• Transactions of the Korean Society of Mechanical Engineers A
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• v.26 no.12
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• pp.2519-2526
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• 2002

A disturbance observer-based vehicle stability controller is proposed in this paper. The lumped disturbance to the vehicle yaw rate dynamics caused by the uncertain factors such as uncertain tire forces and parameters is estimated by the disturbance observer, which is utilized by the robust controller to stabilize the lateral dynamics of the vehicle. The dynamics of the hydraulic actuator is incorporated in the vehicle stability controller design using the model reduction technique. Modular control design methodology is adopted to effectively deal with the mismatched uncertainty. Simulation results indicate that the proposed disturbance observer-based vehicle stability controller can achieve the desired reference tracking performance as well as sufficient level of robustness.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.16 no.3
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• pp.67-73
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• 2002

This paper presents a sliding mode observer and Controller far the state estimation and the dynamic stabilization of the magnetic levitation systems. The proposed striding mode observer is constructed by means of Lyapunov stability theorem to decrease the observer error, and the sliding rode controller is designed by a linear combination of the equivalent and nonlinear control input for the estimated states. The feasibilities of the suggested design method are illustrated with the simulation results.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2004.10a
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• pp.192-196
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• 2004

This paper proposes an alternative observation scheme, T-S fuzzy model based indirect adaptive fuzzy observer. Nonlinear systems are represented by fuzzy models since fuzzy logic systems are universal approximators. In order to estimate the unmeasurable states of a given nonlinear system, T-S fuzzy modeling method is applied to get the dynamics of an observation system. T-S fuzzy system uses the linear combination of the input state variables and the modeling applications of them to various kinds of nonlinear systems can be found. The adaptive fuzzy scheme estimates the parameters comprising the fuzzy model representing the observation system. The proposed indirect adaptive fuzzy observer based on T-S fuzzy model can cope with not only unknown states but also unknown parameters. In the process of deriving adaptive law, the Lyapunov theory and Lipchitz condition are used. To show the performance of the proposed observation method, it is applied to an inverted pendulum on a cart.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.7
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• pp.927-933
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• 2004

This paper proposes an alternative observation scheme, T-S fuzzy model based indirect adaptive fuzzy observer. Nonlinear systems are represented by fuzzy models since fuzzy logic systems are universal approximators. In order to estimate the unmeasurable states of a given nonlinear system, T-S fuzzy modeling method is applied to get the dynamics of an observation system. T-S fuzzy system uses the linear combination of the input state variables and the modeling applications of them to various kinds of nonlinear systems can be found. The adaptive fuzzy scheme estimates the parameters comprising the fuzzy model representing the observation system. The proposed indirect adaptive fuzzy observer based on T-S fuzzy model can cope with not only unknown states but also unknown parameters. In the process of deriving adaptive law, the Lyapunov theory and Lipchitz condition are used. To show the performance of the proposed observation method, it is applied to an inverted pendulum on a cart.

• Proceedings of the IEEK Conference
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• summer
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• pp.348-353
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• 2004

This paper proposes an alternative observation scheme, T-S fuzzy model based indirect adaptive fuzzy observer. Nonlinear systems arc represented by fuzzy models since fuzzy logic systems arc universal approximators. In order to estimate the unmeasurable states of a given nonlinear system, T-S fuzzy modeling method is applied to get the dynamics of an observation system. T-S fuzzy system uses the linear combination of the input state variables and the modeling applications of them to various kinds of nonlinear systems can be found. The adaptive fuzzy scheme estimates the parameters comprising the fuzzy model representing the observation system. The proposed indirect adaptive fuzzy observer based on T-S fuzzy model can cope with not only unknown states but also unknown parameters. In the process of deriving adaptive law, the Lyapunov theory and Lipchitz condition are used. To show the performance of the proposed observation method, it is applied to an inverted pendulum on a cart.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.4
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• pp.973-983
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• 2015

To improve the control performance of the IPMSM, a novel nonlinear disturbance observer is proposed by using the T-S fuzzy model. A T-S fuzzy model is the combination of local linear models considered at each operating point. Usually the inverse model is easy to obtain in linear systems but not in nonlinear systems. To design a nonlinear disturbance observer, a nonlinear inverse model is obtained based on nonlinear inverse model which is the fuzzy combination of the local linear inverse models. The proposed DOB is used with a PDC controller which is one of the T-S fuzzy controller, and its performance improvement is shown from the simulation results.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.4
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• pp.335-343
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• 2007

This paper deals with the method to estimate the friction in a system. We study a nonlinear friction model to estimate the friction in an inverted pendulum and approximate the friction model using fuzzy basis functions expansion. To demonstrate the friction observer using FBFs, we derive a update rule based on the error term that is formed by the output from a real system and observer output with a friction estimate. And two compensation algorithms to improve the response of an inverted pendulum are proposed. The first method that a observer parameter is updated in on-line and the friction is compensated at the same time. The second method is to compensate the friction with observer parameter estimated priori. The two methods is compared through the experimental results.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.9
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• pp.822-826
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• 2013

In this paper, we propose an AFDO (Adaptive Fault Diagnosis Observer) and a fault tolerant controller for a class of nonlinear continuous-time system under the nonlinear abrupt actuator faults. Together with its estimation laws, the AFDO which estimates that the actuator faults is designed by using the Lyapunov analysis. Then, based on the designed AFDO, an adaptive sliding mode controller is proposed as the fault tolerant controller. Using Lyapunov stability analysis, we also prove the uniform boundedness of the state, the output and the fault estimation errors, and the asymptotic stability of the tracking error under the nonlinear time-varying faults. Finally, we illustrate the effectiveness of the proposed diagnosis method and the control scheme thorough computer simulations.

• Transactions of the Korean Society of Automotive Engineers
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• v.12 no.3
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• pp.159-169
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• 2004

In this study, integration control of air-cell seat and semi-active suspension is proposed to minimize the road-tyre force which can cause uncomfortable feeling to rider. The proposed integration control with sliding perturbation observer is consisted of air-cell seat control which uses the force generated by air-cell and the sky-hook control. The air-cell seat itself has been modeled as a 1 degree of freedom spring-damper system. The actual characteristics of the air-cell have been analyzed through experiments. In this paper, we introduces a new robust motion control algorithm using partial state feedback for a nonlinear system with modelling uncertainties and external disturbances. The major contribution of this work is the development and design of robust observer for the state and the perturbation. The combination skyhook controller and air-cell controller using the observer improves control performance, because of the robust routine called Sliding Observer Design for Integration Control of Air-Cell Seat and Semi-active Suspension. The simulation results show a high accuracy and a good performance.

• Journal of Institute of Control, Robotics and Systems
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• v.9 no.12
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• pp.977-983
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• 2003

An output feedback stabilizing controller far non-minimum phase nonlinear systems is presented. We first perform the standard input-output linearization of the system and then transform the zero dynamics into a special normal form in which the antistable part is not affected by the stable part and the antistable part is given in approximately linear form. Under the assumption that the nonlinear system satisfies the observability rank condition, we can design an observer f3r the extended system that is made of the augmentation of a chain of integrators. The proposed output feedback stabilizing controller can then be designed by combining the observer and the state feedback controller.