• Transactions on Control, Automation and Systems Engineering
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• v.1 no.2
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• pp.134-140
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• 1999

The robust generalized H2 filtering problem for a class of discrete time uncertain linear systems satisfying the sum quadratic constraints(SQCs) is considered. The objective of this paper is to develop robust stability condition using SQCs and design a robust generalized Ha filter to take place of the existing robust Kalman filter. The robust generalized H2 filter is designed based on newly derived robust stability condition. The robust generalized Ha filter bounds the energy to peak gain from the energy bounded exogenous disturbances to the estimation errors under the given positive scalar ${\gamma}$. Unlike the robust Lalman filter, it does not require any spectral assumptions about the exogenous disturbances . Therefore the robust generalized H2 filter can be considered as a deterministic formulation of the robust Kalman filter. Moreover, the variance of the estimation error obtained by the proposed filter is lower than that by the existing robust Kalman filter. The robustness of the robust generalized H2 filter against the uncertainty and the exogenous signal is illustrated by a simple numerical example.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.11
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• pp.5194-5201
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• 2011

In this paper, an adaptive nonlinear friction compensation scheme for second-order nonlinear mechanical system with a partially known nonlinear dynamic friction is proposed to achieve asymptotic position and velocity tracking in the absence of disturbances and modeling errors. It is also shown that even with disturbances and modeling errors, in contrast to existing other adaptive control schemes, by proper adjustment of design parameters, reduced error bounds on position and velocity tracking can be achieved.

• International Journal of Control, Automation, and Systems
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• v.3 no.3
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• pp.387-396
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• 2005

The Rotational/Translational Actuator (RTAC) benchmark problem considers a fourth-order dynamical system involving the nonlinear interaction of a translational oscillator and an eccentric rotational proof mass. This problem has been posed to investigate the utility of a rotational actuator for stabilizing translational motion. In order to experimentally implement any of the model-based controllers proposed in the literature, the values of model parameters are required which are generally difficult to determine rigorously. In this paper, an approach to the least-squares estimation of the parameters of a system is formulated and practically applied to the RTAC system. On the other hand, this paper shows how to model a nonlinear system as a linear uncertain system via nonparametric system identification, in order to provide the information required for linear robust $H_\infty$ control design. This method is also applied to the RTAC system, which demonstrates severe nonlinearities, due to the coupling from the rotational motion to the translational motion. Experimental results confirm that this approach can effectively condense the whole nonlinearities, uncertainties, and disturbances within the system into a favorable perturbation block.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.46 no.2
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• pp.7-14
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• 2009

In this paper we consider the problem of global finite-time stabilization for a class of uncertain nonlinear systems which include uncertainties. The uncertainties are time-varying disturbances or parameters belong to a known compact set. The proposed design method is based on backstepping and dynamic exponent scaling using an augmented dynamics, from which, a dynamic smooth feedback controller is derived. The finite-time stability of the closed-loop system and boundedness of the controller are preyed by the finite-time Lyapunov stability theory and a new notion 'degree indicator'.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.7
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• pp.1289-1294
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• 2010

In this paper, a new discrete integral static output feedback variable structure controller based on the a new integral dynamic-type sliding surface and output feedback discrete version of the disturbance observer is suggested for the control of uncertain linear systems. The reaching phase is completely removed by introducing a new proposed integral dynamic-type sliding surface. The output feedback discrete version of disturbance observer is presented for effective compensation of uncertainties and disturbance. A corresponding control with disturbance compensation is selected to guarantee the quasi sliding mode on the predetermined integral dynamic-type sliding surface for guaranteeing the designed output in the integral dynamic-type sliding surface from any initial condition for all the parameter variations and disturbances. Using discrete Lyapunov function, the closed loop stability and the existence condition of the quasi sliding mode is proved. Finally, an illustrative example is presented to show the effectiveness of the algorithm.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.2
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• pp.316-321
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• 2007

[ $H{\infty}$ ] controller, which shows robustness for disturbances and noises, can not be used in the case of uncertain system parameters. Even if the $H{\infty}$ controller can be designed for the parameter uncertain system, its performance can be deteriorated. Therefore, in this paper, the robustness of $H{\infty}$ controller is improved by using the SMC(Sliding Mode Control). The LMI based $H{\infty}$ controller is designed first and then SMC controller is added.

• Journal of IKEEE
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• v.23 no.2
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• pp.716-721
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• 2019

A novel switching differentiator-based backstepping controller for uncertain pure-feedback nonlinear systems is proposed. Using asymptotically convergent switching differentiator, time-derivatives of the virtual controls are directly estimated in every backstepping design steps. As a result, the control law has an extremely simple form and asymptotical stability of the tracking error is guaranteed regardless of parametric or unstructured uncertainties and unmatched disturbances in the considered system. It is required no universal approximators such as neural networks or fuzzy logic systems that are adaptively tuned online to cope with system uncertainties. Simulation results show the simplicity and performance of the proposed controller.

• International Journal of Control, Automation, and Systems
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• v.3 no.2
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• pp.225-235
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• 2005

This paper presents the robust stability analysis and design methodology of the fuzzy feedback linearization control systems. Uncertainty and disturbances with known bounds are assumed to be included in the Takagi-Sugeno (TS) fuzzy models representing the nonlinear plants. $L_2$ robust stability of the closed system is analyzed by casting the systems into the diagonal norm bounded linear differential inclusions (DNLDI) formulation. Based on the linear matrix inequality (LMI) optimization programming, a numerical method for finding the maximum stable ranges of the fuzzy feedback linearization control gains is also proposed. To verify the effectiveness of the proposed scheme, the robust stability analysis and control design examples are given.

• Journal of Mechanical Science and Technology
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• v.15 no.4
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• pp.433-440
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• 2001

A new design of the sliding mode control is proposed for the uncertain linear time-varying second order system. The proposed control drives system states to the target point in the minimum time with specified ranges of parametric uncertainties and disturbances. One of the advantages of the proposed control scheme is that the control inputs do not go beyond saturation limits of the actuators. The other advantage is that the minimum arrival time and the acceleration of the second order actuators system can be estimated with given parametric bounds and can be expressed in the closed from; conversely, the designer can select actuators based on the condition of the minimum arrival time to the target point. The superior performance of the proposed control scheme to other sliding mode controllers is validated by computer simulations.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10a
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• pp.299-302
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• 1996

A control algorithm is proposed for nonlinear multi-input multi-output(MIMO) batch processes by combining quadratic iterative learning control(Q-ILC) with model predictive control(MPC). Both controls are designed based on output feedback and Kalman filter is incorporated for state estimation. Novelty of the proposed algorithm lies in the facts that, unlike feedback-only control, unknown sustained disturbances which are repeated over batches can be completely rejected and asymptotically perfect tracking is possible for zero random disturbance case even with uncertain process model.