• Journal of the Korea Institute of Information and Communication Engineering
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• v.2 no.1
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• pp.19-26
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• 1998

In this paper, Simulation result was studied by PID controller in series to the estblised neural networks controller. Neural network model is composed of two layers to evaluate tracking performance improvement. The regular dynamics was also studied for the expected error to be minimized by using Widrow-Hoff delta rule. As a result of the study, We identified that tracking performance improvement was developed more in case of connecting PID than conventional neural network controller and that tracking plant parameter in 251 sample was approached rapidly in case of time varying.

• Journal of Power Electronics
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• v.18 no.1
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• pp.147-159
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• 2018

In this paper, the voltage tracking control of a conventional DC-DC boost converter affected by unknown, time-varying circuit parameter perturbations is investigated. Based on the fundamental property of incremental passivity, a passivity based control law is designed. Then, to obtain a better disturbance rejection property, two generalized proportional integral (GPI) observers are employed to estimate the time-varying uncertainties in the output voltage and inductor current channels, and the estimated values are applied as feedforward compensation. Moreover, the global trajectory tracking performance of a system with disturbances is ensured under the composite controller. Finally, simulation and experiment studies are provided to demonstrate the feasibility and effectiveness of the proposed method. The results show that the proposed controller delivers a promising disturbance rejection capability as well as a good nominal tracking performance.

• Proceedings of the KIEE Conference
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• 1996.07b
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• pp.1037-1041
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• 1996

Input-output linearization technique in nonlinear control does not guarantee the robustness in the presence of parameter uncertainty or unmodeled dynamics, etc. However, it has been used as an important preliminary step in achieving additional control objectives, for instance, robustness to parameter uncertainty and disturbance attenuation. An indirect adaptive control scheme based on input-output linearization is proposed in this paper. The scheme consists of a Hopfield network for process parameter identification and an adaptive sliding mode controller based on input-output linearization, which steers the system response into a desired configuration. A numerical example is presented for the trajectory tracking of uncertain nonlinear dynamic systems with slowly time-varying parameters.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2002.05a
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• pp.175-178
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• 2002

The proposed immune algorithm has an uncomplicated structure and memory-cell mechanism as the optimization algorithm which imitates the principle of humoral immune response, and has been used as methods to solve parameter optimization problems. Up to now, the applications of immune algorithm have been optimization problems with non-varying system parameters. Therefore, the effect of memory-cell mechanism, which is a merit of immune algorithm, is without. this paper proposes the immune algorithm using a memory-cell mechanism which can be the application of system with nonlinear varying parameters. To verified performance of the proposed immune algorithm, the speed control of nonlinear DC motor are performed. Computer simulation studies show that the proposed immune algorithm has a fast convergence speed and a good control performances under the varying system parameters.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.53 no.11
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• pp.741-746
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• 2004

When investigating a control problem for network based control systems, the main issue is network-induced delay. This delay can degrade the performance of control systems designed without considering the delay and even destabilize the system. In this paper, we consider the stabilization of network based control systems, where there is bounded time-varying delay. This delay is treated like parameter variation of a discrete time system. The state feedback controller design is formulated as linear matrix inequality. Finally, we show that the stability of control systems designed with considering the delay is superior to that is not so.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.1
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• pp.13-18
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• 2005

This paper considers a design problem of the repetitive control system for linear systems with time-varying norm bounded uncertainties. Using the Lyapunov functional for time-delay systems, a sufficient condition ensuring robust stability of the repetitive control system is derived in terms of an algebraic Riccati inequality (ARI) or a linear matrix inequality (LMI). Based on the derived condition, we show that the repetitive controller design problem can be reformulated as an optimization problem with an LMI constraint on the free parameter.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.51 no.8
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• pp.344-351
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• 2002

The proposed immune algorithm has an uncomplicated structure and memory-cell mechanism as the optimization algorithm which imitates the principle of humoral immune response. We use the proposed algorithm to solve parameter optimization problems. Up to now, the applications of immune algorithm have been optimization problems with non-varying system parameters. Therefore the usefulness of memory-cell mechanism in immune algorithm is without. This paper proposes the immune algorithm using a memory-cell mechanism which can be the application of system with nonlinear varying parameters. To verified performance of the proposed immune algorithm, the speed control of nonlinear DC motor are performed. The results of Computer simulations represent that the proposed immune algorithm shows a fast convergence speed and a good control performances under the varying system parameters.

• Nuclear Engineering and Technology
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• v.27 no.3
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• pp.336-343
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• 1995

The Self Tuning Regulator(STR) method which is an approach of adaptive control theory, is ap-plied to design the fully automatic power controller of the nonlinear reactor model. The adaptive control represent a proper approach to design the suboptimal controller for nonlinear, time-varying stochastic systems. The control system is based on a third­order linear model with unknown, time-varying parameters. The updating of the parameter estimates is achieved by the recursive extended least square method with a variable forgetting factor. Based on the estimated parameters, the output (average coolant temperature) is predicted one-step ahead. And then, a weighted one-step ahead controller is designed so that the difference between the output and the desired output is minimized and the variation of the control rod position is small. Also, an integral action is added in order to remove the steady­state error. A nonlinear M plant model was used to simulate the proposed controller of reactor power which covers a wide operating range. From the simulation result, the performances of this controller for ramp input (increase or decrease) are proved to be successful. However, for step input this controller leaves something to be desired.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2006.11a
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• pp.925-933
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• 2006

Using the physics-based model for the vibration isolation system, the model uncertainties are described. With the model including parameter perturbations, the robust controller to meet the robust performance and stability is designed through $\mu$-synthesis by DK-iteration. The order of controller is reduced by virtue of Hankel norm approximation technique to allow the efficient implementation in the real-time experimental environment without any performance degradation. The performance of the reduced $\mu$-controller is accessed in comparison with the original one. The experiments validate the superiority of the proposed control scheme against the model uncertainties and its applicability with varying payload.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.16 no.12 s.117
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• pp.1262-1271
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• 2006

Using the physics-based model for the vibration isolation system, the model uncertainties are described. With the model including parameter perturbations, the robust controller to meet the robust performance and stability is designed through $\mu$-synthesis by DK-iteration. The order of controller is reduced by virtue of Hankel norm approximation technique to allow the efficient implementation in the real-time experimental environment without any performance degradation. The performance of the reduced $\mu$-controller is accessed in comparison with the original one. The experiments validate the superiority of the proposed control scheme against the model uncertainties and its applicability with varying payload.