• Transactions of the Korean Society of Mechanical Engineers A
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• v.28 no.12
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• pp.1833-1844
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• 2004

A controller is proposed for the robust backstepping control of a class of nonlinear multiple-input multiple-output (MIMO) systems which can be converted to a strict feedback form. The proposed robust backstepping control scheme follows a systematic procedure for the design of control laws and uses time delay estimation (TDE) to estimate the uncertainties such as parameter variations, unknown disturbances, and unmodeled dynamics, etc. The proposed controller can be also applied to nonlinear MIMO systems with unmatched uncertainties. Stability analysis of the closed-loop system which contains the plant and the proposed controller is also studied and hereby a sufficient stability condition for the closed-loop system is proposed. The simulation results show that the control scheme works well with uncertainties and the proposed stability condition is valid. The controller is experimentally verified on a single-link flexible arm to show the effectiveness of the proposed scheme in the complicated systems with uncertainties.

• The Pure and Applied Mathematics
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• v.9 no.1
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• pp.81-90
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• 2002

The least informative (favorable) distributions, minimizing Fisher information for a multivariate location parameter, are derived in the parametric class of the exponential-power spherically symmetric distributions under the following characterizing restrictions; (i) a bounded variance, (ii) a bounded value of a density at the center of symmetry, and (iii) the intersection of these restrictions. In the first two cases, (i) and (ii) respectively, the least informative distributions are the Gaussian and Laplace, respectively. In the latter case (iii) the optimal solution has three branches, with relatively small variances it is the Gaussian, them with intermediate variances. The corresponding robust minimax M-estimators of location are given by the $L_2$-norm, the $L_1$-norm and the $L_{p}$ -norm methods. The properties of the proposed estimators and their adaptive versions ar studied in asymptotics and on finite samples by Monte Carlo.

• Proceedings of the KIEE Conference
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• 1994.07a
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• pp.468-471
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• 1994

This paper presents the digital implementation of an optimal and robust VSS controller with sliding observer. Firstly, a discrete-time VSS control law which enables the system state to move into a sliding sector where the closed-loop system is stable is designed. Then optimal control theory is used to design an optimal sliding sector. Secondly, a sliding observer which provide robust state estimation against model-plant mismatches due to parameter uncertainties is designed for the sampled-data multivariable systems. Finally, modified sliding observer which effectively reduce chattering of state variables in state estimation was proposed. The proposed scheme was applied 10 a two degree of freedom inverted pendulum with passive joint to verify robust motion control. Computer simulation results confirm the viability of the proposed observer-based controller.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.5
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• pp.1011-1016
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• 2011

This paper presents a robust current controller for a surface-mounted permanent magnet synchronous motor(SPMSM) by using a PI observer. The decoupling PI(proportional-integral) controller combined with an additional feed-forward compensation has been used for the current controller. The classical feed-forward compensation using velocity information and system parameters is not expected to achieve a robust performance against parameter uncertainties. This paper has adopted a PI observer for the feed-forward compensation to cope with parameter uncertainties without using velocity information. A simple PI observer has been designed to compensate the disturbances that represent velocity coupled terms and parameter uncertainties. Experimental results as well as computer simulations with 630W SPMSM confirm that the proposed approach can deal with the effects of the disturbance and improve the control performance.

• Proceedings of the KIEE Conference
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• 1997.07a
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• pp.112-114
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• 1997

Recently sensorless PMSM is much studied for the industrial applications and home appliances. Most of sensorless algorithm are based on the motor equations of which coefficients are motor parameters. However, uncertainty of motor parameter effects the accuracy of speed estimation of PMSM. This paper investigates the robust speed control of sensorless PMSM which has robustness to parameter uncertainty or variation. The parameter compensation is performed through PI control of the speed error between the estimated speed and the real speed obtained from the measured current. The proposed algorithm is verified through the experiment.

• Journal of the Korean Society for Precision Engineering
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• v.11 no.6
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• pp.143-157
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• 1994

This paper is concerned with the position control of electrohydraulic servo system under parameter variation. An adaptive sliding mode control which uses the direct parameter estimation scheme, is proposed to design a robust controller for fast and accurate control of the system. It is shown that the adaptive sliding mode control algorithm is robust and effective in attaining fast and accurate position control of system under time-dependent parameter variation. It is also shown experimentally that chattering phenomena in a sliding mode control can significantly be reduced by using boundary layer technique, and that new approach in sliding mode control introducing a term proportional to the distance between the current state and the sliding surface in the control law is effective to obtain fast response and to increase stability of the system. Computer simulation on the dynamic performance of the control system is also presented.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.20 no.3
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• pp.843-849
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• 1996

The least square estimation is used frequently in experimental modal analysis techinque to eliminate noise signals. However, identified modal parameters are sometimes inaccurate, since the least squre estimation is sensitive to noise. In this paper, a new total least squre estimation, which is robust to noise signals, is developed and applied to experimental modal analysis technique such as Prony method and Circle Fit method. Several simulated results show that the proposed method is robuster to noise than conventional method.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.12
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• pp.3055-3070
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• 2013

This paper proposes an improved carrier frequency offset (CFO) and sampling frequency offset (SFO) estimation scheme for orthogonal frequency division multiplexing (OFDM) based broadcasting system with cyclic delay diversity (CDD) antenna. By exploiting a periodic nature of channel transfer function, cyclic delay and pilot pattern with a maximum channel power are carefully chosen, which helps to enable a robust estimation of CFO and SFO against the frequency selectivity of the channel. As a performance measure, a closed-form expression for the achievable mean square error of the proposed scheme is derived and is verified through simulations using the parameters of the digital radio mondiale standard. The comparison results show that the proposed frequency estimator is shown to benefit from properly selected delay parameter and pilot pattern, with a performance better than the existing estimator.

• Industrial Engineering and Management Systems
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• v.1 no.1
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• pp.79-86
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• 2002

This paper proposes a new algorithm for estimating ARMA model parameters. In estimating ARMA model parameters, several methods such as generalized least square method, instrumental variable method have been developed. Among these methods, the utilization of a bootstrap type algorithm is known as one of the effective approach for the estimation, but there are cases that it does not converge. Hence, in this paper, making use of a cross correlation function and utilizing the relation of structural a priori knowledge, a new bootstrap algorithm is developed. By introducing theoretical relations, it became possible to remove terms, which is liable to include much noise. Therefore, this leads to robust parameter estimation. It is shown by numerical examples that using this algorithm, all simulation cases converge while only half cases succeeded with the previous one. As for the calculation time, judging from the fact that we got converged solutions, our proposed method is said to be superior as a whole.

• Proceedings of the KIEE Conference
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• 2003.11c
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• pp.433-436
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• 2003

The estimation of the position and the orientation for the mobile robot constitutes an important problem in mobile robot navigation. Although the odometry can be used to describe the motions of the mobile robots, there inherently exist the gaps between the real robots and the mathematical model, which may be caused by a number of error sources contaminating the encoder outputs. Hence, applying the standard extended Kalman filter for the nominal model is not supposed to give the satisfactory performance. As a solution to this problem, a new robust extended Kalman filter is proposed based on the Krein space approach. We consider the uncertain discrete time nonlinear model of the mobile robot that contains the uncertainties represented as sum quadratic constraints. The proposed robust filter has the merit of being constructed by the same recursive structure as the standard extended Kalman filter and can, therefore, be easily designed to effectively account for the uncertainties. The simulations will be given to verify the robustness against the parameter variation as veil as the reliable performance of the proposed robust filter.