• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2001년도 ICCAS
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• pp.37.2-37
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• 2001

This paper addresses the robust adaptive output feedback tracking for nonlinear systems under disturbances whose bounds are unknown. A new algorithm is proposed for estimation of unknown bounds and adaptive control of the uncertain nonlinear systems. The State estimation is solved using K-filters, together with the construction of a bound of an error in the state estimation due to the perturbation of the disturbance. Tuning functions are used to estimate unknown system parameters without overparametrization. The proposed control algorithm ensures that the out put tracking error converges to a residual set which can be arbitrarily small, while maintaining the boundedness of all other variables. A simulation shows the effectiveness of the proposed approach

• 전력전자학회:학술대회논문집
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• 전력전자학회 2004년도 전력전자학술대회 논문집(2)
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• pp.738-741
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• 2004

The overall performance of AC servo system is greatly affected by the uncertainties of unpredictable mechanical parameter variations and external load disturbances. Therefore, to compensate this problem, it is necessary to know different parameters and load disturbances subjected to position/speed control. This paper proposes an online identification method of mechanical parameters/load disturbances for AC servo system using Support Vector Regression (SVR). The proposed methodology advocates analytic parameter regression directly from the training data, rather than adaptive controller and observer approaches commonly used in motion control applications. The experimental results demonstrate that the proposed SVR algorithm is appropriate for control of unknown servo systems even with large measurement noise.

• 전력전자학회논문지
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• 제10권5호
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• pp.468-480
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• 2005

서보 시스템의 전체 제어 성능은 기계적 상수의 변화와 부하 토크의 영향을 크게 받는다. 그러므로 서보 시스템의 성능을 향상시키기 위해서는 기계적 상수와 부하 토크를 정확히 알 필요가 있다. 본 논문에서는 Support Vector Regression(SVR)을 이용한 기계적 상수와 부하 토크 추정 알고리즘을 제안한다. 실험 결과는 제안된 SVR 알고리즘이 서보 시스템의 기계적 상수와 부하 토크를 정확하게 추정하고 있음을 보여준다.

• Journal of the Korean Statistical Society
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• 제14권2호
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• pp.95-99
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• 1985

In this paper, Bayesian analysiss of the general linear econometric model is carried out by using a multinomal prior for the vector of unknown regression coefficents and a half-normal prior for the standard deviation of the disturbances.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1991년도 하계학술대회 논문집
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• pp.670-677
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• 1991

All models of dynamical systems invariably have some measure of uncertainties associated with some of their dynamics. The recent approaches to establish robustness of stabilizing feedback control against the possible uncertainties have a serious limitation, that is, their applicability only to the systems that satisfy the matching conditions. Such conditions are rarely met in general applications. If a particular system satisfies the matching conditions, the addition of an actuator will destroy the satisfaction of such conditions. In this paper, we develop robust control algorithm for uncertain multivariable systems in which the matching conditions are not necessarily met. In order to eliminate an influence over partial state variables due to unknown constant disturbances we perform the appropriate block-decomposition for a given system. Functional observers are introduced to estimate the unknown constant disturbances. The sliding mode controller is designed in such a way that the partial state variables in the state-space are directed towards switching surfaces and regulated to the origin asymptotically. Numerical examples are discussed as illustrations.

• 제어로봇시스템학회논문지
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• 제8권12호
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• pp.1023-1030
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• 2002

Since the dynamics of autonomous underwater vehicles (AUVs) are highly nonlinear and their hydrodynamic coefficients vary with different vehicle's operating conditions, high performance control systems of AUVs are needed to have the capacities of teaming and adapting to the variations of the vehicle's dynamics. In this paper, a linearly parameterized neural network (LPNN) is used to approximate the uncertainties of the vehicle dynamics, where the basis function vector of the network is constructed according to the vehicle's physical properties. The network's reconstruction errors and the disturbances in the vehicle dynamics are assumed be bounded although the bound may be unknown. To attenuate this unknown bounded uncertainty, a certain estimation scheme for this unknown bound is introduced combined with a sliding mode scheme. The proposed controller is proven to guarantee that all signals in the closed-loop system are uniformly ultimately bounded (UUB). Numerical simulation studies are performed to illustrate the effectiveness of the proposed control scheme.

• Transactions on Control, Automation and Systems Engineering
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• 제3권2호
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• pp.71-76
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• 2001

This paper deals with an estimation method for sideslip angle by using an unknown disturbance observation technique in 4WS passenger car systems. Firstly, a 4WS vehicle model with 3DOF is derived under the constant velocity and same tyres properties. The vehicle dynamics is transformed into the linear state space model with considering the external disturbances. Secondly, and unknown disturbance observer is introduced and its property which estimating the states of system without any disturbance information is shown. Lastly, the estimated sideslip angle of the 4WS vehicle system is verified through numerical simulation.

• 전기학회논문지
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• 제65권4호
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• pp.652-658
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• 2016

In practical control systems differences between nominal and real systems arise from internal uncertainties and/or external disturbances. This paper presents a model-based low-order disturbance observer for a sinusoidal disturbance with unknown constant offset. By using the disturbance model of a biased harmonic signal, the proposed method can successfully estimate the biased sinusoidal disturbance with unknown amplitude and phase but known frequency. At the first stage of the observer design, a model-based disturbance observer is designed when all the system states are measurable. Next, a sufficient condition is presented for the proposed observer to estimate the sinusoidal disturbance with a minimal-order additional dynamics using only output measurement. Comparative computer simulations are performed to test the performance of the proposed method. The simulation results show the enhanced performance of the proposed disturbance observer.

• 제어로봇시스템학회논문지
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• 제7권7호
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• pp.605-613
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• 2001

In this paper, we design a robust adaptive controller for a nonlinear system with uncertainties to be rejected via disturbance adaptation law. The nonlinear system considered has unknown nonlinear functions being influenced by external disturbance. The upper bound of unknown nonlinear functions at each time is estimated by using a disturbance adaptation law. The estimated nonlinear functions are used to design a stabilizing function a control input. Tuning function is used to estimates unknown system parameter without overparametrization. A set-point regulation error converges to a residual set close to zero asymptotically. The effectiveness of the proposed controller is investigated by computer simulation.

• Journal of Electrical Engineering and Technology
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• 제11권6호
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• pp.1787-1792
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• 2016

Previous walking pattern generation methods could generate walking patterns that allow only straight walking on flat and uneven terrain. They were unable to generate modifiable walking patterns whereby the sagittal and lateral step lengths and walking direction can be changed at every footstep. This paper proposes a novel walking pattern generation method to realize modifiable walking of humanoid robots on unknown uneven terrain. The proposed method employs a walking pattern generator based on the 3-D linear inverted pendulum model (LIPM), which enables a humanoid robot to vary its walking patterns at every footstep. A control strategy for walking on unknown uneven terrain is proposed. Virtual spring-damper (VSD) models are used to compensate for the disturbances that occur between the robot and the terrain when the robot walks on uneven terrain with unknown height. In addition, methods for generating the foot and vertical center of mass (COM) of the 3-D LIPM trajectories are developed to realize stable walking on unknown uneven terrain. The proposed method is implemented on a small-sized humanoid robot platform, DARwIn-OP and its effectiveness is demonstrated experimentally.