• Journal of Institute of Control, Robotics and Systems
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• v.6 no.3
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• pp.241-247
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• 2000

The reference model of an MRC (model reference control) provides the desired trajectory a plant should follow and thus the design of a reference model has a significant effect on control performance. In most control systems control input to a plant has some bounds and it is preferable to make use of as large control inputs as possible within the range of no saturation. In this paper a new approach of selecting the reference model is proposed for bounded control inputs. Design variables of the reference model are determined in such a way that maximizes the performance index within the range of no saturation. Moreover this variable reference model is regularly updated during control. This scheme is verified by application to the servo motor position control system in various simulations. The responses of the MRC with a variable reference model show better tracking performance than that with a fixed reference mode. Moreover by adjusting the update interval of the reference model the control performance can be further improved.

• Journal of the Institute of Convergence Signal Processing
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• v.8 no.4
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• pp.297-306
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• 2007

Model reference control is control method such that overall response of a plant plus controller approaches that of a given reference model. The reference model provides desired trajectory the plant should follow. There are many kinds of control methods in MRC. However, this paper focuses on Model Reference Sliding Mode Control. The plant of these controls is an uncertain and linear system varying in time, of second order, and with SISO. In this paper, a design scheme of reference model is proposed for MRSMC. The scheme determines reference model based on the information on bounded control inputs, reference inputs and system parameters. It is used to choose a Fixed Reference Model in the process of controller design, to update Variable Reference Model when stepwise reference inputs change and to update Instant Reference Model at every sampling time. The simulation results show that the proposed method yields better control performance than the conventional MRC subject to the stepwise reference input when applied to the position control system for motor system.

• Journal of Institute of Control, Robotics and Systems
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• v.5 no.2
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• pp.166-173
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• 1999

Reference models are used in many control algorithms for improvement of transient response characteristics. They provide desired trajectories that the plant should follow Most control systems have bounded control inputs to avoid saturation of the plant. If we design the reference models that do not account for limits of the control inputs, control performance of the system may be deteriorated. In this paper a new approach of avoiding saturation by varying the reference model for TDC(time delay control) based systems subject to step changes in the reference input. In this scheme, the variable reference model is determined based on the information on control inputs and the size of the step changes in the reference inputs. This scheme was verified by application to the BLDC motor position control system in simulations and experiments. The responses of the TDC with the variable reference model showed better tracking performance than that with the fixed reference model.

• Transactions on Control, Automation and Systems Engineering
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• v.3 no.1
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• pp.32-42
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• 2001

In this paper, a parameter estimator is developed for the plant model whose structure is represented by the Takagi-Sugeno model. The essential idea behind the on-line estimation is the comparison of the measured stated with the state of an estimation model whose structure is the same as that of the parameterized model. Based on the parameter estimation scheme, and indirect Model Reference Adaptive Fuzzy control(MRAFC) scheme is proposed to provide asymptotic tracking of a reference signal for the systems with uncertain for slowly time-varying parameters. The developed control law and adaptive law guarantee the boundedness of all signals in the closed-loop systems. In addition, the plant state tracks the state of the reference model asymptotically with time for any bounded reference input signal.

• Journal of Institute of Control, Robotics and Systems
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• v.15 no.7
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• pp.711-719
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• 2009

This paper presents a design scheme of torque control for wheeled mobile robot(WMR) to asymptotically track the target reference trajectory. By considering the kinematic model of WMR, trajectory tracking control generates the desired tracking trajectory, which is transformed into the command velocity vector for the real WMR to track the target reference trajectory. The dynamic equation of the state error between the target reference trajectory and the desired tracking trajectory is represented by Takagi-Sugeno fuzzy model, and this model is used as the reference model for the real mobile robot error dynamics to follow. The control parameters are updated by adaptive laws that are designed for the error states of the real WMR to asymptotically follow the states of reference error model for the desired tracking trajectory. The proposed control is applied to a typical wheeled mobile robot and simulation studies are carried out to verify the validity and effectiveness of the control scheme.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.15 no.5
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• pp.72-78
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• 2006

The paper proposes reference model error feedback control scheme for motion control system with hard non-linear components as like saturation and dead-zone in plant input part. Additionally, the plant has the system uncertainty effected by plant model parameter deviation and disturbance. The control algorithm uses the reference model to apply additional feedback loop with the error between reference model output and actual output effected by disturbance and non-linear components. And the stability evaluation based on Popov stability and controller design method are formulated to be performed. The effectiveness of the proposed scheme is examined by simulations. The results are proven by reasonable performances following reference model responses with good disturbance rejection performance without over-tuning of controller.

• Journal of Power System Engineering
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• v.11 no.3
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• pp.66-72
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• 2007

This study proposed new method to decide the reference model necessary for design PID controller. In generally, control design problems using the reference model have the following two factors. One factor is that numerical model of the controlled system can be obtained extremely, and the other is that specification for the closed-loop dynamic performance is pure moderate. Therefore, the control design procedure is essentially based on the partial reference model matching which offers a reasonable method to simplify the design and the controller configuration under the controlled system uncertainty. ITAE(Integral of time-multiplied absolute error) performance index and Kitamori method etc. which were used a reference model method had a limit to settling time and rising time of reference model that it arrived to steady state response according to the controlled system. On this study, if it only knew peak time of overshoot and settling time by measurement signal of the controlled system, it can be made the reference model easily. We proposed new method to improve performance index of the reference model superior to existing reference model index and illustrate the numerical simulation results to show the effectiveness of proposed control method design.

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.1
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• pp.130-135
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• 2007

In this paper, a direct model reference adaptive fuzzy control (MRAFC) scheme is developed for the plant model whose structure is represented by the MIMO Takagi-Sugeno fuzzy model. The MRAFC scheme is proposed to provide asymptotic tracking of a reference signal lot the systems with uncertain or slowly time-varying parameters. The developed control law and adaptive law guarantee that all signals in the closed-loop system are bounded. In addition, the plant state tracks the state of the reference model asymptotically with time tot any bounded reference input signal.

• Proceedings of the KSME Conference
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• 2003.11a
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• pp.1602-1607
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• 2003

Vibration causes noise and sometimes makes structure unstable. Especially, due to the efforts of lightening, deformation of flexible structure is increased in its shape. Just a little disturbance can cause vibration and low damping ratio makes residual vibration last long time. This research is concerned with the model reference neuro-controller design for the vibration suppression of smart structures. By using a model reference neurocontroller, which is one of the algorithms of adaptive control, we performed an adaptive control of flexible cantilever plate and opened box structure with piezoelectric materials. The proposed adaptive vibration control algorithm, a model reference neuro-controller, was proved in its effectiveness by applying to an opened box structure. The model reference neuro-controller is implemented with DSP, and the real-time adaptive vibration control experiment results confirm that the model reference neuro-controller is reliable.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.387-387
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• 2000

In this paper, we present a model reference sliding mode control for the system with input/output disturbance. The proposed model reference sliding mode control makes always the error remain on the surface in finite time. Therefore the system is insensitive to external disturbance. Simulation results are included to illustrate the effectiveness of proposed scheme.