• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.542-547
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• 2003

A new approach to design of a discrete-time robust $H_{\infty}$ filter in finite horizon case is proposed. It is shown that robust $H_{\infty}$ filtering problem can be cast into the minimization problem of an indefinite quadratic form, which can be solved by implementing the Kalman filter defined in Krein space. The proposed filter is readily derived by simply augmenting the state space model and has the robustness property against the parameter uncertainties of a given system.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.969-974
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• 2004

For a maneuvering unmanned autonomous helicopter, it is necessary to design a proper controller of each flight mode. In this paper, overall helicopter dynamics is derived and hovering model is linearized and transformed into a state equation form. However, since it is difficult to obtain parameters of stability derivatives in the state equation directly, a linear control model is derived by time-domain parametric system identification method with real flight data of the model helicopter. Then, two different controllers - a linear feedback controller with proportional gains and a robust controller - are designed and their performance is compared. Both proposed controllers show outstanding results by computer simulation. These validated controllers can be used to autonomous flight controller of a real unmanned model helicopter.

• Proceedings of the KIEE Conference
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• 2005.07d
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• pp.2477-2479
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• 2005

A robust bending frequency tracker is proposed to design the adaptive notch filter which removes the time-varying missile structural modes from the sensor measurements. To do this, the state-space form of a bending frequency model is derived under the assumption that the bending signal could be described as the lightly damped sinusoid. Since the resultant bending frequency model contains the parametric uncertainties in the measurement matrix, the design problem of bending frequency tracker is tackled by applying the robust Kalman filter to the model. This technique could be easily expanded to the multiple frequencies case because it newly illuminates the bending frequency tracking problem in view of general state estimation.

• The Journal of the Korea institute of electronic communication sciences
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• v.7 no.5
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• pp.1133-1138
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• 2012

In the paper, design of nonlinear sliding surfaces which are based on optimal control is studied, The state trajectory by the input of optimal control was obtained by Frobenius theorem and matrix decomposition method, was set the nonlinear sliding surfaces of the system. The states is maintained to sliding surfaces from initial states. As the result, robustness of the system can be guaranteed throughout an entire response of the system starting form the initial time instance, the uncertainty and external disturbance that can occur during the reaching time is removed, the problem of large control input was solved, and setting the sliding surfaces optimal path was able to reduce the tracking time. The validity of the proposed control scheme is shown in computer simulation for inverted pendulum.

• International Journal of Aeronautical and Space Sciences
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• v.8 no.1
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• pp.10-20
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• 2007

For spacecraft attitude control, reaction wheel (RW) steering laws with more than three wheels for three-axis attitude control can be derived by using a control allocation (CA) approach.1-2 The CA technique deals with a problem of distributing a given control demand to available sets of actuators.3-4 There are many references for CA with applications to aerospace systems. For spacecraft, the control torque command for three body-fixed reference frames can be constructed by a combination of multiple wheels, usually four-wheel pyramid sets. Multi-wheel configurations can be exploited to satisfy a body-axis control torque requirement while satisfying objectives such as minimum control energy.1-2 In general, the reaction wheel steering laws determine required torque command for each wheel in the form of matrix pseudo-inverse. In general, the attitude control command is generated in the form of a feedback control. The spacecraft body angular rate measured by gyros is used to estimate angular displacement also.⁵ Combination of the body angular rate and attitude parameters such as quaternion and MRPs(Modified Rodrigues Parameters) is typically used in synthesizing the control command which should be produced by RWs.¹ The attitude sensor signals are usually corrupted by noise; gyros tend to contain errors such as drift and random noise. The attitude determination system can estimate such errors, and provide best true signals for feedback control.⁶ Even if the attitude determination system, for instance, sophisticated algorithm such as the EKF(Extended Kalman Filter) algorithm⁶, can eliminate the errors efficiently, it is quite probable that the control command still contains noise sources. The noise and/or other high frequency components in the control command would cause the wheel speed to change in an undesirable manner. The closed-loop system, governed by the feedback control law, is also directly affected by the noise due to imperfect sensor characteristics. The noise components in the sensor signal should be mitigated so that the control command is isolated from the noise effect. This can be done by adding a filter to the sensor output or preventing rapid change in the control command. Dynamic control allocation(DCA), recently studied by Härkegård, is to distribute the control command in the sense of dynamics⁴: the allocation is made over a certain time interval, not a fixed time instant. The dynamic behavior of the control command is taken into account in the course of distributing the control command. Not only the control command requirement, but also variation of the control command over a sampling interval is included in the performance criterion to be optimized. The result is a control command in the form of a finite difference equation over the given time interval.⁴ It results in a filter dynamics by taking the previous control command into account for the synthesis of current control command. Stability of the proposed dynamic control allocation (CA) approach was proved to ensure the control command is bounded at the steady-state. In this study, we extended the results presented in Ref. 4 by adding a two-step dynamic CA term in deriving the control allocation law. Also, the strict equality constraint, between the virtual and actual control inputs, is relaxed in order to construct control command with a smooth profile. The proposed DCA technique is applied to a spacecraft attitude control problem. The sensor noise and/or irregular signals, which are existent in most of spacecraft attitude sensors, can be handled effectively by the proposed approach.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.109.1-109
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• 2001

This paper deals with the path following problem of car-like intelligent mobile robot. A robust sliding mode control law based on time-varying state feedback is performed via Lyapunov method for path tracking of nonholonomic mobile robot with uncertainties. At first, A sliding control law is designed by combing the natural algebraic structure of the chained form system with ideas from sliding mode theory. Then, a robust control law is proposed to impose robustness against bounded uncertainties in path tracking. The problem of estimating the asymptotic stability region and the sliding domain of uncertain sliding mode system with bounded control input is also discussed. The proposed sliding mode control law can ensure the global reaching condition of the uncertain control system.

• Proceedings of the KIEE Conference
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• 1990.07a
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• pp.433-436
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• 1990

An optimal Stabilization technique for a bilinear in duction model is introduced. This technique includes to o parts; the one is an stabilization control using Lyap unov Function which has the form of a sum of linear and quadratic function of the state variables, and the other is an optimal control using the performance index which depends on the choice of the elements of the Ly apunov matrices concerning both the state variables and the input variables. Therefore, induction motor is drived with the shorter transient time of the state variables and with the smaller overshoot of the ones, simulation results are obtained from a digital computer. Experimental ones are obtained from implementation of the optimizing controller using 8086 microprocessor kits and analog circuits are compared.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.1
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• pp.1-9
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• 2013

This paper presents a new control algorithm for dynamic control of a unicycle robot. The unicycle robot motion consists of a pitch that is controlled by an in-wheel motor and a roll that is controlled by a reaction wheel pendulum. The unicycle robot doesn't have any actuator for a yaw axis control, which makes the derivation of the dynamics relatively simple. The Euler-Lagrange equation is applied to derive the dynamic equations of the unicycle robot to implement the dynamic speed control of the unicycle robot. To achieve the real time speed control of the unicycle robot, the sliding mode control and LQ regulator are utilized to guarantee the stability while maintaining the desired speed tracking performance. In the roll controller, the sigmoid-function based sliding mode controller has been adopted to minimize the chattering by the switching function. The LQR controller has been implemented for the pitch control to drive the unicycle robot to follow the desired velocity trajectory in real time using the state variables of pitch angle, angular velocity, angle and angular velocity of the wheel. The control performance of the two control systems form a single dynamic model has been demonstrated by the real experiments.

• 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.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2011.04a
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• pp.273-278
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• 2011

This work presents an active vibration control of a stiffened hull structure using a flexible macro fiber composite (MFC) actuator. As first step, the governing equation of the hull structure is derived in a matrix form and its dynamic characteristics such as natural frequency are obtained via a finite element analysis (FEA). The natural frequencies obtained from the FEA are compared with those determined from experimental measurement. After formulating the control model in a state space representation, an optimal controller is designed in order to attenuate the vibration of the stiffened hull structure. The controller is then empirically realized through dSPACE and control responses are evaluated in time domain.