• The Transactions of the Korean Institute of Electrical Engineers P
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• v.67 no.4
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• pp.175-182
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• 2018

In recent years, micro-grid has been widely focused on the fields of renewal energy systems. This paper proposes a novel robust power converter control against arbitrary electric load changes for islanded micro-grid topology. First, we provide a state-space representation of our micro-grid model including power converter and electric load circuit. And then a state feedback control method is applied to construct a nominal control framework. Next, we propose a robust adaptive control law to enhance a control performance against unexpected load perturbation. In addition, we analytically investigate a passivity property for the micro-grid model and carry out computer simulation to demonstrate superiority and reliability of the proposed control methodology.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2003.10a
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• pp.186-194
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• 2003

This paper proposes a combined controller frame of the adaptive robust control(ARC) and the sliding mode control(SMC) for the trajectory tracking control of the excavator to preserve the advantages of the both methods while overcoming their drawbacks, namely, asymptotic stability of adaptive system fir parametric uncertainties and guaranteed transient performance of sliding mode control for both parametric uncertainties and external disturbance. The suggested control technique is applied for the tracking of a straight-line motion of end-effector of manipulators, and through computer simulations, its trajectory tracking performances and the robustness to payload variation and uncertainties are illustrated.

• Journal of the Korean Institute of Intelligent Systems
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• v.12 no.6
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• pp.554-558
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• 2002

In this paper, we propose a robust indirect adaptive fuzzy state feedback regulator based on Takagi-Sugeno fuzzy model. The proposed adaptive fuzzy regulator is less sensitive to singularity than the conventional one based on the feedback linearization method. Furthermore, the proposed control method is applicable to not only plants with a perfect model but also plants with an imperfect model, which causes uncertainties. We verify the global stability of the proposed method by using Lyapunov method. In order to support the achievement, the application of the proposed adaptive fuzzy regulator to the control of a nonlinear system under the external disturbance is presented and the performance was verified by some simulation result.

• International Journal of Aeronautical and Space Sciences
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• v.11 no.4
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• pp.285-302
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• 2010

Active aeroelastic control is an emerging technology aimed at providing solutions to structural systems that under the action of aerodynamic loads are prone to instability and catastrophic failures, and to oscillations that can yield structural failure by fatigue. The purpose of the aeroelastic control among others is to alleviate and even suppress the vibrations appearing in the flight vehicle subcritical flight regimes, to expand its flight envelope by increasing the flutter speed, and to enhance the post-flutter behavior usually characterized by the presence of limit cycle oscillations. Recently adaptive and robust control strategies have demonstrated their superiority to classical feedback strategies. This review paper discusses the latest development on the topic by the authors. First, the available control techniques with focus on adaptive control schemes are reviewed, then the attention is focused on the advanced single-input and multi-input multi-output adaptive feedback control strategies developed for lifting surfaces operating at subsonic and supersonic flight speeds. A number of concepts involving various adaptive control methodologies, as well as results obtained with such controls are presented. Emphasis is placed on theoretical and numerical results obtained with the various control strategies.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.5
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• pp.326-331
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• 2016

This paper presents a novel robust adaptive AC8B exciter system against synchronous generators for ships. A PID (proportional integral derivative) control framework, which is a part of the AC8B exciter system, is simply composed of nominal and auxiliary control configurations. For selecting these proper parameter values, the former is conventionally chosen based on the experience and knowledge of experts, and the latter is optimally estimated via a neural networks optimization procedure. Additionally, we propose an online parameter learning-based auxiliary control to practically cope with deterioration of control performance owing to uncertainty in electric generator systems. Such a control mechanism ensures the robustness and adaptability of an AC8B exciter to enhance control performance in real-time implementation. We carried out simulation experiments to test the reliability of the proposed robust adaptive AC8B exciter system and prove its superiority through a comparative study in which a conventional PID control-based AC8B exciter system is similarly applied to our simulation experiments under the same simulation scenarios.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2004.10a
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• pp.193-200
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• 2004

In this paper, it is presented a new scheme of adaptive-neuro control system to implement real-time control of robot manipulator. Unlike the well-established theory for the adaptive control of linear systems, there exists relatively little general theory for the adaptive control of nonlinear systems. Adaptive control technique is essential for providing a stable and robust performance for application of robot control. The proposed neuro control algorithm is one of learning a model based error back-propagation scheme using Lyapunov stability analysis method. Through simulation, the proposed adaptive-neuro control scheme is proved to be a efficient control technique for real-time control of robot system using DSPs.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.11
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• pp.2139-2146
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• 2011

In this paper, a robust adaptive controller is proposed for trajectory tracking of robot manipulators with the unknown friction coefficient and bounded disturbance. A new adaptive control law is developed based on sliding mode and derived from the Lyapunov stability analysis. The introduction of a boundary layer solves the problem of chattering. The proposed adaptive controller is globally asymptotically stable and guarantees zero steady state error for joint positions. The estimated friction coefficients can also approach the actual coefficients asymptotically. A simulation example is provided to demonstrate the performance of the proposed algorithm.

• Journal of the Korean Society for Precision Engineering
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• v.25 no.12
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• pp.89-99
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• 2008

In this paper, the position tracking control problem of the servo system with nonlinear dynamic friction is issued. The nonlinear dynamic friction contains a directly immeasurable friction state variable and the uncertainty caused by incomplete parameter modeling and its variations. In order to provide the efficient solution to these control problems, we propose the composite control scheme, which consists of the robust friction state observer, the FNN approximator and the approximation error estimator with sliding mode control. In first, the sliding mode controller and the robust friction state observer is designed to estimate the unknown internal state of the LuGre friction model. Next, the FNN estimator is adopted to approximate the unknown lumped friction uncertainty. Finally, the adaptive approximation error estimator is designed to compensate the approximation error of the FNN estimator. Some simulations and experiments on the servo system assembled with ball-screw and DC servo motor are presented. Results show the remarkable performance of the proposed control scheme. The robust friction state observer can successfully identify immeasurable friction state and the FNN estimator and adaptive approximation error estimator give the robustness to the proposed control scheme against the uncertainty of the friction parameters.

• Journal of the Korean Society for Precision Engineering
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• v.12 no.4
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• pp.55-66
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• 1995

This paper presents an explicit pole-assignment adaptive servocontrol shceme and its application to cutting force regulation for feedrate maximization. The controller structure of the suggested adaptive control scheme is based on robust control theory. This controller structure is then combined with an on-line model estimation algorithm. The whole scheme is applied to a milling process control. The results of real time cutting experimental studies show that the asymptotic regulation of milling peak cutting forces can be achieved with robust- ness against the time varying perturbations to the process model parameters, which are caused by nonlinear cutting dynamics.

• Proceedings of the KIEE Conference
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• 2015.07a
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• pp.649-651
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• 2015

This paper describes a robust adaptive sliding mode control (RASMC) for torque ripple minimization of switched reluctance motor (SRM) using it in automotive application. The objective is to control effort smoothness while the system is under perturbations by unstructured uncertainties, unknown parameters and external disturbances. The control algorithm employs an adaptive approach to remove the need for prior knowledge within the bound of perturbations. This is suitable for tackling the chattering problem in the sliding motion of sliding mode control method. The algorithm then incorporates modifications in order to build a chattering-free modified robust adaptive sliding mode control using Lyapunov stability theory.