• Proceedings of the KIEE Conference
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• 1998.11b
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• pp.420-422
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• 1998

In this paper, we propose a position-speed control of servo system with a state estimator. And also we utilized two mass modelling in order to deals with real system accurately. The overall control system consists of two parts: the position-speed controller and state estimator. The Kalman filter applied as state - feedback controller is an optimal state estimator applied to a dynamic system that involves random perturbations and gives a linear,unbiased and minimun error variance recursive algorithm to estimate the unknown state optimally. Therefore we consider the error problem about the servo system modelling, the measurement noise at low-speed ranges a stochastic system, and implement a optimal state observer. Performance of the proposed state estimator are demonstrated by computer simulations.

• Journal of Drive and Control
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• v.5 no.2
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• pp.32-36
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• 2008

• 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.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.3
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• pp.458-465
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• 2008

In this paper, we propose a non-fragile guaranteed cost controller design method for uncertain linear systems with constant delyas in state. The norm bounded and time-varying uncertainties are subjected to system and controller design matrices. A quadratic cost function is considered as the performance measure for the system. Based on the Lyapunov method, an LMI(Linear Matrix Inequality) optimization problem is established to design the controller which uses information of delayed state and minimizes the upper bound of the quadratic cost function for all admissible system uncertainties and controller gain variations. Numerical examples show the effectiveness of the proposed method.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.569-572
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• 1996

Explicit state-space formulate for an H$_{.inf}$ based two-degrees-of-freedom robust controller are derived in discrete-time. The controller provides robust stability against coprime factor uncertainty, and a degree of robust performance in the sense of making the closed-loop system match a prespecified reference model. It is shown that the controller consists of a plant observer, the chosen reference model, and a generalized state feedback law associated with the plant and model states. The controller structure is shown to be relatively simple and thus may reduce the computational load on the digital control processor.

• 제어로봇시스템학회:학술대회논문집
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• 1990.10b
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• pp.963-968
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• 1990

An iterative learning control scheme for tracking control of a class of uncertain nonlinear systems is presented. By introducing a model reference adaptive controller in the learning control structure, it is possible to achieve zero tracking of unknown system even when the upperbound of uncertainty in system dynamics is not known apriori. The adaptive controller pull the state of the system to the state of reference model via control gain adaptation at each iteration, while the learning controller attracts the model state to the desired one by synthesizing a suitable control input along with iteration numbers. In the controller role transition from the adaptive to the learning controller takes place in gradually as learning proceeds. Another feature of this control scheme is that robustness to bounded input disturbances is guaranteed by the linear controller in the feedback loop of the learning control scheme. In addition, since the proposed controller does not require any knowledge of the dynamic parameters of the system, it is flexible under uncertain environments. With these facts, computational easiness makes the learning scheme more feasible. Computer simulation results for the dynamic control of a two-axis robot manipulator shows a good performance of the scheme in relatively high speed operation of trajectory tracking.

• The Transactions of the Korean Institute of Power Electronics
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• v.25 no.6
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• pp.442-450
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• 2020

A small-signal modeling approach for a three-level boost (TLB) converter and a design methodology for a double-loop controller are proposed in this study. Conventional modeling of TLB converters involves three state variables. Moreover, TLB converters have two operation modes depending on the duty ratio. Consequently, complex mathematical calculations are required for controller design. This study proposes a simple system modeling method that uses two state variables, unlike previous methods that require three state variables. Analysis shows that the transfer functions of the two operation modes can be expressed as identical equations. This condition means that the linear feedback controller can be applied to all operational ranges, that is, for full duty ratios. The design method for a double-loop controller using a PI controller is presented in step-by-step sequences. Simulation and experimental verifications are conducted to verify the effectiveness of the small-signal analysis and control system design.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.64 no.2
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• pp.297-303
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• 2015

We propose a disturbance observer(DOB) based feedback linearization control to improve position tracking performance in the presence of disturbance. The proposed method consists of a disturbance observer and a feedback linearization controller. The disturbance observer is designed to estimate the load force disturbance in electro-hydraulic systems. An auxiliary state variable is proposed in order to avoid amplification of the measurement noises in the disturbance observer. Using the estimated disturbance enables the Electro-hydraulic servo systems(EHS) dynamics to be changed into feedback linearization from. In order to compensate for the disturbance and to track the desired position, the feedback linearization based controller is proposed. The proposed method has a simple structure which can easily be implemented in practice. As a result, the proposed method improves the position tracking performance in the presence of disturbance. Its performance is validated via simulations.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.42 no.6
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• pp.9-14
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• 2005

In this paper, we consider the synthesis of non-fragile $H_{\infty}$ state feedback controllers for singular systems and static state feedback controller with multiplicative uncertainty. The sufficient condition of controller existence, the design method of non-fragile $H_{\infty}$ controller, and the measure of non-fragility in controller are presented via LMI(linear matrix inequality) technique. Also, the sufficient condition can be rewritten as LMI form in terms of transformed variables through singular value decomposition, some changes of variables, and Schur complements. Therefore, the obtained non-fragile $H_{\infty}$ controller guarantees the asymptotic stability and disturbance attenuation of the closed loop singular systems within a prescribed degree. Moreover, the controller design method can be extended to the problem of robust and non-fragile $H_{\infty}$ controller design method for singular systems with parameter uncertainties. Finally, a numerical example is given to illustrate the design method.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.8
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• pp.731-737
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• 2013

In this paper, we propose an image-based output feedback robust controller of robot manipulators which have bounded parametric uncertainty. The proposed controller contains an integral action and high-gain observer in order to improve steady state error of joint position and performance deterioration due to measurement errors of joint velocity. The stability of the closed-loop system is proved by Lyapunov approach. The performance of the proposed method is demonstrated by simulations on a 5-link robot manipulators with two degrees of freedom.