• Proceedings of the KIEE Conference
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• 1992.07a
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• pp.276-278
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• 1992

This paper presents a method of hierachical optimal control for time invariant large scale systems via Single Term Walsh Series. It is well known that the optimal control of a large scale system with quadratic performance criteria often involves the determination of time varying feedback gain matrix by solving the matrix Riccati differential equation, which is usually quite difficult. Therefore, in order to solve the problem, this paper is introduced to Single Term Walsh Series. The advantages of proposed method are simple and attractive for the control of large scale system in computation.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.13-18
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• 2003

This paper proposes a design method of PID controllers in the framework of a constrained optimization problem. Owing to the popularity for the controller's simplicity and robustness, a great deal of literature concerning PID control design has been published, which can be classified into frequency-based and time-based approaches. However, both approaches have to be considered together for a designed PID control to work well with a guaranteed closed-loop stability. For this purpose, a penalty function is formulated to satisfy both frequency- and time-domain specifications, and is minimized by a recet nonlinear optimization algorithm to attain optimal PID control gains. The proposed method is compared with Wang's and Ho's methods on a suite of example systems. Simulation results show that the PID control tuned by the proposed method improves time-domain performance without deteriorating closed-loop stability.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.4 no.1
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• pp.70-78
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• 2004

This paper proposes non-linear control method using immune algorithm based fuzzy logic. Nonlinear dynamic system exist widely in many types of systems such as chemical processes, biomedical processes, and the main steam temperature control system of the thermal power plant. Up to the present time, PID Controllers have been used to operate these systems. However, it is very difficult to achieve an optimal PID gain with no experience, because gain of the PID controller has to be manually tuned by trial and error. An inverted pendulum control problem is selected to illustrate the efficiency of the proposed method and defines relationship state variables $\chi$, $\chi$, $\theta$, $\theta$ using immune fuzzy.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.1 no.1
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• pp.95-103
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• 2001

The purpose of Introducing a combined cycle with gas turbine in power plants is to reduce losses of energy, by effectively using exhaust gases from the gas turbine to produce additional electricity or process. The efficiency of a combined power plant with the gas turbine increases, exceeding 50%, while the efficiency of traditional steam turbine plants is approximately 35% to 40%. Up to the present time, the PID controller has been used to operate this system. However, it is very difficult to achieve an optimal PID gain without any experience, since the gain of the PID controller has to be manually tuned by trial and error procedures. This paper focuses on the neural network tuning of the 2-DOF PID controller with a combined 2-DOF parameter (NN-Tuning 2-DOF PID controller), for optimal control of the Gun-san gas turbine generating plant in Seoul, Korea. In order to attain optimal control, transfer function and operating data from start-up, running, and stop procedures of the Gun-san gas turbine have been acquired and a designed controller has been applied to this system. The results of the NN-Tuning 2-DOF PID are compared with the PID controller and the conventional 2-DOF PID controller tuned by the Ziegler-Nichols method through experimentation. The experimental results of the NN-Tuning 2-DOF PID controller represent a more satisfactory response than those of the previously-mentioned two controllers.

• Journal of the Korean Institute of Navigation
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• v.4 no.1
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• pp.31-50
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• 1980

It does not seem necessarily practicable to keep the system always in optimal condition, athough the control system of the follow-up mechanism on the most marine gyro compasses is to be adjusted by the operator through the gain adjustment. Sometimes a sustained oscillation or an incorrect gyro reading occurs to the system. For such a system any systematical research or theoretical basis of the guide for the optimal gain adjustment has not been reported yet. As a basic investigation of the theoretical system analysis to solve the problems concerned, the author attempts in this paper to express the system in a mathematical model deduced from the results of the theoretical approach and the experimental observation of each element contained in the follow-up mechanism of Hokshin D-1 gyro compass, and to constitute an over-all closed loop transfer function. This funciton being reverted to a fourth orderlinear differential equation, the first order simultaneous differential equations are obtained by means of the state-variables. The latter equations are solved by the Runge-Kutta method with digital computer. By comparing the characteristic of the simulated over-all output with that of the experimental result, it is shown that both outputs are nearly consistent with each other. It is also expected that the system representation proposed by this paper is valid and will be a prospective means in a further study on the design and optimal adjustment of the system.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.525-530
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• 2003

This paper focuses on design of nonlinear power plant controller using immune based multiobjective fuzzy approach. The thermal power plant is typically regulated by the fuel flow rate, the spray flow rate, and the gas recirculation flow rate. However, Strictly maintaining the steam temperature can be difficult due to heating value variation to the fuel source, time delay changes in the main steam temperature. the change of the dynamic characteristics in the steam-turbine system. Up to the present time, PID Controller has been used to operate this system. However, it is very difficult to achieve an optimal PID gain with no experience, since the gain of the PID controller has to be manually tuned by trial and error. These parameters tuned by multiobjective based on immune network algorithms could be used for the tuning of nonlinear power plant.

• Proceedings of the KIEE Conference
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• 1998.07f
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• pp.2012-2014
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• 1998

The conventional PI controller has been widely used in industrial applications. If a PI control gain is selected suitable, the PI controller shows very good control performance. But it is very difficult to find the optimal PI control gain. Therefore, in this paper, the 4-rule based fuzzy logic modifier of the conventional PI controller are presented. The fuzzy logic modifier which exhibits a stabilizing effects on the closed-loop system, has good robustness regarding the improperly tuned PI controller. The simulation are performed to verify the capability of proposed control method on vector controlled induction motor drive system.

• ETRI Journal
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• v.25 no.6
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• pp.437-444
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• 2003

We derive a new joint power and rate control rule with which we can minimize the mean transmission delay in CDMA networks for a given mean transmission power. We show that it is optimal to respectively control the power inverse-linearly and the rate linearly to the square root of channel gain while maintaining the signal-to-interference ratio at a constant. We also show that the proposed joint power/rate control rule achieves excellent performance results in terms of the probability of the instantaneous delay being within a target delay against one-dimensional control schemes.

• Proceedings of the KIEE Conference
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• 1998.07b
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• pp.549-551
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• 1998

In this paper, we design the optimal satellite-tracking antenna $H_{\infty}$ control system using genetic algorithm(GA). To do this, we give gain and dynamics parameters to the weighting functions and apply GA with reference model to the optimal determination of weighting functions and design parameter ${\gamma}$ that are given by Glover-Doyle algorithm which can design $H_{\infty}$ controller in the state space. These weighting functions and design parameter ${\gamma}$ are simultaneously optimized in tile search domain guaranteeing the robust stability of closed-loop system. The effectiveness of this satellite-tracking antenna $H_{\infty}$ control system is verified by computer simulation.

• Proceedings of the KIEE Conference
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• 1997.07b
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• pp.587-589
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• 1997

In this paper we design the model following ${\mu}$-synthesis control system for optimal fuel-injection of diesel engine using genetic algorithms. To do this, we give gain and dynamics parameters to the weighting functions and apply genetic algorithms with reference model to the optimal determination of weighting functions that are given by D-K iteration method which can design ${\mu}$-synthesis controller in the state space. These weighting functions are optimized simultaneously in the search domain selected adequately. The effectiveness of this ${\mu}$-synthesis control system for fuel-injection is verified by computer simulation.