• Journal of Institute of Control, Robotics and Systems
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• v.18 no.4
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• pp.314-320
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• 2012

This paper proposes a new robust motion deblurring filter using the inertial sensor measurements for strapdown image IR applications. With taking the PSF measurement error into account, the motion blurred image is modeled by the linear uncertain state space equation with the noise corrupted measurement matrix and the stochastic parameter uncertainty. This motivates us to solve the motion deblurring problem based on the recently developed robust least squares estimation theory. In order to suppress the ringing effect on the deblurred image, the robust least squares estimator is slightly modified by adoping the ridge-regression concept. Through the computer simulations using the actual IR scenes, it is demonstrated that the proposed algorithm shows superior and reliable motion deblurring performance even in the presence of time-varying motion artifact.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1997.10a
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• pp.199-203
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• 1997

In this paper is proposed a new direct adaptive fuzzy controller that dan ve applied for tracking control of a class of uncertain nonlinear SISO systems. It is shown that, in the presence of the perturbations such as fuzzy approximation error and external disturbance, boundedness of all the signals in the system is ensured, while under the assumption of no perturbations, the stability of the overall system in guaranteed. Also, the concept of persistent excitation in the adaptive fuzzy control systems is introduced to guarantee the convergence and the boundedness of adaptation parameter in the proposed controllers. Simulation example shows the effectiveness of the proposed method in the presence of fuzzy approximation error and external disturbance.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.12 no.1
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• pp.47-52
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• 2012

This paper focuses on discrete-time sliding mode control with SIIM fuzzy adaptive switching gain. The adaptive switching gain is calculated using the simplified indirect inference fuzzy logic. Two fuzzy inputs are the normal distance from the present state trajectory to the switching function and the distance from the present state trajectory to the equilibrium state. The fuzzy output $f_{out}$(k) out f k is used to adjust the speed the adaptation law depending on the location of the state trajectory. The simulation results showed that the proposed method had no chattering in case of uncertain parameter without disturbance. Moreover the convergent rate of the switching gain was faster and more stable even in case of disturbance.

• Journal of Power Electronics
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• v.13 no.5
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• pp.814-828
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• 2013

The LCL resonant inductive power transfer (IPT) system is increasingly used because of its harmonic filtering capabilities, high efficiency at light load, and unity power factor feature. However, the modeling and controller design of this system become extremely difficult because of parameter uncertainty, high-order property, and switching nonlinear property. This paper proposes a frequency and load uncertainty modeling method for the LCL resonant IPT system. By using the linear fractional transformation method, we detach the uncertain part from the system model. A robust control structure with weighting functions is introduced, and a control method using structured singular values is used to enhance the system performance of perturbation rejection and reference tracking. Analysis of the controller performance is provided. The simulation and experimental results verify the robust control method and analysis results. The control method not only guarantees system stability but also improves performance under perturbation.

• Proceedings of the KIEE Conference
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• 1999.07b
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• pp.522-524
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• 1999

This paper addresses the systematic approach to the fuzzy modeling of the class of complex and uncertain nonlinear systems. While the conventional genetic algorithm (GA) only searches the global solution, Virus-Evolutionary Genetic Algorithm(VEGA) can search the global and local optimal solution simultaneously. In the proposed method the parameter and the structure of the fuzzy model are automatically identified at the same time by using VEGA. To show the effectiveness and the feasibility of the proposed method, a numerical example is provided. The performance of the proposed method is compared with that of conventional GA.

• Proceedings of the KIEE Conference
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• 1999.07b
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• pp.592-595
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• 1999

In this paper, we propose a unified method to solve the various robust filtering problem for a class of uncertain discrete time systems. Generally, to solve the robust filtering problem, we must convert the convex optimization problem with uncertainty blocks to the uncertainty free convex optimization problem. To do this, we derive the robust matrix inequality problem. This technique involves using constant scaling parameter which can be optimized by solving a linear matrix inequality problem. Therefore, the robust matrix inequality problem does not conservative. The robust filter can be designed by using this robust matrix inequality problem and by considering its solvability conditions.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10a
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• pp.425-430
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• 1991

For satellite orbit determination, a satellite (K-3H) which is affected by the earth's gravitational field and the earth's atmospheric drag, the sun, and the moon is chosen as a dynamic model. The state vector include orbit parameters, uncertain parameters associated with perturbations and tracking stations. These perturbations include gravitational constant, atmospheric drag, and jonal harmonics due to the earth nonsphericity. Early orbit was obtained with given the predicted orbital parameter of the satellite. And orbit determination, which is applied to Extended Kalman Filter(EKF) for real time implementation , use the observation data which is given by satellite tracking radar system and then orbit estimation is accomplished. As a result, extended sequential estimation algorithm has a fast convergence and also indicate effectiveness for real time operation.

• Journal of applied mathematics & informatics
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• v.20 no.1_2
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• pp.513-522
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• 2006

This paper considers a robust output feedback $H\infty$ controller design method for singular systems with time-varying delay in state and parameter uncertainty in system matrix by an LMI approach and observer based technique, which can be solved efficiently by convex optimization. The sufficient condition for the existence of controller and the controller design method are presented by strict LMI(linear matrix inequality) approach. Since the obtained condition can be expressed as an LMI form, all variables including feedback gain and observer gain can be calculated simultaneously by Schur complement and changes of variables.

• Journal of the Korean Society for Precision Engineering
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• v.18 no.9
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• pp.53-60
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• 2001

This paper presents a position control of a platform at the seaport cargo handling system. After brief description of the operating principles of the cargo handling system, the governing equation of the moving platform is derived. The equation is described in the state space model, and a robust H$_{\infty}$ controller to achieve position tracking of the moving platform. which can carry 200ton of containers, is formulated. In the synthesis of the controller, the weight of the container is treated as uncertain parameter. Both regulating and tracking control responses are analyzed for the loading and unloading procedures of the proposed automatic cargo handling system.

• Proceedings of the Korean Society of Marine Engineers Conference
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• 2006.06a
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• pp.77-78
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• 2006

A mixed method between $H_2\;and\;H_{\infty}$ control are widely applied to systems which has parameter perturbation and uncertain model to obtain an optimal robust controller. Brushless Direct Current (BLDC) motors are widely used for high performance control applications. Conventional PID controller only provides satisfactory performance for set-point regulation. However, with the presence of nonlinearities, uncertainties and perturbations in the system, conventional PID is not sufficient to achieve an optimal robust controller. This paper presents an approach to ease designing a Mixed $H_2/H_{\infty}$ PID controller for controlling speed of Brushless DC motors and the genetic algorithm is used to solve the optimized problems. Numerical results are shown to prove that the performance in the proposed controller is better than that in the optimal PID controller using LQR approach.