• Earthquakes and Structures
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• 제27권5호
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• pp.401-417
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• 2024

This study presents a method for optimization of weighting matrices of the linear quadratic regulator (LQR) control algorithm in order to design an optimal active control system using metaheuristic algorithms. The LQR is a widely used control technique in engineering for designing optimal controllers for linear systems by minimizing a quadratic cost function. However, the performance of the LQR strongly depends on the appropriate selection of weighting matrices, which are usually determined by some thumb rule or exhaustive search method. In the present study, for the optimization of weighting matrices, four metaheuristic algorithms including, Particle Swarm Optimization (PSO), Genetic Algorithm (GA), Grey Wolf Optimizer (GWO) and, Whale Optimization Algorithm (WOA) are considered. To generate optimal weighting matrices, the objective function used consists of displacement and absolute acceleration. During the optimization process, a response effectiveness factor is also checked for displacement and acceleration as a constraint for the proper selection of weighting matrices. To study the effectiveness of optimized active control system to those for the exhaustive search method, the various controlled responses of the system are compared with the corresponding uncontrolled system. The optimized weighting matrices effectively reduce the displacement, velocity, and acceleration responses of the structure. Based on the simulation study, it can be observed that GWO performs well compared to the PSO, GA, and WO algorithms. By employing metaheuristic algorithms, this study showcases a more efficient and effective approach to finding optimal weighting matrices, thereby enhancing the performance of active control systems.

• 한국지진공학회:학술대회논문집
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• 한국지진공학회 2002년도 춘계 학술발표회 논문집
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• pp.475-482
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• 2002

This paper provides the systematic procedure to determine the weighting matrices of optimal controllers considering structural energy. Optimal controllers consist of LQR and ILQR. The weighting matrices are needed first in the conventional optimal control design strategy. However, they are in general dependent on the experienced knowledge of controll designers. Applying the Lyapunov function to the total structural energy and using the contrition that its derivative is negative, we can determine the weighting matrices without difficulty. It is proven that the control efficiency is achieved well for LQR and ILQR.

• 한국지진공학회논문집
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• 제6권6호
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• pp.49-53
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• 2002

가중행렬은 일반적인 최적 제어 설계에서 우선적으로 필요하지만 일반적으로 제어 설계자들 이 경험적 지식에 의존하고 있다. 이 논문은 구조물의 에너지를 고려한 최적제어기의 가중행렬을 결정하는 체계적인 절차를 제시하였다. 최적제어기는 LQR과 ILQR로 구분될 수 있다. 구조물의 총에너지를 고려한 Lyapunov 함수를 적용하고, 이로부터 유도된 식이 음수라는 상태를 이용하면 가중행렬을 어렵지 않게 구할 수 있다. 이러한 방법으로 산정된 가중행렬을 이용하여 LQR과 ILQR제어기를 설계하고 제어효율을 입증하였다.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1989년도 한국자동제어학술회의논문집; Seoul, Korea; 27-28 Oct. 1989
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• pp.473-476
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• 1989

Quadratic weighting matrices have an effect on the transition and steady state responses in a LQ tracking problem. They are usually decided on trial and error in order to get a good response. In this paper a method is presented which calculates a steady - state deviation without solving Riccati equation. By using this method, a new procedure for selecting the weighting matrices is proposed when a tolerance on the steady - state deviation is given.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1997년도 하계학술대회 논문집 D
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• pp.841-843
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• 1997

In this paper we present a Genetic approach to select weighting matrices of LQ(Linear Quadratic) controller for optimal TCSC(Thyristor Controlled Series Capacitor) control. A design of LQ controller depends on choosing weighting matrices. The selection of weighting matrices is usually carried out by trial and error, which is not a trivial problem. We proposed a efficient method using GA of finding weighting matrices for optimal control law. The proposed GA method was applied to design LQ controller of TCSC in one machine infinite bus system and showed good results.

• 조명전기설비학회논문지
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• 제16권6호
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• pp.40-50
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• 2002

본 논문에서는 정지형 무효전력 보상기에 대한 최적 LQ 제어기의 가중행렬 선정과정을 유전알고리즘을 이용하여 최적의 가중행렬을 결정하는 기법을 제시하였다. FACTS로 분류되는 여러 기기중 고정된 용량의 커패시터와 싸이리스터 제어에 의하여 용량이 가변되는 인덕터가 병렬로 연결된 구조를 가지고 있는 SVC 시스템은 전압을 효과적으로 제어할 뿐만 아니라 동기발전기의 댐핑을 향상시킬수 있다. LQ제어기의 설계는 최적 가중행렬 선정에 의존하므로 본 논문에서는 종래의 일반적인 방법과는 달리, 자연 생태계의 진화를 모의한 전역적 탐색 최적화 기법인 유전 알고리즘을 이용하여 설계하였다. 이에 대해 고유치 해석과 시뮬레이션을 통해 제어성능을 검토하여 우수한 제어 성능을 가지는 제어기를 최적화 기법인 GA에 의해서 설계할 수 있음을 확인하였다

• Journal of Communications and Networks
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• 제18권6호
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• pp.892-901
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• 2016

In the multi-user multiple-input multiple-output (MIMO) system, orthogonal random beamforming (ORBF) scheme is proposed to serve multiple users simultaneously in order to achieve the multi-user diversity gain. The opportunistic space-division multiple access system (OSDMA-S) scheme performs multiple weighting matrices during the training phase and chooses the best weighting matrix to be used to broadcast data during the transmitting phase. The OSDMA-S scheme works better than the original ORBF by decreasing the inter-user interference during the transmitting phase. To save more time in the training phase, a partly random multiple weighting matrices selection scheme is proposed in this paper. In our proposed scheme, the Base Station does not need to use several unitary matrices to broadcast pilot symbol. Actually, only one broadcasting operation is needed. Each subscriber generates several virtual equivalent channels with a set of pre-saved unitary matrices and the channel status information gained from the broadcasting operation. The signal-to-interference and noise ratio (SINR) of each beam in each virtual equivalent channel is calculated and fed back to the base station for the weighting matrix selection and multi-user scheduling. According to the theoretical analysis, the proposed scheme relatively expands the transmitting phase and reduces the interactive complexity between the Base Station and subscribers. The asymptotic analysis and the simulation results show that the proposed scheme improves the throughput performance of the multi-user MIMO system.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1988년도 한국자동제어학술회의논문집(국제학술편); 한국전력공사연수원, 서울; 21-22 Oct. 1988
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• pp.729-733
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• 1988

In this paper, a new procedure for selecting weighting matrices in linear discrete time quadratic optimal control problems (LQ-problem) is proposed. In LQ problems, the quadratic weighting matrices are usually decided on trial and error in order to get a good response. But using the proposed method, the quadratic weights are decided in such a way that all poles of the closed loop system are located in a desired area for good responses as well as for stability and values of the quadratic cost functional are kept less then a specified value. The closed loop systems constructed by this method have merits of LQ problems as well as those of pole assignment problems. Taking into consideration that little is known about the relationship among the quadratic weights, the poles and the values of cost functional, this procedure is also interesting from the theoretical point of view.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1998년도 하계학술대회 논문집 C
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• pp.1024-1026
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• 1998

In this paper we present a Neural network approach to select weighting matrices of Linear-Quadratic-Gaussian (LQG) controller for TCSC control. The selection of weighting matrices is usually carried out by trial and error. A weighting matrices of LQG control selected effectively using Neural network. It is shown that simulation results in application of this method to one machine infinite bus system are satisfactory.

• 대한전기학회논문지:전력기술부문A
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• 제48권3호
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• pp.212-219
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• 1999

In this paper we present a neural network approach to select weighting matrices of Linear-Quadratic-Gaussian(LQG) controller for TCSC control. The selection of weighting matrices is usually carried out by trial and error. A weighting matrices of LQG control are selected effectively using Kohonen network. It is shown that simulation results in application of this method to three machine nine bus system are satisfactory.