• The Transactions of the Korean Institute of Electrical Engineers D
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• v.49 no.1
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• pp.26-32
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• 2000

In this paper, we consider to robust controller design problem for the linear large scale systems with the uncertainties and the time-delays. The considered time-delays are that exist in the state and the input of the subsystems and the interconnected subsystems. And the considered uncertainties are two general types that exist in the system, input and interconnected matrices. Based on the linear matrix inequality(LMI) and Lyapunov theorem, we present sufficient conditions for the existence of a controller that guarantees the asymptotic stability of systems regardless of the uncertainties and the time-delays. Also, the controller can be easily obtained by checking the feasibility of the LMI's. Finally, we show the usefulness of our results by an example.

• International Journal of Precision Engineering and Manufacturing
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• v.3 no.4
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• pp.78-86
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• 2002

In this paper, LMI (Linear Matrix Inequality) based on H$\_$$\infty$/ controller for a lire of sight (LOS) stabilization system. It shows that the proposed controller has more excellent stabilization performance than that of the conventional PI-Lead controller. An H$\_$$\infty$/ control has been also applied to the system for reducing modeling errors and the settling time of the system. The LMI-based H$\_$$\infty$/ controller design is more practical in view of reducing a run-time than Riccati-based H$\_$$\infty$/ controller. This H$\_$$\infty$/ controller is available not only to decrease the gain in PI-Lead control, but also to compensate the identifications for the various uncertain parameters. Therefore, this paper, shows that the proposed LMI-based H$\_$$\infty$/ controller had good disturbance attenuation and reference input tracking performance compared with the control performance of the conventional controller under any real disturbances.

• International Journal of Ocean System Engineering
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• v.1 no.3
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• pp.120-135
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• 2011

This paper proposes a model based trajectory tracking control scheme for under-actuated underwater robotic vehicles. The difficulty in stabilizing a non-linear system using smooth static state feedback law means that the design of a feedback controller for an under-actuated system is somewhat challenging. A necessary condition for the asymptotic stability of an under-actuated vehicle about a single equilibrium is that its gravitational field has nonzero elements corresponding to non-actuated dynamics. To overcome this condition, we propose a continuous time-varying control law based on the direct estimation of vehicle dynamic variables such as inertia, damping and Coriolis & centripetal terms. This can work satisfactorily under commonly encountered uncertainties such as an ocean current and parameter variations. The proposed control law cancels the non-linearities in the vehicle dynamics by introducing non-linear elements in the input side. Knowledge of the bounds on uncertain terms is not required and it is conceptually simple and easy to implement. The controller parameter values are designed using the Taguchi robust design approach and the control law is verified analytically to be robust under uncertainties, including external disturbances and current. A comparison of the controller performance with that of a linear proportional-integral-derivative (PID) controller and sliding mode controller are also provided.

• Journal of the Earthquake Engineering Society of Korea
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• v.15 no.2
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• pp.1-9
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• 2011

An optimal design method for a structural control system considering load variations due to their uncertain characteristics is studied in this paper. The conventional design problem for a control system generally deals with the optimization problem of a structural control system and interaction between the structure and the control device. This study deals with the optimization problem of a load-structure-control system and the more complicated interactions with each other. The problem of finding the load that maximizes the structural responses and the structural control system that minimizes the responses simultaneously is formulated as the min-max problem. In order to effectively obtain the optimal design variables, a co-evolutionary algorithm is adopted and, as a result, an optimal design procedure for the linear structural control system with uncertain dynamic characteristics is proposed. The example design and simulated results of an earthquake excited structure validates the proposed method.

• 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 Institute of Control, Robotics and Systems
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• v.6 no.9
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• pp.758-767
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• 2000

The properties of linear time-varying(LTV) systems vary because of the time-varying property of plant parameters. The generalized controller design method for linear time-varying systems does not exit because the analytic soultion of dynamic equation has not been found yet. Hence, to design a controller for LTV systems, the robust control methods for uncertain LTI systems which are the approximation of LTV systems have been generally ised omstead. However, these methods are not sufficient to reflect the fast dynamics of the original time-varying systems such as missiles and supersonic aircraft. In general, both the performance and the robustness of the control system which is designed with these are not satisfactory. In addition, since a better model will give the more robustness to the controlled system, a gain scheduling technique based on LTI controller design methods has been uesd to solve time problem. Therefore, we propose a new gain scheduled QFT method for LTV systems based on neural networks in this paper. The gain scheduled QFT involves gain dcheduling procedured which are the first trial for QFT and are well suited consideration of the properties of the existing QFT method. The proposed method is illustrated by a numerical example.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.3
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• pp.211-217
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• 2011

This paper proposes a quasi-optimal linear DOA (Direction-of-Arrival) estimator which is necessary for the development of a real-time robot auditory system tracking moving acoustic source. It is well known that the use of conventional nonlinear filtering schemes may result in the severe performance degradation of DOA estimation and not be preferable for real-time implementation. These are mainly due to the inherent nonlinearity of the acoustic signal model used for DOA estimation. This motivates us to consider a new uncertain linear acoustic signal model based on the linear prediction relation of a noisy sinusoid. Using the suggested measurement model, it is shown that the resultant DOA estimation problem is cast into the NCRKF (Non-Conservative Robust Kalman Filtering) problem [12]. NCRKF-based DOA estimator provides reliable DOA estimates of a fast moving acoustic source in spite of using the noise-corrupted measurement matrix in the filter recursion and, as well, it is suitable for real-time implementation because of its linear recursive filter structure. The computational efficiency and DOA estimation performance of the proposed method are evaluated through the computer simulations.

• 제어로봇시스템학회:학술대회논문집
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• 1986.10a
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• pp.554-559
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• 1986

This paper considers the problem of stabilizing a composite system formed by interconnecting a number of single-input single-output linear continuous systems. The problem is general in the sense that in addition to the standard assumption about the uncertainty of the subsystems, the strength of interconnections is assumed unknown. A method to design a local adaptive feedback control is first presented, and then the resultant closed-loop system is assured to be globally stable. Also, a numerical example is illustrated via computer simulation.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1955-1959
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• 2005

This paper presents a systematic analysis and a simple design of a robust adaptive control law for a class of non linear systems with modeling errors and a time-delay input. The theory for designing a robust adaptive control law based on input- output feedback linearization of non linear systems with uncertainties and a time-delay in the manipulated input by the approach of parameterized state feedback control is presented. The main advantage of this method is that the parameterized state feedback control law can effectively suppress the effect of the most parts of nonlinearities, including system uncertainties and time-delay input in the pp-coupling perturbation form and the relative order of non linear systems is not limited.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 1993.04a
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• pp.135-140
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• 1993

The optimum weight design of structure is to determine the combination of structural members which minimize the weight of structures and satisfy design conditions as well. Since most of loads and design variables considered in structural design have uncertain natures, the reliability-based optimization techniques need to be developed. The aim of this study is to estabilish the general algorithm for the minimum weight design of transmission tower structure system with reliability constraints. The sequential linear programming method is used to solve non-linear minimization problems, which converts original non-linear programming problems to sequential linear programming problems. The optimal solutions are produced for various reliability levels such as reliability levels inherent in current standard transmission tower cross-section and optimal transmission tower cross-section obtained with constraints of current design criteria as well as selected target reliability index. The optimal transmission towers satisfying reliability constraints sustain consistent reliability levels on all members. Consequently, more balanced optimum designs are accomplished with less structural weight than traditional designs dealing with deterministic design criteria.