• Structural Engineering and Mechanics
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• v.85 no.5
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• pp.607-620
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• 2023

The classical optimal control (COC) method has been widely used for linear quadratic regulator (LQR) problems of structural control. However, the equation of motion of the structure is incorporated into the optimization model as the constraint condition for the LQR problem, which needs to be solved through the Riccati equation under certain assumptions. In this study, an explicit optimal control (EOC) method is proposed based on the explicit time-domain method (ETDM). By use of the explicit formulation of structural responses, the LQR problem with the constraint of equation of motion can be transformed into an unconstrained optimization problem, and therefore the control law can be derived directly without solving the Riccati equation. To further optimize the weighting parameters adopted in the control law using the gradient-based optimization algorithm, the sensitivities of structural responses and control forces with respect to the weighting parameters are derived analytically based on the explicit expressions of dynamic responses of the controlled structure. Two numerical examples are investigated to demonstrate the feasibility of the EOC method and the optimization scheme for weighting parameters involved in the control law.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10a
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• pp.647-651
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• 1992

This paper presents a model-based control scheme for a robot manipulator to track a desired trajectory as closely as possible in spite of a wide range of manipulator motions and parameter uncertainties of links and payload. The scheme has two components: a nominal control and a variational control. The nominal control, generated from direct calculation of the manipulator dynamics along a desired trajectory, drives the manipulator to a neighborhood of the trajectory. Then a discrete-time PID regulator is designed based on the linearized dynamic model and Linear Quadratic(LQ) method, which generates the variational control that regulates perturbations in the vicinity of the desired trajectory.

• Journal of KSNVE
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• v.7 no.2
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• pp.301-310
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• 1997

This paper presents active noise control method to form the near-field quiet zone for passengers in an automobile. The actuator model including interior acoustic plant, speaker and amplifier is experimentally identified in forms of auto-regressive and moving average by means of least mean square algorithm, The digital controller is composed of the regulator and Kalman filter to be designed based on LQG (linear quadratic gaussian). If the actuator model is prefiltered with digital filter to be properly designed for concentrating control performance index on the frequency band of primary noise source, LQG design approach can be effectively applied for the design of headset controller. Experimental results demonstrate that near-field quiet zone showing about 10dB noise reduction at microphone position can be formed using the headset located at passenger seat.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.2
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• pp.236-242
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• 2008

In this paper, we propose an optimized fuzzy controller based on Hierarchical Fair Competition-based Genetic Algorithms (HFCGA) for rotary inverted pendulum system. We adopt fuzzy controller to control the rotary inverted pendulum and the fuzzy rules of the fuzzy controller are designed based on the design methodology of Linear Quadratic Regulator (LQR) controller. Simple Genetic Algorithms (SGAs) is well known as optimization algorithms supporting search of a global character. There is a long list of successful usages of GAs reported in different application domains. It should be stressed, however, that GAs could still get trapped in a sub-optimal regions of the search space due to premature convergence. Accordingly the parallel genetic algorithm was developed to eliminate an effect of premature convergence. In particular, as one of diverse types of the PGA, HFCGA has emerged as an effective optimization mechanism for dealing with very large search space. We use HFCGA to optimize the parameter of the fuzzy controller. A comparative analysis between the simulation and the practical experiment demonstrates that the proposed HFCGA based fuzzy controller leads to superb performance in comparison with the conventional LQR controller as well as SGAs based fuzzy controller.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1382-1386
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• 2003

In this paper, we propose a controller for the position of a cart and the angle of a pendulum. To achieve both purposes simultaneously, we divide the system into the dominant subsystem and the dominated one after partial feedback linearization. The proposed controller is composed of a nonlinear controller stabilizing the dominant subsystem and a linear quadratic controller. Using the proposed controller, the controllable region is increased by the nonlinear control part and the control input minimized by the linear control part (LQR).

• 제어로봇시스템학회:학술대회논문집
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• 1999.10a
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• pp.79-82
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• 1999

The right half plane (RHP) zeros may cause severe problems, such as undershoots, oscillations and time delay in the transient response of the systems. In this paper, we formulate a linear quadratic type problem to deal with the effects of the RHP zeros in the nonminimum phase systems. Based on the LQ formulation, this paper shows the trade-off relation between undershoot and rising time performances in nonminimum phase systems by using a new performance index which consists of new state and tracking error. And performances of the proposed method are shown via computer simulations.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.1091-1094
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• 1996

The Object of this study is to find the relations between LQR and eigenstructure assignment regulator. Algorithms for computing weighting matrices are proposed for the case that (i) closed-loop eigenvalues are specified, and (ii) closed-loop gain matrix is given. We also present a new eigenstructure assignment algorithm that minimizes a linear quadratic performance index.

• 제어로봇시스템학회:학술대회논문집
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• 1987.10a
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• pp.812-816
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• 1987

A quadratic regulator problem for a class of nonlinear system, in which a small parameter multiplies the control cost, is considered. In the analysis of the problem, we utilize the method of multiple time-scale decomposition which has been devised for analyzing complex linear cheap control problems. In so doing, we extend the class of nonlinear systems, considerably, for which the minimum cost becomes zero as the small parameter goes to zero.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.75.4-75
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• 2001

This paper designs the robust hybrid controller for the multi degree-of-freedom system having uncertainty caused by modeling error and disturbances. The controlled plant is the construction which has an active dynamic vibration absorber on the top and is excited by the El Centre earthquake at the base. The active controller designed by the LQR(Linear Quadratic Regulator) and H-infinity control theory. The robustness of the hybrid H$\infty$ controller is compared with that of the hybrid LQ controller from computer simulation.

• 제어로봇시스템학회:학술대회논문집
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• 1990.10b
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• pp.1049-1054
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• 1990

We formulate optimal quadratic regulator problems with trajectory sensitivity terms as a optimization problem for a fixed controller structure. Using well-known techniques for parametric LQ problems, we give an algorithm to obtain suboptimal feedback gains by iterative solutions of two Lyapunov equations. A numerical example is given to illustrate the effectiveness of the proposed algorithm.