• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1008-1013
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• 2005

In this paper, position tracking control of an autonomous helicopter is presented. Velocity is controlled by using an optimal state controller LQR. A position control loop is added to form a PD controller. To minimize a position tracking error, neural network is introduced. The reference compensation technique as a neural network control structure is used, and a position tracking error of an autonomous helicopter is compensated by neural network installed in the remotely located ground station. Considering time delays between an autonomous helicopter and the ground station, simulation studies have been conducted. Simulation results show that the LQR with neural network compensation performs better than that of the LQR itself.

• Journal of the Korean Institute of Intelligent Systems
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• v.23 no.3
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• pp.268-274
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• 2013

Any new method for controlling a nonlinear system has widely been reported. An inverted pendulum system has typically been used as a target system for demonstrating its usefulness. In this paper, we propose an algorithm to control a flexible joint cart based inverted pendulum system. Two carts are connected with a spring and one is a driving cart and the other is no driving cart with a pole. We here present a system modeling and a good fuzzy logic based control algorithm. We also introduce LQR (Linar Quadratic Regulator) technique for reducing the number of control variables. By using this technique, the number of input variables for a fuzzy logic controller is become only two not six. So the computational complexity is largely reduced. Moreover, a two-input fuzzy logic controller has a control rule table with a skew-symmetric property. And it will lead the design of a single-input fuzzy logic controller. In order to demonstrate the usefulness of the proposed method and prove the superiority of the proposed method, some computer simulations are presented.

• 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.

• 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 KIEE Conference
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• 2002.07d
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• pp.2171-2175
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• 2002

Helicopter dynamics are plenty of nonlinearity. A complete mathematical model including propeller dynamics and fortes generated by the propellers is very difficult to obtain. So the method used to design to design a controller is a parameter estimation. Design controller based on variable structure system. This paper deals with LQR control technique to control efficiently, its elevation angle and azimuth one. The purpose of the experiment is to design a controller allows to use a desired elevation angle and azimuth ones. The system model has a helicopter model with 2-degree-of freedom. The simulation results were verified usefulness of controller.

• 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.

• Structural Engineering and Mechanics
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• v.81 no.5
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• pp.633-645
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• 2022

The active tuned mass damper (ATMD) is an efficient and reliable structural control system for mitigating the dynamic response of structures. The inertial force that an ATMD exerts on a structure to attenuate its otherwise large kinetic energy and undesirable vibrations and displacements is proportional to its excursion. Achieving a balance between the inertial force and excursion requires a control law or feedback mechanism. This study presents a technique for the optimum design of a sliding mode controller (SMC) as the control law for ATMD-equipped structures subjected to earthquakes. The technique includes optimizing an SMC under an artificial earthquake followed by testing its performance under real earthquakes. The SMC of a real 11-story shear building is optimized to demonstrate the technique, and its performance in mitigating the displacements of the building under benchmark near- and far-fault earthquakes is compared against that of a few other techniques (proportional-integral-derivative [PID], linear-quadratic regulator [LQR], and fuzzy logic control [FLC]). Results indicate that the optimum SMC outperforms PID and LQR and exhibits performance comparable to that of FLC in reducing displacements.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 1996.04a
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• pp.113-118
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• 1996

Nonlinear Attitude Dynamic Equation for rigid-body satellite is derived and linearzed. Estimator using Kalman filter and controller are designed. Controller using LQR technique implemented on satellite under torque disturbance shows much better performance than those by using of Bang-Bang technique.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10a
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• pp.324-327
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• 1996

This paper describes the robust controller design methods applied to the problem of an automatic system for tow-vehicle/trailer combinations. This study followed an inverse Linear Quadratic Regulator(LQR) approach which combines pole assignment methods with conventional LOR methods. It overcomes two concerns associated with these separate methods. It overcomes the robustness problems associated with pole placement methods and trial and error required in the application of the LQR problem. Moreover, a Kalman filter is used as the observer, but is modified by using the loop transfer recovery (LTR) technique with modified transmission zero assignment. The proposed inverse LQG,/LTR controllers enhances the forward motion stability and maneuverability of the combination vehicles. At high speeds, where the inherent yaw damping of the vehicle system decreases, the controller operates to maintain an adequate level of yaw damping. At backward moton, both 4WS (2WS tow-vehicle, 2WS trailer) and 6WS (4WS tow-vehicle, 2WS trailer) control laws are proposed by using inverse LQG/LTR method. To evaluate the stability and robustness of the proposed controllers, simulations for both forward and backward motion were conducted using a detailed nonlinear model. The proposed controllers are significantly more robust than the previous controllers and continues to operate effectively in spite of parameter perturbations that would cause previous controllers to enters limit cycles or to loose stability.

• International Journal of Control, Automation, and Systems
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• v.6 no.4
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• pp.506-514
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• 2008

This paper presents an intelligent model; named as free model, approach for a closed-loop system identification using input and output data and its application to design a power system stabilizer (PSS). The free model concept is introduced as an alternative intelligent system technique to design a controller for such dynamic system, which is complex, difficult to know, or unknown, with input and output data only, and it does not require the detail knowledge of mathematical model for the system. In the free model, the data used has incremental forms using backward difference operators. The parameters of the free model can be obtained by simultaneous perturbation stochastic approximation (SPSA) method. A linear transformation is introduced to convert the free model into a linear model so that a conventional linear controller design method can be applied. In this paper, the feasibility of the proposed method is demonstrated in a one-machine infinite bus power system. The linear quadratic regulator (LQR) method is applied to the free model to design a PSS for the system, and compared with the conventional PSS. The proposed SPSA-based LQR controller is robust in different loading conditions and system failures such as the outage of a major transmission line or a three phase to ground fault which causes the change of the system structure.