertain fuzzy systems with time-varying delay via static output feedback is investigated. The Takagi-Sugeno (T-S) fuzzy model is employed to represent uncertain nonlinear systems with time-varying delayed state, which is a continuous-time or discrete-time system. Using a single Lyapunov function, the globally asymptotic stability and disturbance 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.

• Proceedings of the KIEE Conference
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• 2004.11c
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• pp.379-381
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• 2004

In this paper, a robust $H_{\infty}$ stabilization problem to a uncertain fuzzy systems with time-varying delay via static output feedback is investigated. The Takagi-Sugeno (T-S) fuzzy model is employed to represent an uncertain nonlinear systems with time-varying delayed state. Using a single Lyapunov function, the globally asymptotic stability and disturbance 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.

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.3
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• pp.324-329
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• 2005

In this paper, a robust $H\infty$ stabilization problem to a uncertain discrete-time nonlinear systems with time-delay via fuzzy static output feedback is investigated. The Takagj-Sugeno (T-S) fuzzy model is employed to represent an uncertain nonlinear system with time-delayed state. Then, the parallel distributed compensation technique is used for designing of the robust fuzzy controller. Using a single Lyapunov function, the globally asymptotic stability and disturbance 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 via similarity transform and congruence transform technique. We have shown the effectiveness and feasibility of the proposed method through the simulation.

• 전기의세계
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• v.49 no.9
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• pp.17-24
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• 2000

This paper presents sufficient conditions7 for monotonicity of the saddle point value for receding-horizon H$\infty$ control(RHHC). The resulting monotonicity is used to prove the stability of the closed-loop. Under these sufficient conditions the well-known terminal equality condition is handled as a special case and the condition on the state weighting matrix is weakened so as to include even the zero matrix. The whole procedure is much simpler than the previous results and thus is expected to be easily extended for constrained delayed and/or nonlinear systems with the RHHC.