• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.41.4-41
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• 2001

In this paper, we propose a LQR(Linear Quadratic Regulator) controller design for the active suspension using two-degree-of-freedom quarter-car model. We can improve the inherent suspension problem, the tradeoff between ride quality and suspension travel by selecting appropriate weights in the LQR-objective function. Because any definite rules for selecting weights do not exist, we replace the designer´s trial and error with the optimization-algorithm, ES(Evolution Strategy). Using the ES, we can find the proper control gains for selected frequencies, which have major effects on the vibrations of the vehicle´s state variables.

• Proceedings of the KIEE Conference
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• 2004.11c
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• pp.62-65
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• 2004

An optimal robust controller design method for gun driving system is discussed in this paper. The parameters of the gun driving controller are tuned by using the LQR characteristics for the performance and robustness. Tuning method that optimize velocity error gives a significant improvement over the existing PID tuning methods. It is shown that the tuning result of real gun driving system which is regarded as rigidness model or stiffness model satisfy performance and robustness.

• Proceedings of the KIEE Conference
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• 2001.11c
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• pp.3-6
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• 2001

This paper presents optimal robust PID controller design method for second order systems to satisfy the design specifications in time domain. The parameters of PID controller are determinated by the weighting factors Q and R of cost function. It is suggested that the selection of Q and R matrix can be determinated by its relationship with the natural frequency of ITAE criterion.

• Smart Structures and Systems
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• v.20 no.3
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• pp.273-283
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• 2017

This paper presents and compares three feedback control strategies for active control of noise inside a 3-D vibro-acoustic cavity. These are a) control strategy based on direct output feedback (DOFB) b) control strategy based on linear quadratic regulator (LQR) to reduce structural vibrations and c) LQR control strategy with a weighting scheme based on structural-acoustic coupling coefficients. The first two strategies are indirect control strategies in which noise reduction is achieved through active vibration control (AVC), termed as AVC-DOFB and AVC-LQR respectively. The third direct strategy is based on active structural-acoustic control (ASAC). This strategy is an LQR based optimal control strategy in which the coupling between the various structural and the acoustic modes is used to design the controller. The strategy is termed as ASAC-LQR. A numerical model of a 3-D rectangular box cavity with a flexible plate (glued with piezoelectric patches) and with other five surfaces treated rigid is developed using finite element (FE) method. A single pair of collocated piezoelectric patches is used for sensing the vibrations and applying control forces on the structure. A comparison of frequency response function (FRF) of structural nodal acceleration, acoustic nodal pressure, and piezoelectric actuation voltage is carried out. It is found that the AVC-DOFB control strategy gives equal importance to all the modes. The AVC-LQR control strategy tries to consume the control effort to damp all the structural modes. It is seen that the ASAC-LQR control strategy utilizes the control effort more intelligently by adding higher damping to those structural modes that matter more for reducing the interior noise.

• Journal of the Korean Institute of Intelligent Systems
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• v.26 no.1
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• pp.16-22
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• 2016

The research on two-wheeled inverted pendulum (TWIP) mobile robots has been ongoing in a number of robotic laboratories around the world. In this paper, we consider a robust controller design for the TWIP mobile robot driving on uniform slopes. We use a 2 degree-of-freedom (DOF) model which is obtained by restricting the spinning motion in a 3 DOF motion dynamic equation. In order to design the robust controller guaranteeing stability of the TWIP mobile robot driving on inclined surface, we propose a sliding mode control based on the theory of variable structure systems and design a sliding surface using the theory of the linear quadratic regulation (LQR). For simulation, the dynamic model of the TWIP mobile robot is constructed using Mathworks' Simulink and the sliding mode control is also implemented using Simulink. From simulation results, we show that the proposed controller effectively controls the TWIP mobile robot driving on slopes.

• 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.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.50 no.2
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• pp.103-110
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• 2022

Degradation of handling qualities(HQs) due to bad weather or mechanical failure can pose a fatal risk to pilots unfamiliar with such situation. In particular, icing is an important issue to consider as it is a frequent cause of accidents. Most of the previous research works focuses on aerodynamic performance changes due to icing and the corresponding icing modeling or methods to prevent icing, whereas the present work attempts to actively compensate for HQ degradation due to icing on a full-scale helicopter through flight control law design. To this end, the present work first demonstrates HQ degradation due to icing using CONDUIT software, and subsequently presents a robust control design via the RS-LQR(Robust Servomechanism Linear Quadratic Regulation) procedure to compensate for the HQ degradation. Simulation results show that the proposed robust control maintains Level 1 HQ in the presence of icing.

• 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.

• 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 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.