• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1991년도 한국자동제어학술회의논문집(국내학술편); KOEX, Seoul; 22-24 Oct. 1991
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• pp.197-202
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• 1991

Recently, an output feedback variable structure control scheme(OFVSCS) is proposed to remove the assumption of full state availability and to make the application of VSC scheme to the high order systems with unmeasurable state variables possible. In this paper, a design method of an output feedback variable structure control system (IOFVSCS) that guarantees the invariance of the sliding mode against process parameter variation and external disturbance is proposed. The IOFVSCS is composed of two components; dynamic switching surface driven by measured I/0 informations and switching control input generator driven by switching surface information and measured output, where the two components are constructed by adopting unknown vector modelling approach. The invariance condition for the IOFVSCS is proved to be the same as that of the conventional VSCS. Simulation results show that the IOFVSCS can be designed to have robust properties better than that of the conventional VSCS in spite that the IOFVSCS is driven by small amount of measured information.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1992년도 한국자동제어학술회의논문집(국내학술편); KOEX, Seoul; 19-21 Oct. 1992
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• pp.502-506
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• 1992

In this study, we proposed the fuzzy modeling method and designed a model-based logic controller for Activated and Sludge Process(A.S.P.) in sewage treatment. The identification of the structure of fuzzy implications is carreid out by use of fuzzy c-means clustering algorithm. And to identify the parameters of fuzzy implications, we used the complex and the least square method. To tune the premise parameters automatically the complex method is implemented. The model-based fuzzy controller is designed by rules generated from the identified A.S.P. fuzzy model. The feasibility of the proposed approach is evaluated through the identification of the fuzzy model to describe an input-output relation of the A.S.P.. The performance of identified model-based fuzzy controller is evaluated through the computer simulations.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1992년도 한국자동제어학술회의논문집(국내학술편); KOEX, Seoul; 19-21 Oct. 1992
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• pp.736-741
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• 1992

The Stewart platform is one example of a motion simulator which generates 6 DOF motion in space by 6 actuators connected in parallel. The present SISO controllers are designed to track displacement command of each actuator computed from reference 6 DOF motion of platform by Stewart platform inverse kinematics. But this type of control can't cope with external load variation, geometric configuration of motion simulator, and different dynamic behavior of 6 DOF motion. In this paper, a multivariable controller using H- optimal control theory is designed for linerized simulator model with each actuator driving force as control input and platform 6 DOF motion as measured output. Nonlinear simulation result of the H$_{\infty}$ MIMO controller is not satisfied in steady-state characteristics. But the proposed H$_{\infty}$ + PI control scheme shows acceptable performance.e.e.

• 제어로봇시스템학회논문지
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• 제5권7호
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• pp.808-813
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• 1999

A fuzzy learning method to control an unstable and multivariable system is presented in this paper, Because the multivariable system has generally a coupling effect between the inputs and outputs, it is difficult to find its modeling equation or parameters. If the system is unstable, initial condition rules are needed to make it stable because learning is nearly impossible. Therefore, this learning method uses the initial rules and introduces a cost function composed of the actual error and error-rate of each output without the modeling equation. To minimize the cost function, we experimentally got the Jacobian matrix in the operating point of the system. From the Jacobian matrix, we can find the direction of the convergence in the learning, and the optimal control rules are finally acquired when the fuzzy rules are updated by changing the portion of the errors and error rates.

• 제어로봇시스템학회논문지
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• 제7권4호
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• pp.295-303
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• 2001

The demand for steam generators is increasing in industrial systems in which the design strategy should be implemented for safe and efficient operation of steam generators. It is, however, difficult to design a controller by the conventional method because of the nonlinear dynamics of the steam generator and influences by the set value of disturbance. This paper presents an automatic parameter optimization technique for a multivariable fuzzy controller using evolutionary strategy, At first, we use the steady state information such as a steady state gain matrix(SSGM) and a relative gain matrix(RGM). We can obtain much information on the control inputs and the outputs of the boiler-turbine system from the matrices. In order to determine the structure of the controller by using RGM and SSGM, the fuzzy rules are trained by evolutionary strategy. The good performance of the proposed multivariable fuzzy controller is verified through simulations.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 1996년도 추계학술대회 논문집
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• pp.248-254
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• 1996

A disturbance rejection controller using eccentricity filtering and LQ control techniques is proposed to alleviate significantly the effect of roll eccentricity in multivariable cold-rolling processes. Fundamental problems such as process time delay inherent in exit thickness measurement and non-stationary characteristics of roll eccentricity signals can be overcome by the proposed control method. The filtered instantaneous estimate of roll eccentricity may be exploited to improve instantaneous estimate of the exit thickness variation based on roll force and roll gap mearsurements, and a feedforward compensator is augmented as a reference for a gaugemeter thickness estimator. And, LQ feedback controller is combined with eccentricity filter for the attenuation of the exit thickness variation due to the entry thickness variation. The simulation results show that eccentricity components have been significantly eliminated and simultaneously other distrubances also have been attenuated.

• 한국자동차공학회논문집
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• 제2권5호
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• pp.110-120
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• 1994

Due to the increasing demands in comfortable drivability, most motor companies are developing their own unique shift controller to suppress the shift shock induced by gear change. For a typical automatic transmission system, the dynamic constraints of friction clutch was clarified for efficient program development and major factors effecting the shift transient was confirmed by simulation study. The MIMO LQG/LTR controller was designed to control the turbine and corresponding gear speed. By establishing the control strategy recalling transient response during shift the speed controller mentioned above was used as an indirect torque controller. Consequently a new concept for a systematic design method of shift controller applicable to wide-varying systems was suggested which is time efficient and cost efficient saving a lot of experimental study.

• 제어로봇시스템학회논문지
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• 제12권5호
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• pp.505-508
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• 2006

This paper presents a new analytical approach for designing multiloop PI controllers for disturbance rejection in multivariable processes with time delay. The proposed method is based on IMC-PID design approach. To overcome a sluggish load response by dominant pole in the process, the IMC filter is modified to compensate the dominant pole effect. Based on the modified IMC filter, an analytical tuning rule for multiloop PI controller is driven by extending the generalized IMC-PID method for single input/single output (SISO) systems [1] to multi input/multi output (MIMO) systems. Simulation results show that the proposed method gives a satisfactory load performance as well as servo performance in the multiloop system.

• 제어로봇시스템학회논문지
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• 제3권6호
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• pp.582-587
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• 1997

This paper deals with the control problem under nonlinear boiler systems with noise, and input constraints. MCMBPC(Multivariable Constrained Model-Based Predictive Controller) proposed by Wilkinson et al.[10,11] is used and nominal model is modified in this paper in order to applied to nonlinear boiler systems with feed-forward terms. The solution of the cost function optimization constrained on input and/or output variables is achieved using quadratic programming, via singular value decomposition(SVD). The controller designed is shown to satisfy the constraints and to have excellent tracking performance via simulation applied to nonlinear dynamic drum boiler turbine model for 16OMW unit.

• 융합신호처리학회논문지
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• 제4권3호
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• pp.41-48
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• 2003

본 논문은 개선된 카오틱 신경망을 이용한 비선형 시스템의 적응제어에 관한 것이다. 개선된 카오틱 신경망은 기존의 카오틱 신경망을 간략화하며 동적 특성을 강화하기 위하여 제안하였다 또한 새로운 동적 역전파 학습방법을 개발하였다. 제안된 신경회로망은 다변수 시스템의 시스템식별과 신경망 적응제어 시스템에 적용하였다. 제안된 신경망은 비선형 동적시스템에 우수한 적응성을 가지므로 시뮬레이션 결과는 우수한 성능을 보였다.