• The Transactions of the Korean Institute of Electrical Engineers D
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• v.53 no.6
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• pp.395-401
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• 2004

By using an adaptive algorithm, together with an additional dynamic system, this paper proposes a new approach to design of a state observer for a class of uncertain systems. We enlarge the class of linear systems from the canonical form of [1] by proposing an adaptive observer that allows unknown parameters to affect those unmeasured states. The result is based on a recent result which presents a design algorithm for an additional system to replace output derivative measurements with the additional dynamics. A numerical example illustrates the design procedure of the state observer.

• Proceedings of the KIEE Conference
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• 1996.07b
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• pp.1037-1041
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• 1996

Input-output linearization technique in nonlinear control does not guarantee the robustness in the presence of parameter uncertainty or unmodeled dynamics, etc. However, it has been used as an important preliminary step in achieving additional control objectives, for instance, robustness to parameter uncertainty and disturbance attenuation. An indirect adaptive control scheme based on input-output linearization is proposed in this paper. The scheme consists of a Hopfield network for process parameter identification and an adaptive sliding mode controller based on input-output linearization, which steers the system response into a desired configuration. A numerical example is presented for the trajectory tracking of uncertain nonlinear dynamic systems with slowly time-varying parameters.

• Proceedings of the KIEE Conference
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• 1996.11a
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• pp.401-403
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• 1996

In this paper, a new control strategy is presented that combines sliding mode control theory with a neural network. Sliding mode control theory requires the complete knowledge of the dynamics of the controlled system. However, in practice, one often bas only a small number of state measurements. This could be a serious limitation on the practical usefulness of sliding mode control theory. A multilayer neural network is employed to solve this kind of problem. The neural network serves as a compensator without a prior knowledge about the system. The proposed control algorithm is applied to a class of uncertain nonlinear system. The robustness against parameter uncertainty, nonlinearity and external disturbances, and the effectiveness is verified by the simulation results.

• Proceedings of the KIEE Conference
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• 1993.07a
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• pp.345-347
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• 1993

It is known that Feedback linearization has important limitations-the full state has to be measured; no robustness is guaranteed with respect to parameter uncertainty and unmodeled dynamics. In this paper, we construct a nonlinear feedback linearization controller for the system containing uncertain parameters and unknown states, in the case of EMS system with rail vibration. Performance of this controller is demonstrated by computer simulation.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.2
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• pp.409-415
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• 2017

This paper addresses on an linear matrix inequality (LMI) formulation of the robust waypoint tracking problem of large diameter unmanned underwater vehicles (LDUUVs) in the horizontal plane. The interested design issue can be reformed as the robust asymptotic stabilization of the provided error dynamics with respect to the desired yaw angle, surge speed and attitude. Sufficient conditions for its robust asymptotic stabilizability against the hydrodynamic uncertainties are derived in the format of LMI. An example is provided to testify the validity of the proposed theoretical claims.

• Journal of Electrical Engineering and Technology
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• v.11 no.4
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• pp.1012-1019
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• 2016

A robust control intended for a nonholonomic mobile robot is considered to guarantee good tracking a desired trajectory. The main drawbacks of the mobile robot model are the existence of nonholonomic constraints, uncertain system parameters and un-modeled dynamics. in order to overcome these drawbacks, we propose a robust control based on Lyapunov theory associated with sliding-mode control, this solution shows good robustness with respect to parameter variations, measurement errors, noise and guarantees position and velocity tracking. The global asymptotic stability of the overall system is proven theoretically. The simulation results largely confirm the effectiveness of the proposed control.

• Proceedings of the KIEE Conference
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• 2007.07a
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• pp.1716-1717
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• 2007

In this paper, a second order fuzzy sliding mode control that combines with a adaptive self-regulating technique is proposed for a nonlinear system with unknown dynamics. The chattering effect that is a representative disadvantage of the sliding mode control is avoided by using the second order sliding mode control instead of the first order sliding mode control. The proposed sub-controller is composed of the equivalent control that is approximated by an online rule regulation sheme and the hitting control that is used to constrain the states of the sub-system to maintain on the sub-sliding surface and used to guarantee the system robustness. Simulation results are presented to show the effectiveness of the proposed controller

• Proceedings of the KIEE Conference
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• 2001.07d
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• pp.2081-2083
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• 2001

In this paper, without mathematical modeling dynamics, the plant parameter in sliding mode are estimated by the indirect adaptive fuzzy control. Adaptive laws for fuzzy parameters and fuzzy rule structure are established so that the whole system is stable in the sense of Lyapunov stability. The computer simulation results for inverted pendulum system show the performance of the proposed fuzzy sliding mode controller.

• Proceedings of the KIEE Conference
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• 2003.11c
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• pp.468-471
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• 2003

In this paper, a second order sliding mode control that combines with a fuzzy adaptation technique is presented for a nonlinear system with unknown dynamics. The chattering effect that is a representative disadvantage of the sliding mode control is avoided by using the second order sliding mode control instead of the first order sliding mode control. The proposed controller is composed of the equivalent control that is approximated by an online adaptation scheme and the hitting control that is used to constrain the states to maintain on the sub-sliding surface and used to guarantee the system robustness. Simulation results are presented to show the effectiveness of the proposed controller.

• Journal of Power Electronics
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• v.19 no.5
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• pp.1193-1202
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• 2019

A SMPMSM drive system is a typical nonlinear system with time-varying parameters and unmodeled dynamics. The speed outer loop and current inner loop control structures are coupled and coexist with various disturbances, which makes the speed control of SMPMSM drive systems challenging. First, an ultra-local model of a PMSM driving system is established online based on the algebraic estimation method of model-free control. Second, based on the backstepping control framework, model-free adaptive integral backstepping (MF-AIB) control is proposed. This scheme is applied to the permanent magnet synchronous motor (PMSM) drive system of an electric vehicle for the first time. The validity of the proposed control scheme is verified by system simulations and experimental results obtained from a SMPMSM drive system bench test.