• Journal of the Korean Society for Precision Engineering
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• v.16 no.5 s.98
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• pp.169-174
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• 1999

In this paper, the CLQR(Constrained LQR) controller, which considers the actuator saturation in a cross-product term of a given performance index for an automotive active suspension control has been proposed. The effects of actuator saturations have been reflected directly in the states by using the linear relation between the control input and states. The method proposed here is more effective and intuitive compared with the conventional schemes. The CLQR has been applied to designing an automotive active suspension control system to verify its effectiveness and practical aspects.

• IEMEK Journal of Embedded Systems and Applications
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• v.6 no.3
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• pp.132-138
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• 2011

This paper presents an intelligent control approach for lateral position control of an autonomous four wheel steered snowplowing robotic vehicle. The vehicle is built for removing snow on the highway. Dynamics of the vehicle is derived and linearized for LQR control. Lateral position is controlled by the LQR method first, then the neural network control technique is introduced to improve tracking performances under the presence of load. The feasibility of using four wheel steering control is investigated by simulation studies of lateral position tracking of the Ford F-250 truck model. Performances of a LQR control method and a neural network control method under virtual snowplowing situation are compared.

• Journal of Wind Energy
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• v.2 no.1
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• pp.74-81
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• 2011

This paper deals with the application of LQ control to the power curve tracking control of wind turbine. However, two more additional tasks are required to apply the LQR theory to wind turbine control. One is the tracking problem instead of regulation, because the wind turbine is controlled as variable speed and variable pitch. The other is LQ integral control., because the rotor speed should be tightly controlled without any steady state error. Starting from the analysis of wind characteristics, design requirement of a wind turbine control system is defined. A design procedure of LQ tracking with integral control is introduced. The performance of LQ tracking system is analyzed and evaluated by numeric simulation.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.41 no.3
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• pp.217-225
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• 2013

Typical quadrotor aircraft use four differential thrust vectors to control the motion. In this study, we design a quadrotor aircraft using collective and cyclic control to improve the shortcomings of existing quadrotor aircraft. The quadrotor aircraft with cyclic control can fly at various attitudes due to the excessive control degrees of freedom. Hence the quadrotor aircraft with cyclic control is suitable as high performance aircraft. In this study, modeling and stability analysis of the quadrotor aircraft have been performed using FLIGHTLAB. LQR control systems were designed using linear models at various flight conditions and verified through nonlinear simulations using MATLAB.

• Proceedings of the KIEE Conference
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• 2005.05a
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• pp.87-89
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• 2005

This paper presents an optimal tuning method of the decentralized PI controller of the two-input, two-output(TITO) second order system with time-delay using LQR approach.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.5
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• pp.551-556
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• 2014

This paper proposes a balancing control and driving control of a bicycle robot based on dynamic modeling of the bicycle robot, which has been derived using the Lagrange equations. For the balancing control of the bicycle robot, a reaction wheel pendulum method has been adopted in this research. By using the dynamics equations of the bicycle robot, an LQR controller has been designed for a balancing and driving control of a bicycle robot. The performance of the balance control is verified experimentally before the driving control, which shows a stable posture within one degree vibrations. To show the dynamic characteristics of the bicycle robot during driving, a trapezoidal velocity trajectory is selected as the references. Through simulations and real experiments, the effectiveness of the proposed algorithm has been demonstrated.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2000.04b
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• pp.431-438
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• 2000

The cost function consists of the weighting functions concerning the structural responses to be controlled and the controller capability. Therefore, the control efficiency depends on the characteristics of the weighting functions. The objective of this paper is the comparative study of the time domain control strategies of LQR and LQG and the frequency domain strategy of H₂ by setting the equivalent weighting functions to the all control strategies. As a result of analysis, LQR strategy is found to be more efficient than other strategies in terms of the response reduction. but the control force is found to be a little highter. As LQG can compensate the limitation of LQR that all state variables should be identified, LQG is more acceptable algorithm than LQR. Furthermore LQG shows a good performance both in the response reduction and the control force. Finally H₂ algorithm is employed to illustrate the importance of weighting filters considering the frequency characteristics of the response and the controller. It Is shown that the H₂ algorithm is found to be the most effective one for the response control with a little control force having a low frequency band.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1080-1085
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• 2005

A hybrid control scheme is proposed for the stabilization of backward movement along simple paths for a vehicle composed of a truck and six trailers. The hybrid comprises the combination of a linear quadratic regulator (LQR) and a neurocontroller (NC) that is trained by a genetic algorithm (GA). Acting singly, either the NC or the LQR are unable to perform satisfactorily over the entire range of the operation required, but the proposed hybrid is shown to be capable of providing good overall system performance. The evaluation function of the NC in the hybrid design has been modified from the conventional type to incorporate both the squared errors and the running steps errors. The reverse movement of the trailer-truck system can be modeled as an unstable nonlinear system, with the control problem focusing on the steering angle. Achieving good backward movement is difficult because of the restraints of physical angular limitations. Due to these constraints the system is impossible to globally stabilize with standard smooth control techniques, since some initial states necessarily lead to jack-knife locks. This paper demonstrates that a hybrid of neural networks and LQR can be used effectively for the control of nonlinear dynamical systems. Results from simulated trials are reported.

• Journal of the Korea Institute of Military Science and Technology
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• v.12 no.4
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• pp.540-547
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• 2009

In the near future, military robots are likely to be substituted for military personnel in the field of battle. The power system of a legged robot is considerably more complex than the one used for a land vehicle because of the coordination and stability issues due to the large number of degree of freedom. In this paper, a servovalve-piston combination system for a straight-line motion of robot leg is modeled as three degree of freedom based on double inputs and single output transfer function. The output is the displacement of piston from neutral. The inputs are valve displacement from neutral and arbitrary load force in this system. LQR(Linear Quadratic Regulator) technique is applied in order to achieve robust stability and fast responses of the system. The Kalman filter loop, rejection of disturbance and noise, riccati equation, filter gain matrix, and frequency domain equality are analyzed and designed.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.40 no.2
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• pp.118-128
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• 2012

The goal of this paper is to design the target tracking controller for a quadrotor micro UAV using a vision sensor. First of all, the mathematical model of the quadrotor was estimated through the Prediction Error Method(PEM) using experimental input/output flight data, and then the estimated model was validated via the comparison with new experimental flight data. Next, the target tracking controller was designed using LQR(Linear Quadratic Regulator) method based on the estimated model. The relative distance between an object and the quadrotor was obtained by a vision sensor, and the altitude was obtained by a ultra sonic sensor. Finally, the performance of the designed target tracking controller was evaluated through flight tests.