• 제어로봇시스템학회논문지
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• 제4권3호
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• pp.280-288
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• 1998

In this paper, a novel relation between the weighting matrix Q in LQR and the eigenstructure of the desired closed-loop system is proposed. Thus, the state feedback gain with the desired eigenstructure in the LQR can be obtained. The proposed scheme is applied to design a simple 3rd-order system and a flight control system design to show the usefulness of the scheme.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2005년도 심포지엄 논문집 정보 및 제어부문
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• pp.109-112
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• 2005

This paper presents an optimal and robust PI-PD controller design method for the second-order systems both with dead time and without dead time to satisfy the design specifications in the time domain via LQR design technique. The optimal tuning method of PI-PD controller are also developed by setpoint weighting and neural networks. It is shown that the simulation results show significantly improved performance by proposed method.

• 제어로봇시스템학회논문지
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• 제11권10호
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• pp.864-869
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• 2005

This paper proposes a new method for LQR controller design. It is unsystematic and difficult to design an LQR controller by trial and error. The proposed method is capable of systematically calculating weighting matrices for desired pole(s) by the pole's moving-range in S-plane and the relational equation between closed-loop pole(s) and weighting matrices. This will provide much-needed functionality to apply LQR controller. The example shows the feasibility of the proposed method.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2003년도 하계종합학술대회 논문집 V
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• pp.2509-2512
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• 2003

The active magnetic bearing(AMB) has statey-state error of the displacement by the external force. This paper presents a PID controller design using LQR method in the active magnetic bearing to compensate for the displacement by the external force.

• 한국정밀공학회지
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• 제22권8호
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• pp.34-41
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• 2005

Generally, it is not easy to get a suitable controller for multi variable systems. If the modeling equation of the system can be found, it is possible to get LQR control as an optimal solution. This paper suggests an LQR learning method to design LQR controller without the modeling equation. The proposed algorithm uses the same cost function with error and input energy as LQR is used, and the LQR controller is trained to reduce the function. In this training process, the Jacobian matrix that informs the converging direction of the controller Is used. Jacobian means the relationship of output variations for input variations and can be approximately found by the simple experiments. In the simulations of a hydrofoil catamaran with multi variables, it can be confirmed that the training of LQR controller is possible by using the approximate Jacobian matrix instead of the modeling equation and this controller is not worse than the traditional LQR controller.

• 제어로봇시스템학회논문지
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• 제5권6호
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• pp.676-682
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• 1999

A study which develops a controller design methodology that has flexibility of eigenstructure assignment within the stability-robustness contraints of LQR is requried and has been performed. The previously developd control design methodology, namely, EALQR(Eigenstructure Assignment/LQR) has better performance than that of conventional LQR or eigenstructure assignment but has a constraint for the weitgting matrix in LQR, which could be indefinite for high-order system. In this paper, the effects of the indefinite Q in EALQR on the frequency domain properties are analyzed. The robustness criterion and quantitative frequency domain properties are also resented. Finally, the frequency domain properties of EALQR has been analyzed by applying to a flight control system design example.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2002년도 합동 추계학술대회 논문집 정보 및 제어부문
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• pp.46-49
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• 2002

This paper presents I-PD controller design using LQR method in a two-inerita motor system to satisfy the design specification in time domain. And to provide a systematic LQ analysis for two-inerita motor system. The tuning parameters of LQ(I-PD) controller are determinated by the relationships between the design parameters of the overshoot and the settling time which are design specifications in time domain, and the weighting factors Q and R in LQR we can achieve the performance-robustness in time domain as well as the stability-robustness.

• 에너지공학
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• 제13권1호
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• pp.68-74
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• 2004

본 논문에서는 전압 sag 보상을 위한 배전용 정지형 보상기 (DSTATCOM) 제어기를 설계하고 PSCAD/EMTDC로 확인하였다. DSIATCOM의 전류성분을 dq분해 해석을 통하여 상태방정식을 유도하고 부하모델과 네트워크의 제약조건을 고려하여 결합 모델을 제시하였다. 1선 지락 사고시 PI 제어기보다 LQR 제어기의 응답 특성이 우수함을 검증하고 전압 Sag가 개선됨을 보였다.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1996년도 한국자동제어학술회의논문집(국내학술편); 포항공과대학교, 포항; 24-26 Oct. 1996
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• pp.988-991
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• 1996

The purpose of this thesis is to develop methods of designing robust LQR/LQG controllers for time-varying systems with real parametric uncertainties. Controller design that meet desired performance and robust specifications is one of the most important unsolved problems in control engineering. We propose a new framework to solve these problems using Linear Matrix Inequalities (LMls) which have gained much attention in recent years, for their computational tractability and usefulness in control engineering. In Robust LQR case, the formulation of LMI based problem is straightforward and we can say that the obtained solution is the global optimum because the transformed problem is convex. In Robust LQG case, the formulation is difficult because the objective function and constraint are all nonlinear, therefore these are not treatable directly by LMI. We propose a sequential solving method which consist of a block-diagonal approach and a full-block approach. Block-diagonal approach gives a conservative solution and it is used as a initial guess for a full-block approach. In full-block approach two LMIs are solved sequentially in iterative manner. Because this algorithm must be solved iteratively, the obtained solution may not be globally optimal.

• 제어로봇시스템학회논문지
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• 제13권6호
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• pp.574-580
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• 2007

This paper deals with LQR controller design method tor system having complex poles. The proposed method is capable of systematically calculating weighting matrices based on the pole's moving-range and the relational equation between closed-loop pole(s) and weighting matrices. The method moves complex poles to complex poles or two distinct real poles. This will provide much-needed functionality to apply LQR controller. The example shows the feasibility of the proposed method.