• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.198-198
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• 2000

In this paper, the linearization method of nonlinear systems via fuzzy controllers which can be the basic research for designing a systematic fuzzy controllers with singleton consequents is proposed. We regard a closed loop system as a canonical form and propose a methodology for linearization of nonlinear system which adjust the input at vertex using zero condition and affinity condition. Through some examples, we show the validity of the proposed method and it can be extended to the design problem of fuzzy controller.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10a
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• pp.34-39
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• 1991

In this paper, we provide a treatment of the $H^{\infty}$-mixed sensitivity optimization approach to feedback system design. With compromising between the effect of a disturbance at the plant output and the effect of plant perturbations, we propose an algorithm to design robust controller. A $H^{\infty}$-optimization problem is to be equivalent to a Hankel-approximation, this enables the problem to be solved using state-space methods based on balanced realizations.s.

• Journal of Electrical Engineering and information Science
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• v.3 no.2
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• pp.193-201
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• 1998

In this paper, the standard Dole, Glover, Khargoneker, and Francis (abbr. : DGKF 1989) H\ulcorner controller (H\ulcornerC) is extended to the nonlinear feedback linearization-H\ulcorner/sliding mode controller (NFL-H\ulcorner/SMC), to tackle the problem of the unmeasurable state variables as in the conventional SMC, to obtain smooth control as the linearized controller in a linear system, and to improve the time-domain performance under a worst scenario. The proposed controller is obtained by combining the H\ulcorner estimator with the nonlinear feedback linearization-sliding mode controller (NFL-SMC) and it does not need to measure all the state variables as in the traditional SMC. The proposed controller is applied as a nonlinear power system stabilizer (PSS) for the improvement of the power system damping characteristics of an single machine infinite bus system (SMIBS) connected through a double circuit line. The effectiveness of the proposed controller is verified by nonlinear time-domain simulation in case of a 3-cycle line-to-ground fault and in case of the parameter variations for the AVR gain K\ulcorner and for the inertia moment M.

• Nuclear Engineering and Technology
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• v.38 no.1
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• pp.81-92
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• 2006

In this study, the core dynamics of a PWR reactor is identified online by a recursive least-squares method. Based on the identified reactor model consisting of the control rod position and the core average coolant temperature, the future average coolant temperature is predicted. A model predictive control method is applied to designing an automatic controller for the thermal power control of PWR reactors. The basic concept of the model predictive control is to solve an optimization problem for a finite future at current time and to implement as the current control input only the first optimal control input among the solutions of the finite time steps. At the next time step, this procedure for solving the optimization problem is repeated. The objectives of the proposed model predictive controller are to minimize both the difference between the predicted core coolant temperature and the desired temperature, as well as minimizing the variation of the control rod positions. In addition, the objectives are subject to the maximum and minimum control rod positions as well as the maximum control rod speed. Therefore, a genetic algorithm that is appropriate for the accomplishment of multiple objectives is utilized in order to optimize the model predictive controller. A three-dimensional nuclear reactor analysis code, MASTER that was developed by the Korea Atomic Energy Research Institute (KAERI) , is used to verify the proposed controller for a nuclear reactor. From the results of a numerical simulation that was carried out in order to verify the performance of the proposed controller with a $5\%/min$ ramp increase or decrease of a desired load and a $10\%$ step increase or decrease (which were design requirements), it was found that the nuclear power level controlled by the proposed controller could track the desired power level very well.

• Proceedings of the KIEE Conference
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• 2005.10b
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• pp.104-106
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• 2005

In this work, a PWR reactor core dynamics is identified online by a recursive least squares method. Based on this identified reactor model consisting of the control rod position and the core average coolant temperature, the future average coolant temperature is predicted. A model predictive control method is applied to design an automatic controller for thermal power control in PWRs. The basic concept of the model predictive control is to solve an optimization problem for a finite future at current time and to implement as the current control input only the first optimal control input among the solutions of the finite time steps. At the next time step, the procedure to solve the optimization problem is then repeated. The objectives of the proposed model predictive controller are to minimize both the difference between the predicted core coolant temperature and the desired one, and the variation of the control rod positions. Also, the objectives are subject to maximum and minimum control rod positions and maximum control rod speed. Therefore, the genetic algorithm that is appropriate to accomplish multiple objectives is used to optimize the model predictive controller. A 3-dimensional nuclear reactor analysis code, MASTER that was developed by Korea Atomic Energy Research Institute (KAERI), is used to verify the proposed controller for a nuclear reactor. From results of numerical simulation to check the performance of the proposed controller at the 5%/min ramp increase or decrease of a desired load and its 10% step increase or decrease which are design requirements, it was found that the nuclear power level controlled by the proposed controller could track the desired power level very well.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.7
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• pp.619-624
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• 2011

This paper presents a controller design method for a robust control problem with multiple constraints using genetic algorithms and LMI design method. A robust $H_{\infty}$ constraint with loop shaping and pole placement is used to address disturbance attenuation with error limits and desired transient specifications, in spite of the plant uncertainties and disturbances. In addition, a loop gain constraint is considered so as not to enlarge the loop gain unnecessarily. The robust $H_{\infty}$ constraint and pole placement constraint can be expressed in terms of two matrix inequalities and the loop gain constraint can be considered as an objective function so that genetic algorithms can be applied. Accordingly, a robust controller can be obtained by integrating genetic algorithms with LMI approach. The proposed controller design method is applied to a track-following system of an optical disk drive and is evaluated through simulation results.

• Journal of Ocean Engineering and Technology
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• v.26 no.3
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• pp.6-12
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• 2012

In this paper, addressed is the control problem of generating a formation for a group of unmanned surface and underwater vehicles. The formation control scheme proposed in this work is based on a fusion of theleader-follower and virtual reference approaches. This scheme gives a formation constraint representation that is independent of the number of vehicles in the formation and the resulting control algorithm is scalable. One of the most important features in controller design is the ability of the controller to globally and exponentially stabilize the formation errors defined by the formation constraints. The proposed controller is based on feedback linearization, and the formation errors are shown to be globally and exponentially stable in the sense of Lyapunov.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.54 no.1
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• pp.48-55
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• 2005

Mobility of an indoor wheeled robot is affected by adhesion force that is related to various floor conditions. When the adhesion force between driving wheels and floor decreases suddenly, the robot begins slip. In order to overcome this slip problem, optimal slip velocity must be decided for stable movement of wheeled robot. First of all, this paper shows that conventional PI control can not be applied to a wheeled robot of the light weight. Secondly, proposed fuzzy logic is applied to the Takagi-Sugeno model for the configuration of fuzzy sets. For the design of Takagi-Sugeno model and fuzzy rule, proposed algorithm uses FCM(Fuzzy c-mean clustering method) algorithm. In additionally, this algorithm adjusts the driving torque for restraining re-slip. The proposed fuzzy logic controller(FLC) is pretty useful with prevention of the slip phenomena for the controller performance in the re-adhesion control strategy, These procedures are implemented using a Pioneer 2-DXE wheeled robot parameter.

• 전기의세계
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• v.25 no.5
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• pp.70-74
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• 1976

In this paper, the problem of controlling deterministic contimuous linear system with a slightly modified quadratic performance criteria is studied. When the number of out put variables is much lesser then that of state variables, either the controller becomes complex or the performance measure becomes much higher with only output feedback. So the design philosphy treated in this paper lies in finding a compromising point between the controller complexity and the performance measure. thd controller is composed of stasic plus dynamic compensator with order equal to the mtmber of output variables. Several unknowns are unknown parameters are bundled into one, and using Pontryagin's minimum principle, conditions and formula for optimum control are induced which are different from that of Kalman optimal regulator.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2002.05a
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• pp.203-206
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• 2002

This paper describes fuzzy control methodologies of the steam generator which have nonlinear characteristics in the nuclear power plant. Actually, the steam generator part of the power generator has a problem to control water level because it has complex components and nonlinear characteristics. In order to control nonlinear terms of the model, Takagj-Sugeno (75) fuzzy system is used to design a controller. In designing procedure, intelligent digital redesign method is used to control the nonlinear system. This digital controller keeps the performance of the analog controller. Simulation examples are included for ensuring the proposed control method.