• Journal of Institute of Control, Robotics and Systems
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• v.16 no.12
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• pp.1201-1207
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• 2010

This paper shows to stabilize a balancing robot. We derive the dynamics of a balancing robot and design its controller using LQR method. For stabilizing balancing robot, we introduce a method to detect an angle using inertial sensors. In this study, we use a complementary filter to fuse signals by frequency response of gyroscope and accelerometer in order to measure the inclined angle of balancing robot. The filter coefficients are obtained by least square to minimize error in angle-detecting filter design. And then, after we derive a dynamics of balancing robot using Lagrange method, we linearize that dynamics for using LQR method.

• 제어로봇시스템학회:학술대회논문집
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• 1998.10a
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• pp.429-434
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• 1998

The previously developed control design methodology, EALQR(Eigenstructure Assignment/LQR), has better performance than that of conventional LQR or eigen-structure assignment. But it has a constraint for the weigting matrix in LQR, that is the weighting matrix could be indefinite for high-order systems. In this paper, the effects of the indefinite weighting matrix in EALQR on the Sequency domain properties are analyzed. The robustness criterion and quantitative frequency domain properties are also presented. Finally, the frequency do-main properties of EALQR has been analyzed by applying to a flight control system design example.

• Journal of the Korean Institute of Navigation
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• v.23 no.3
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• pp.35-44
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• 1999

This research aims to seek active control of ball-beam position stability by resorting to neural networks whose layers are given bias weights. The controller consists of an LQR (linear quadratic regulator) controller and a neural networks controller in parallel. The latter is used to improve the responses of the established LQR control system, especially when controlling the system with nonlinear factors or modelling errors. For the learning of this control system, the feedback-error learning algorithm is utilized here. While the neural networks controller learns repetitive trajectories on line, feedback errors are back-propagated through neural networks. Convergence is made when the neural networks controller reversely learns and controls the plant. The goals of teaming are to expand the working range of the adaptive control system and to bridge errors owing to nonlinearity by adjusting parameters against the external disturbances and change of the nonlinear plant. The motion equation of the ball-beam system is derived from Newton's law. As the system is strongly nonlinear, lots of researchers have depended on classical systems to control it. Its applications of position control are seen in planes, ships, automobiles and so on. However, the research based on artificial control is quite recent. The current paper compares and analyzes simulation results by way of the LQR controller and the neural network controller in order to prove the efficiency of the neural networks control algorithm against any nonlinear system.

• 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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• 1997.10a
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• pp.1867-1870
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• 1997

Waypoint guidance is a technique used to steer an autonomous vehicle along a desired trajectory. In this paper, a waypoint guidance algorithm for horizontal plane is derived by combining a line following guidance law and a turning guidance law. The line following guidance is derived based on LQR while the turning guidance is designed using rendzvous problem. Through simulation, the proposed method shows a good performance.

• Proceedings of the Korean Nuclear Society Conference
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• 1996.05a
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• pp.380-385
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• 1996

The genetic algorithm(GA) is applied to the design of the nuclear power control system. The reactor control system model is described in the LQR configuration. The LQR system order is increased to make the tracking system. The key parameters of the design are weighting matrices, and these are usually determined through numerous simulations in the conventional design. To determine the more objective and optimal weightings, the improved GA is applied. The results show that the weightings determined by the GA yield the better system responses than those obtained by tile conventional design method.

• Journal of Korean Association for Spatial Structures
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• v.8 no.4
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• pp.73-80
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• 2008

The objective of current study is to develop an optimization technique for the seismic actively controlled building structures using active tendon devices by an efficient solution of LQR control gain. In order to solve the active control system, the Ricatti closed-loop algorithm has been applied, and the state vector has been formulated by the transfer matrix and solved by a numerical technique of the trapezoidal rule. The time-delay problem has been also considered by phase compensation. To optimize the performance index, the ratio of the weighted matrix is the design variable, allowable story drift limits of IBC 2000 and tendon forces have been applied as restraint conditions, and the optimum control program has been developed with the algorithm of the SUMT technique. In examples of the optimization problem of eight stories shear buildings, it is evaluated that the optimum controlled building is more suitable in the control of earthquake response than the uncontrolled system and can reduce the performance index to compare with the controlled system with a constant ratio of the weighted matrix.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.39 no.6
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• pp.505-516
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• 2011

The concept of the IGC(Integrated Guidance and Control) has been introduced to overcome the performance limit of the SGC(Separated Guidance and Control) loop. A new type of IGC with impact angle constraint has been proposed in this paper. Angle of attack, pitch angle rate, pitch angle and line of sight angle are considered as state variables. A controllability analysis and equilibrium point analysis have been carried out to investigate the control characteristic of the prposed IGC. The LQR(Linear Quadratic Regulator) has been adopted for the control law and detailed explanations about the adoption has been provided. The performance comparison between the IGC and the SGC has been carried out. The result of numerical simulations shows that the IGC guarantees better guidance performance than the SGC when the agile maneuver is needed for a specific guidance geometry.

• Steel and Composite Structures
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• v.32 no.6
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• pp.753-767
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• 2019

Vibration control in mechanical equipments is an important problem where unwanted vibrations are vanish or at least diminished. In this paper, free vibration active control of the porous sandwich piezoelectric polymeric nanocomposite microbeam with microsensor and microactuater layers are investigated. The aim of this research is to reduce amplitude of vibration in micro beam based on linear quadratic regulator (LQR). Modified couple stress theory (MCST) according to sinusoidal shear deformation theory is presented. The porous sandwich microbeam is rested on elastic foundation. The core and face sheet are made of porous and three-phase carbon nanotubes/resin/fiber nanocomposite materials. The equations of motion are extracted by Hamilton's principle and then Navier's type solution are employed for solving them. The governing equations of motion are written in space state form and linear quadratic regulator (LQR) is used for active control approach. The various parameters are conducted to investigate on the frequency response function (FRF) of the sandwich microbeam for vibration active control. The results indicate that the higher length scale to the thickness, the face sheet thickness to total thickness and the considering microsensor and microactutor significantly affect LQR and uncontrolled FRF. Also, the porosity coefficient increasing, Skempton coefficient and Winkler spring constant shift the frequency response to higher frequencies. The obtained results can be useful for micro-electro-mechanical (MEMS) and nano-electro-mechanical (NEMS) systems.

• Proceedings of the KIEE Conference
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• 2011.07a
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• pp.1766-1767
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• 2011

본 논문에서는 기존의 proportional-integral-derivative (PID) 제어기의 이득조정과정에서 linear quadratic regulator(LQR)을 이용하여 이득조정을 하는 방법을 제안한다. 제안된 제어기의 이득은 LQR의 수식으로 표현되어지며 Matlab/simulink을 이용한 모의실험을 통해 위치프로파일에 대한 위치추종오차의 성능이 평가되어진다.