• Journal of the Korean Institute of Intelligent Systems
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• v.9 no.4
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• pp.384-388
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• 1999

This paper describes an approach for synthesizing a modularized gain scheduled PD type fuzzy logic controller(FLC) of nonlinear magnetic bearing system where the gains of FLC are on-line adapted according to the operating point. Specifically the systematic procedure via root locus technique is carried out for the selection of the gains of FLC. Simulation results demonstrate that the proposed gain scheduled fuzzy logic controller yields not only maximization of stability boundary but also better control performance than a single operating point (without gain scheduling)fuzzy controller.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.141.1-141
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• 2001

This paper describes an approach for synthesizing a modularized gain scheduled PD type fuzzy logic controller(FLC) for a high maneuverable aircraft system, where the gains of FLC are on-line adapted according to the flight condition. Specially, the systematic procedure via root locus technique is carried out for the sellection of the gains of FLC. Simulation results demonstrate that the proposed gain scheduled fuzzy logic controller yields better control performance than the normal (without gain scheduling) fuzzy controller.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.1
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• pp.95-103
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• 2008

This paper deals with the problem of autolanding for aircraft under windshear environment for which the landing trajectory is given. It is well known that the landing maneuver in windshear turbulence is very dangerous and hard for the pilot to control because windshear is unpredictable in when and where it happens and its aerodynamic characteristics are complicated. In order to accomplish satisfactory autolanding maneuver in this environment, we propose a gain-scheduled controller. The proposed controller consists of three parts: PID controller, called baseline controller, which is designed to satisfy requirements of stability and performance without considering windshear, gain scheduler based on fuzzy logic, and safety decision logic, which decides if the current autolanding maneuver needs to be aborted or not. The controller is applied to a 6-DOF simulation model of the associated airplane in order to illustrate the effectiveness of the proposed control algorithm. It is noted that a cross wind in the lateral direction is included to the simulation model. From the simulation results it is observed that the proposed gain scheduled controller shows superior performance than the case of controller without gain scheduling even in severe downburst and tailwind region of windshear. In addition, touchdown along centerline of the runway is more precise for the proposed controller than for the controller without gain scheduling in the cross wind and the tailwind.

• The Transactions of the Korean Institute of Electrical Engineers B
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• v.54 no.12
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• pp.569-575
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• 2005

This paper proposes a gain scheduled control technique using time-delay for the nonlinear system with plant uncertainties and unexpected disturbances. The time delay-based gain scheduled control depends on a direct estimation of a function representing the effect of uncertainties. The information from the estimation is used to cancel the unknown dynamics and the unexpected disturbances simultaneously. The proposed estimation scheme with a finite convergence time is formulated in order to estimate the unknown scheduling variable variation. In other words, the time delay-based gain scheduled control uses the past observation of the system's response and the control input to directly modify the control actions rather than to adjust the controller gains or to identify system parameters. It has a simple structure so as to minimize the computational burden. The benefits of this proposed scheme are demonstrated in the simulation of an electromagnetic suspension system with plant uncertainties and external disturbances, and the proposed controller is compared with the conventional state feedback controller.

• Proceedings of the KSME Conference
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• 2007.05a
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• pp.915-920
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• 2007

A new optimal state feedback and disturbance feedforward control design in the sense of minimizing $L_{2}-gain$ from disturbance to control output is proposed for disturbance attenuation of systems with bounded control input and measurable disturbance. The controller is derived in the framework of linear matrix inequality(LMI) optimization. A gain scheduled state feedback and disturbance feedforward control design is also suggested to improve disturbance attenuation performance. The control gains are scheduled according to the proximity to the origin of the state of the plant and the magnitude of disturbance. This procedure yields a stable linear time varying control structure that allows higher gain and hence higher performance controller as the state and the disturbance move closer to the origin. The main results give sufficient conditions for the satisfaction of a parameter-dependent performance measure, without violating the bounded control input condition.

• Journal of the Korean Society for Precision Engineering
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• v.24 no.11
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• pp.59-65
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• 2007

A new optimal state feedback and disturbance feedforward control design in the sense of minimizing $L_2$-gain from disturbance to control output is proposed for disturbance attenuation of systems with bounded control input and measurable disturbance. The controller is derived in the framework of linear matrix inequality(LMI) optimization. A gain scheduled state feedback and disturbance feedforward control design is also suggested to improve disturbance attenuation performance. The control gains are scheduled according to the proximity to the origin of the state of the plant and the magnitude of disturbance. This procedure yields a stable linear time varying control structure that allows higher gain and hence higher performance controller as the state and the disturbance move closer to the origin. The main results give sufficient conditions for the satisfaction of a parameter-dependent performance measure, without violating the bounded control input condition.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.48.5-48
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• 2001

The resulting stabilizing controller in this paper consists of the disturbance estimator and the gain scheduled controller. The disturbance estimator tracks the unknown external disturbance and its derivative information in the closed-loop control system using fuzzy logic based adaptation law. Moreover, the gains of the stabilizing controller are appropriately scheduled according to the estimated values. Furthermore, since the estimation law is combined with the stabilizing controller in the closed control loop, it asymptotically minimizes the estimation error. In order to conrm the usefulness of the proposed control scheme, it is applied to the magnetic suspension systems.

• Proceedings of the KIEE Conference
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• 2005.04a
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• pp.221-225
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• 2005

This paper proposes a gain scheduled control technique using time-delay for the nonlinear system with plant uncertainties and unexpected disturbances. The time delay-based gain scheduled control depends on a direct estimation of a function representing the effect of uncertainties. The information from the estimation is used to cancel the unknown dynamics and the unexpected disturbances simultaneously. The proposed estimation scheme with a finite convergence time is formulated in order to estimate the unborn scheduling variable variation. In other words, the time delay-based gain scheduled control uses the past observation of the system's response and the control input to directly modify the control actions rather than to adjust the controller gains or to identify system parameters. It has a simple structure so as to minimize the computational burden. The benefits of this proposed scheme are demonstrated in the simulation of an electromagnetic suspension system with plant uncertainties and external disturbances, and the proposed controller is compared with the conventional state feedback controller.

• Journal of Institute of Control, Robotics and Systems
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• v.6 no.9
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• pp.758-767
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• 2000

The properties of linear time-varying(LTV) systems vary because of the time-varying property of plant parameters. The generalized controller design method for linear time-varying systems does not exit because the analytic soultion of dynamic equation has not been found yet. Hence, to design a controller for LTV systems, the robust control methods for uncertain LTI systems which are the approximation of LTV systems have been generally ised omstead. However, these methods are not sufficient to reflect the fast dynamics of the original time-varying systems such as missiles and supersonic aircraft. In general, both the performance and the robustness of the control system which is designed with these are not satisfactory. In addition, since a better model will give the more robustness to the controlled system, a gain scheduling technique based on LTI controller design methods has been uesd to solve time problem. Therefore, we propose a new gain scheduled QFT method for LTV systems based on neural networks in this paper. The gain scheduled QFT involves gain dcheduling procedured which are the first trial for QFT and are well suited consideration of the properties of the existing QFT method. The proposed method is illustrated by a numerical example.

• Smart Structures and Systems
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• v.9 no.4
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• pp.373-392
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• 2012

Tracking control of systems with variable stiffness hysteresis using a gain-scheduled (GS) controller is developed in this paper. Variable stiffness hysteretic system is represented as quasi linear parameter dependent system with known bounds on parameters. Assuming that the parameters can be measured or estimated in real-time, a GS controller that ensures the performance and the stability of the closed-loop system over the entire range of parameter variation is designed. The proposed method is implemented on a spring-mass system which consists of a semi-active independently variable stiffness (SAIVS) device that exhibits hysteresis and precisely controllable stiffness change in real-time. The SAIVS system with variable stiffness hysteresis is represented as quasi linear parameter varying (LPV) system with two parameters: linear time-varying stiffness (parameter with slow variation rate) and stiffness of the friction-hysteresis (parameter with high variation rate). The proposed LPV-GS controller can accommodate both slow and fast varying parameter, which was not possible with the controllers proposed in the prior studies. Effectiveness of the proposed controller is demonstrated by comparing the results with a fixed robust $\mathcal{H}_{\infty}$ controller that assumes the parameter variation as an uncertainty. Superior performance of the LPV-GS over the robust $\mathcal{H}_{\infty}$ controller is demonstrated for varying stiffness hysteresis of SAIVS device and for different ranges of tracking displacements. The LPV-GS controller is capable of adapting to any parameter changes whereas the $\mathcal{H}_{\infty}$ controller is effective only when the system parameters are in the vicinity of the nominal plant parameters for which the controller is designed. The robust $\mathcal{H}_{\infty}$ controller becomes unstable under large parameter variations but the LPV-GS will ensure stability and guarantee the desired closed-loop performance.