• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1986년도 한국자동제어학술회의논문집; 한국과학기술대학, 충남; 17-18 Oct. 1986
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• pp.370-372
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• 1986

In this paper we propose a Generalized Minimum Variance Self-tuning Control of the system with an autoregressive noise model. To establish a Generalized Minimum Variance Control, the control input is also included in a cost function and a novel identity is introduced. The effectiveness of this algorithm is demonstrated by the computer simulation.

• International Journal of Control, Automation, and Systems
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• 제4권3호
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• pp.281-292
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• 2006

The design and implementation of Generalized Minimum Variance control laws for nonlinear multivariable systems that can include severe nonlinearities is considered. The quadratic cost index minimised involves dynamically weighted error and nonlinear control signal costing terms. The aim here is to show the controller obtained is simple to design and implement. The features of the control law are explored. The controller obtained includes an internal model of the process and in one form is a nonlinear version of the Smith Predictor.

• 대한전자공학회논문지
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• 제25권4호
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• pp.372-378
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• 1988

The elimination of offsets such as those induced by load disturbance is a principal requirement in the control of industrial processes. In this paper we propose a self-tuning minimum variance control in the two tuypes of k-incremental and integrating form. Since the objective of control design in this paper is a generalized minimum variance control, it can be applied to nonminimum phase system. And we compare the proposed algorithm wiht that of the positional self-tuning control and show that it can also be applied to nonminimum phase system by computer simulation.

• Journal of Advanced Marine Engineering and Technology
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• 제27권3호
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• pp.388-394
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• 2003

Hydraulic system is difficult to obtain a suitable performance due to the nonlinearity load pressure change and system parameter variation. The requirement of control a1gorithm has been complex in order to satisfy the performance. The adaptive control is a control method which is suggested to achieve the control object under the plant characteristics change. In spite of the case that plant characteristics and the degree of variation are difficult to grasp. the adaptive control could keep the characteristics of closed-loop system generally. In this study. a method of combined generalized minimum variance adaptive control (GMVAC) and output error feedback is proposed, in order to solve the problem of non-minimum phase of plant and the vibration and overshoot in initial response. The control performance according to the variation of characteristics of plant is evaluated by changing the supply pressure. The experimental results show the effectiveness of the proposed scheme.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1997년도 한국자동제어학술회의논문집; 한국전력공사 서울연수원; 17-18 Oct. 1997
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• pp.629-632
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• 1997

This paper presents the design method of controller which is combined Genetic Algorithms with the Generalized minimum variance self tuning controller. It is shown that the controllers adapts to changes in the system parameters with time delays and noises. The self tuning effect is achieved through the recursive least square algorithm at the parameter estimation stage and also through the Robbins-Monro algorithm at the stage of optimizing a polynomial parameters. The computer simulation results are presented to illustrate the procedure and to show the performance of the control system.

• 한국정밀공학회지
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• 제21권1호
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• pp.124-132
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• 2004

A hydraulic system is difficult to keep the performance due to non-linearity, load pressure which changes according to working condition and system parameter variation, the requirement of control algorithm has been risen in order to satisfy them. An adaptive control is a control method which is suggested to achieve a control object though plant characteristics change. In spite of the case that plant characteristics and the degree of variation are difficult to grasp, adaptive control can keep the characteristics of closed-loop system regularly. In this study GMVAC(generalized minimum variance adaptive control) combined with output error feedback is proposed in order to solve problems of non-minimum phase, vibration and overshoot in initial response of the plant. The control performance according to the variation of characteristics of the plant is evaluated by changing the supply pressure only.

• 한국정밀공학회지
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• 제16권3호통권96호
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• pp.109-115
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• 1999

This paper presents a stabilization control designed to improve position stabilization performance of a position servo-system(turret) mounted on a manuvering platform(vehicle). In the consideration of the motion of the platform, a dynamic model of the stabilization system is derived and shows the viscous and stick-slip friction torques are the major source of stabilization errors. An extended generalized minimum variance control which consists of a feedforward disturbance compensation as well as a pole placement feedback control is suggested to reduce the stabilization errors caused from the friction disturbances. This modeling and control are applied to a small experimental set-up and the experimental results confirm the accuracy of the model and the effectiveness of the suggested control.

• 대한전기학회논문지
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• 제37권8호
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• pp.557-562
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• 1988

This paper presents a class of discrete adaptive controller that can be applied to a plant without sufficient a priori information. It is well known that the GMV(Generalized Minmum Variance) contrlller performs satisfactorily if the plant time delay is known. By introducing the long-range prediction into the GMV controller, robustness to the time delay can be improved, although optimality is lost. Such an idea motivates a predictive control system to be proposed here, where the system minimizes multi-stage cost via the GMV approach. Moreover, the detuning control weight is determined by an on-line tuning method. It is shown that robustness, computational efficiency, and performance of the resulting control system are improved as compared with those of the GPC(Generalized Predictive Control)system.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1988년도 전기.전자공학 학술대회 논문집
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• pp.902-904
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• 1988

For a generalized minimum variance controller algorithm the weighting polynomials are are calculated in a way to assign the closed loop poles of the system and to specify the controller gain at a frequency. As a result the oscillations in the control signal may be reduced without changing the deterministic behaviour of the system.

• Journal of Mechanical Science and Technology
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• 제18권3호
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• pp.379-387
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• 2004

A novel flatness sensing system which is called the Flatness Sensing Inter-stand Looper(FlatSIL) system is suggested and a self-tuning PI control system using the FlatSIL is designed for improving the flatness of hot strip in finishing mill processes. The FlatSIL system measures the tension along the direction of the strip width by using segmented rolls, and the tension profile is approximated through the tension of each segmented roll. The flatness control system is operated by using the tension profile. The proposed flatness control system as far as the tension profile-measuring device works for the full strip length during the strip rolling in finishing mills. The generalized minimum variance self-tuning (GMV S-T) PI control method is applied to control the flatness of hot strip which has a design parameter as weighting factor for updating the PI gains. Optimizing the design parameter in the GMV S-T PI controller, the Robbins-Monro algorithm is used. It is shown by the computer simulation and experiment that the proposed GMV S-T PI flatness control system has better performance than the fixed PI flatness control system.