• 제어로봇시스템학회:학술대회논문집
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• 1993.10a
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• pp.987-993
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• 1993

A loop-shaping LQ controller is synthesized for tandem cold mills. And a new loop-shaping technique is suggested for LQ controller design. The suggested loop-shaping LQ control system is compared with the standard loop-shaping LQ control system. The simulation results show that the thickness and interstand tension control accuracy of tandem cold mills can be improved by the compensated loop-shaping LQ controller.

• Journal of the Korean Society for Precision Engineering
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• v.11 no.5
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• pp.66-74
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• 1994

A loop-shaping LQ controller is synthesized for tandem cold mills. And a new loop- shaping technique is suggested for LQ controller design. The suggested loop-shaping LQ control system is compared with the standard loop-shaping LQ control system. The simulation results show that the theickness and interstand tension control accuracy of tandem cold mills can be improved by the compensated loop-shaping LQ controller.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.8
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• pp.972-979
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• 1999

QFT(Quantitative Feedback Theory) is a very practical design technique that emphasizes the use of feedback for achieving the desired system performance tolerances in despite of plant uncertainty and disturbance. The fundamental concept of QFT is a loop shaping procedure that a suitable controller can be found by shaping a nominal loop transfer function. The loop shaping synthesis involves the identification of a structure and the specialization of parameter optimization of a desired system. This paper presents an improved loop shaping approach of QFT with model validation using GA(Genetic Algorithm). The method presented in this paper removes the problems of iterative operation, transformation error, and model validation in the conventional methods without consideration of frequency domain.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.433-437
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• 2003

Quantitative Feedback Theory (QFT) is one of effective methods of robust controller design. In QFT design we can considers the phase information of the perturbed plant so it is less conservative than $H_{\infty}$ and ${\mu}$-synthesis methods and as be shown, it is more transparent than the sensitivity reduction methods mentioned . In this paper we want to overcome the major drawback of QFT method which is lack of an automatic method for loop-shaping step of the method so we focus on the following problem: Given a nominal plant and QFT bounds, synthesize a controller that achieves closed-loop stability and satisfies the QFT boundaries. The usual approach to this problem involves loop-shaping in the frequency domain by manipulating the poles and zeros of the nominal loop transfer function. This process now aided by recently developed computer aided design tools proceeds by trial and error and its success often depends heavily on the experience of the loop-shaper. Thus for the novice and First time QFT user, there is a genuine need for an automatic loop-shaping tool to generate a first-cut solution. Clearly such an automatic process must involve some sort of optimization, and while recent results on convex optimization have found fruitful applications in other areas of control theory we have tried to use LMI theory for automating the loop-shaping step of QFT design.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.51 no.2
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• pp.94-98
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• 2002

QFT(Quantitative Feedback Theory) is a very practical design technique that emphasizes the use of feedback for achieving the desired system performance tolerances in despite of plant uncertainty and disturbance. The gain-phase loop shaping procedure of QFT is employed to design controller, until the bounds at desired frequencies are satisfied. This paper presents a transfer function synthesis using TLS(Total Least Squares) and offers a loop shaping method with the suggested technique. An example illustrates a feasibility of the presented algorithm.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.11C
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• pp.1062-1069
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• 2003

This paper presents a new loop shaping technique for design of robust optimal PID controllers in order to satisfy the performance requirements. PID controller can be designed by selecting the suitable weighting factors Q and R. This technique is developed by pushing all two zeros formed by PID controller closely to a larger pole of the second order plant. As a result, a good loop shaping is achieved in the high frequencies region on the Bode plot. For the robust optimal tuning of PID controller for second order system, a new loop shaping procedure is developed via LQR approach.

• Transactions of the Korean Society of Mechanical Engineers
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• v.18 no.10
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• pp.2629-2639
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• 1994

A robust multivariable controller is synthesized for tandem cold mills. A blocked-noninteracting control method is applied for simplifying the structure of rolling control systems. And, a loop-shaping LQ control method is applied for maintaining the variation of the thickness and tension of each rolling stand as small as possible. In this paper, the effects of the design parameter on loop-shaping and the number of control inputs are evaluated. The simulation results show that the thickness and tension control accuracy of tandem cold mills can be improved by the blocked-noninteracting and compensated loop-shaping LQ controller.

• Journal of Institute of Control, Robotics and Systems
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• v.8 no.8
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• pp.649-654
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• 2002

The essential philosophy of the QFT(Quantitative Feedback Theory) is that a suitable controller can be found by loop shaping a nominal loop transfer function such that the frequency response of this function does not violate the QFT bounds. The loop shaping synthesis involves the identification of a structure and its specialization by means of the parameter optimization. This paper presents an optimization algorithm to estimate the controller parameters from the frequency transfer function synthesis using the TLS(Total Least Squares) in the QFT loop shaping procedure. The proposed method identifies the parameter vector of the robust controller from an overdetermined linear system developed from rearranging the two dimensional system matrices and output vectors obtained from the QFT bounds. The feasibility of the suggested algorithm is illustrated with an example.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10a
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• pp.1028-1033
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• 1992

Loop shaping techniques are developed for the LQG/LTR controller design of singular multivariable sytems. One approach is to use the mode form of plant and the other is to replace the eigenvalues at 0 by ones at .epsilon.(.rarw.0). These two concepts for the target filter loop design are applied to a flight autopilot. And it is shown that these techniques are effective ones for the desired loop-shaping of singular multivariable systems.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.428-432
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• 2003

Quantitative Feedback Theory (QFT) is one of most effective methods of robust controller design and can be considered as a suitable method for systems with parametric uncertainties. Particularly it allows us to obtain controllers less conservative than other methods like $H_{\infty}$ and ${\mu}$-synthesis. In QFT method, we transform all the uncertainties and desired specifications to some boundaries in Nichols chart and then we have to find the nominal loop transfer function such that satisfies the boundaries and has the minimum high frequency gain. The major drawback of the QFT method is that there is no effective and useful method for finding this nominal loop transfer function. The usual approach to this problem involves loop-shaping in the Nichols chart by manipulating the poles and zeros of the nominal loop transfer function. This process now aided by recently developed computer aided design tools proceeds by trial and error and its success often depends heavily on the experience of the loop-shaper. Thus for the novice and First time QFT user, there is a genuine need for an automatic loop-shaping tool to generate a first-cut solution. In this paper, we approach the automatic QFT loop-shaping problem by using an algorithm involving Linear Programming (LP) techniques and Genetic Algorithm (GA).