• Journal of the Korean Society for Precision Engineering
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• v.22 no.8 s.173
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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.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.30 no.8
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• pp.71-77
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• 2002

We consider the simultaneous slewing and vibration suppression control problem of an idealized structural model which has a rigid hub with two cantilevered flexible appendages and finite tip masses. The finite clement method(FEM) is used to obtain linear finite dimensional equations of motion for the model. In the linear quadratic regulator(LQR) problem, a simple method is introduced to provide a physically meaningful performance index for space structure models. This method gives us a mathematically minor but physically important modification of the usual energy type performance index. A numerical procedure to solve a time-variant LQR problem with inequality control constraints is presented using the method of particular solutions.

• Journal of the Korean Society for Precision Engineering
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• v.23 no.9 s.186
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• pp.84-91
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• 2006

The synthesis of optimal controllers for multivariable systems usually requires an accurate linear model of the plant dynamics. Real systems, however, contain nonlinearities and high-order dynamics that may be difficult to model using conventional techniques. This paper presents a novel loaming method for the synthesis of LQR controllers that doesn't require explicit modeling of the plant dynamics. This method utilizes the sign of Jacobian and gradient descent techniques to iteratively reduce the LQR objective function. It becomes easier and more convenient because it is relatively very easy to get the sign of Jacobian instead of its Jacobian. Simulations involving an overhead crane and a hydrofoil catamaran show that the proposed LQR-LC algorithm improves controller performance, even when the Jacobian information is estimated from input-output data.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.10
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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.

• Proceedings of the KIEE Conference
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• 2005.05a
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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.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.6
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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.

• Proceedings of the IEEK Conference
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• 2003.07c
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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.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.11
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• pp.930-935
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• 2005

In this paper, position tracking control of an autonomous helicopter is presented. Combining an LQR method and a proportional control forms a simple PD control. Since LQR control gains are set for the velocity control of the helicopter, a position tracking error occurs. To minimize a position tracking error, neural network is introduced. Specially, in the frame of the reference compensation technique for teaming neural network compensator, a position tracking error of an autonomous helicopter can be compensated by neural network installed in the remotely located ground station. Considering time delay between an auto-helicopter and the ground station, simulation studies have been conducted. Simulation results show that the LQR with neural network performs better than that of LQR itself.

• Smart Structures and Systems
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• v.23 no.3
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• pp.243-261
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• 2019

This paper introduces an appropriate technique to estimate the weighting matrices used in the linear quadratic regulator (LQR) method for active structural control. For this purpose, a parameter is defined to regulate the relationship between the structural energy and control force. The optimum value of the regulating parameter, is determined for single degree of freedom (SDOF) systems under seismic excitations. In addition, the suggested technique is generalized for multiple degrees of freedom (MDOF) active control systems. Numerical examples demonstrate the robustness of the proposed method for controlled buildings under a wide range of seismic excitations.

• Proceedings of the Earthquake Engineering Society of Korea Conference
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• 2003.09a
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• pp.419-426
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• 2003

An efficient procedure using LQR method for determining optimal sliding surfaces appropriate for different controller types is provided. The parametric evaluation of the dynamic characteristics of sliding surfaces is peformed in terms of SMC controller performance of single-degree-of-freedom(SDOF) systems. The control force limit is considered in this procedure. Numerical simulations for multi-degree-of-freedom(MDOF) systems verify the effectiveness of proposed method.