• Journal of applied mathematics & informatics
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• v.28 no.5_6
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• pp.1249-1262
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• 2010

An approximate alternating linearization decomposition method, for minimizing the sum of two convex functions with some separable structures, is presented in this paper. It can be viewed as an extension of the method with exact solutions proposed by Kiwiel, Rosa and Ruszczynski(1999). In this paper we use inexact optimal solutions instead of the exact ones that are not easily computed to construct the linear models and get the inexact solutions of both subproblems, and also we prove that the inexact optimal solution tends to proximal point, i.e., the inexact optimal solution tends to optimal solution.

• Proceedings of the KIEE Conference
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• 1998.07b
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• pp.452-454
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• 1998

Asymmetric cylinders are usually used as an actuator of active suspensions. The conventional optimal controller design does not include actuator dynamics as a state. and force controller is needed to track the desired force. But the actuator is not ideal, so performance of an active suspension system is degraded. In this paper, we take account nonlinear actuator dynamics and obtain a linear model using a feedback linearization technique then apply optimal control method. For real time application, gain-scheduling method is used. Effectiveness of proposed method is demonstrated by numerical simulation of 1/4 car model.

• Journal of Institute of Control, Robotics and Systems
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• v.12 no.2
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• pp.93-100
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• 2006

In this paper, a new-type Extended Kalman Filter (EKF) is proposed as a robust nonlinear filter for a stochastic nonlinear system. The original EKF is widely used for various nonlinear system applications. But it is fragile to its estimation errors because they give rise to linearization errors that affect the system mode1 as the modeling errors. The linearization errors are nonlinear functions of the estimation errors therefore it is very difficult to obtain the accurate error covariance of the EKF using the linear form. The inaccurately estimated error covariance hinders the EKF from being a sub-optimal estimator. The proposed filter tries to obtain the upper bound of the error covariance tolerating the uncertainty of the error covariance instead of trying to obtain the accurate one. It treats the linearization errors as uncertain modeling errors that can be handled by the robust linear filtering. In order to be more robust to the estimation errors than the original EKF, the proposed filter minimizes the upper bound like the robust linear filter that is applied to the linear model with uncertainty. The in-flight alignment problem of the inertial navigation system with GPS position measurements is a good example that the proposed robust filter is applicable to. The simulation results show the efficiency of the proposed filter in the robustness to initial estimation errors of the filter.

• Journal of IKEEE
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• v.22 no.1
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• pp.110-120
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• 2018

In this paper, we apply the input-output linearization technique to tracking the follow-up trajectory r(t) in the ball-beam system. There exist system disturbance and various uncertainties, the conventional input-output linearization based control yields some noticeable errors in tracking performance. As a result, a new robust control technique for the uncertainty of the system was proposed and its improved performance verified through simulation and experimental results. So, more realistic system model is obtained with unmatched uncertainties and disturbance. Then, in order to improve the control performance, a new optimal bang-bang control input is additionally added.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1228-1233
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• 2005

In this paper, we present a new guidance law for a reusable launch vehicle (RLV) that lands vertically after reentry. In our past studies, a guidance law was developed for a vertical/soft landing to a target point. The guidance law, which is analytically obtained, can regenerate a trajectory against disturbances because it is expressed in the form of state feedback. However, the guidance law does not necessarily guarantee a vertical/soft landing when a dynamical system such as an RLV includes a nonlinear phenomenon owing to the atmosphere of the earth. In this study, we introduce a design of the guidance law for a nonlinear system to achieve a vertical/soft landing on the ground using the exact linearization method and solving the two-point boundary-value problem for the derived linear system. Numerical simulation confirmed the validity of the proposed guidance law for an RLV in an atmospheric environment.

• The Transactions of the Korean Institute of Power Electronics
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• v.7 no.4
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• pp.384-394
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• 2002

In this paper, a new control strategy is proposed to improve the quality of the welding products. The conventional nonlinear power control system of spot welders is linearized using nonlinear feedback linearization technique based on differential geometry theory. An evolution strategy(ES) geometry is used to find optimal gain of PI controllers. It tries to find out the optimal control parameters by imitating the natural evolution. Some Simulation and experimental results show that the proposed variable power control system using ES algorithm has better dynamic performances than the conventional one.

• Journal of Institute of Control, Robotics and Systems
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• v.5 no.5
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• pp.630-639
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• 1999

To achieve fast loading and unloading of containers from a container ship, quick suppression of the remaining sway motion of the container at the end of each trolley stroke is crucial. Due to the pendulum motion of the container and disturbances like sind, residual sway always exists at the end of trolley movement. In this paper, the sway-control problem of a container crane is investigated. A two-stage control is proposed. The first stage is a time optimal controlfor the purpose of fast trolley traveling. The second stage is a nonlinear control for the quick suppression of residual sway, which starts right after the first stage while lowering the container. The nonlinear control is investigated in the perspective of controlling an underatuated mechanical system, which combines partial feedback linearization to account for the known nonlinearities as much as possible, and variable structure control to account for the unmodeled dynamics and disturbances. Simulation and experimental results are provided.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 1998.10a
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• pp.159-165
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• 1998

In this paper the sway-control problem of a container crane is investigated. The control loop is divided into two stages. The first stage is a modified time optimal control for trolley traversing. The velocity command for trolley traversing consists of three components ; a reference velocity and two feedback signals for compensating the deviations of trolley and sway angle from their desired trajectories. For trolley's exact positioning the trolley dynamics is identified via an error equation identifier structure. The second stage is a nonlinear residual sway control that starts at the end of first stage. The control design for the second stage is investigated from the perspective of controling an underactuated system, and the control law combines the feedback linearization and variable structure control.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.75.5-75
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• 2001

In this paper, we study design of a ILQ(Inverse Linear Quadratic optimal control) looper control system for hot strip mills. The looper which is placed between stands plays an important role in controlling strip width by regulating strip tension variation generated from the velocity difference of main work rolls. A Looper servo controller is designed by ILQ control theory which is an inverse problem of LQ(Linear Quadratic optimal control) control. The mathematical model for looper system is obtained by Taylor´s linearization of nonlinear differential equations. Then we designed linear controller for linearization model by using the ILQ control algorithm. Thereafter this controller is applied to the nonlinear model for model identification. As a result, we show the controller´s robustness for the model error, external disturbance and sensor noise.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.40 no.9
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• pp.929-936
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• 1991

An estimator for a discrete nonlinear system is derived in the sense of minimum mean square error. An optimal estimator for nonlinear system is very difficult to find and it will be infinite dimensional even if it is found. It has been known that the statistical linearization technique makes it possible to obtain a finite dimensional estimator. In this paper, the procedure of its derivation using the statistical linearization technique that gives an exact mean and variance information is introduced in the sense of minimum mean square error. The derived estimator cannot be clainmed to be globally optimal estimator because it uses the Gaussian assumption to the non-Gaussian distributed nonlinear output. However, the proposed filter exhibits a better performance compared to extended Kalman filter. Simulation results of a simple example present the improvement of the proposed filter in convergent property over the extended Kalman filter.