• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.2667-2668
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• 2000

In this paper we consider the TORA system and use sliding observer and backstepping to design a robust controller for tracking problem.

• Proceedings of the IEEK Conference
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• 2000.07b
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• pp.677-680
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• 2000

The technique of reinforcement learning algorithm is extended to solve the multiobjective control problem for uncertain dynamic systems. A multiobjective adaptive critic structure is proposed in order to realize a max-min method in the reinforcement learning process. Also, the proposed reinforcement learning technique is applied to a multiobjective satisfactory fuzzy logic controller design in which fuzzy logic subcontrollers are assumed to be derived from human experts. Some simulation results are given in order to show effectiveness of the proposed method.

• Proceedings of the KIEE Conference
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• 1985.07a
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• pp.47-48
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• 1985

This paper is concerned with the problem of designing satisfactory low-order controller starting with a high-order, state space model. The success of a design approach is rooted in the Choice of a model reduction procedure. The powerful new reduction method of a modal approach was already evaluated /1/. Application of the technique to a simulated steam generator is demonstrated for the case of modal control with low-order controllers.

• Proceedings of the KIEE Conference
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• 1996.07b
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• pp.1193-1195
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• 1996

For an automatic steering problem of vehicles, the main task is to keep a reference path with assumption that the displacement from the guideline can be measured by a sensor. In this paper, a sliding mode fuzzy logic controller design method is introduced and it shows highly enhanced performance in comparison with the other results. The method can be relatively simply implemented.

• Proceedings of the KIEE Conference
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• 1996.11a
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• pp.42-45
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• 1996

This paper presents a solution of the $H_{\infty}$ control problem for linear systems with input time delay. $H_{\infty}$ norm bounded condition is obtained as a sufficient condition for linear systems with input time delay. Based upon this sufficient condition, an $H_{\infty}$ controller design method which involves the solutions of linear matrix inequalities via convex optimization is developed.

• Proceedings of the KIEE Conference
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• 2001.07d
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• pp.1973-1975
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• 2001

In this paper, we consider the problem of robust peak-to-peak controller design of linear system. The goal is to design a controller which minimizes the maximum peak value of the measured output subjects to the peak bounded disturbance. The control is obtained by checking the feasibility of the derived matrix inequalities. Finally, we shows the usefulness of our result comparing to $H_{\infty}$ and $H_{2}$ control by an example.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.2
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• pp.228-233
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• 2004

Nowadays, the robot with various and complex functions is required. previous algorithms, however, cannot satisfy the requirement. In order to solve these problems, we introduce the 2-Layer Fuzzy Controller, which has a small number of fuzzy rules corresponding to various inputs and outputs. Also, it controls robustly and effectively an object. The main problem in the fuzzy controller is how to design the fuzzy rule. This paper designs the optimal 2-layer fuzzy controller using the Schema Co-Evolutionary Algorithm. The schema co-evolutionary algorithm can find more rapidly and excellently than simple genetic algorithm does.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.42 no.6
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• pp.9-14
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• 2005

In this paper, we consider the synthesis of non-fragile $H_{\infty}$ state feedback controllers for singular systems and static state feedback controller with multiplicative uncertainty. The sufficient condition of controller existence, the design method of non-fragile $H_{\infty}$ controller, and the measure of non-fragility in controller are presented via LMI(linear matrix inequality) technique. Also, the sufficient condition can be rewritten as LMI form in terms of transformed variables through singular value decomposition, some changes of variables, and Schur complements. Therefore, the obtained non-fragile $H_{\infty}$ controller guarantees the asymptotic stability and disturbance attenuation of the closed loop singular systems within a prescribed degree. Moreover, the controller design method can be extended to the problem of robust and non-fragile $H_{\infty}$ controller design method for singular systems with parameter uncertainties. Finally, a numerical example is given to illustrate the design method.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10b
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• pp.56-60
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• 1992

This paper addresses the problem of designing a neural network based controller for a discrete-time nonlinear dynamical system. Using two multi-layered neural networks we first design an indirect controller the weights of which are updated by the informations obtained from system identification. The weight update is executed by parameter optimization method under Lagrangian formulation. For the nonlinear dynamical system, we define several cost functions and by computer simulations analyze the control performances of them and the effects of penalty-weighting values.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.359-359
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• 2000

Generally, level control in the steam generator of a nuclear power plant is difficulty process control, because the low power operating can lead nonminimum phase characteristics(swell and shrink phenomenon) and flow measurement are unreliable and nonlinear characteristics. This paper presents a framework for solving this problem based on the constrained linear model predictive control and introduces the design of method for the level of the controller in the entire operating power of the steam generator, and compares with conventional PI controller.