• Journal of Power Electronics
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• v.5 no.2
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• pp.129-141
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• 2005

A high-performance robust hybrid speed controller for a permanent-magnet synchronous motor (PMSM) drive with an on-line trained neural-network model-following controller (NNMFC) is proposed. The robust hybrid controller is a two-degrees-of-freedom (2DOF) integral plus proportional & rate feedback (I-PD) with neural-network model-following (NNMF) speed controller (2DOF I-PD NNMFC). The robust controller combines the merits of the 2DOF I-PD controller and the NNMF controller to regulate the speed of a PMSM drive. First, a systematic mathematical procedure is derived to calculate the parameters of the synchronous d-q axes PI current controllers and the 2DOF I-PD speed controller according to the required specifications for the PMSM drive system. Then, the resulting closed loop transfer function of the PMSM drive system including the current control loop is used as the reference model. In addition to the 200F I-PD controller, a neural-network model-following controller whose weights are trained on-line is designed to realize high dynamic performance in disturbance rejection and tracking characteristics. According to the model-following error between the outputs of the reference model and the PMSM drive system, the NNMFC generates an adaptive control signal which is added to the 2DOF I-PD speed controller output to attain robust model-following characteristics under different operating conditions regardless of parameter variations and load disturbances. A computer simulation is developed to demonstrate the effectiveness of the proposed 200F I-PD NNMF controller. The results confirm that the proposed 2DOF I-PO NNMF speed controller produces rapid, robust performance and accurate response to the reference model regardless of load disturbances or PMSM parameter variations.

• Journal of Advanced Marine Engineering and Technology
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• v.30 no.7
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• pp.791-799
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• 2006

The aim of this paper is to design an adaptive speed control system of a marine diesel engine by fusion of hard computing based proportional integral derivative (PID) control and soft computing based fuzzy control methods. The model of a marine diesel engine is considered as a typical non oscillatory second order system. When its model and the actual marine diesel engine ate not matched, it is hard to control the speed of the marine diesel engine. Therefore, this paper proposes two methods in order to obtain the speed control characteristics of a marine diesel engine. One is an efficient method to determine the PID control parameters of the nominal model of a marine diesel engine. Second is a reference adaptive speed control method that uses a fuzzy controller and derivative operator for tracking the nominal model of the marine diesel engine. It was found that the proposed PID parameters adjustment method is better than the Ziegler & Nichols' method, and that a model reference adaptive control is superior to using only PID controller. The improved control method proposed here, could be applied to other systems when a model of a system does not match the actual system.

• Proceedings of the KIEE Conference
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• 1997.11a
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• pp.130-132
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• 1997

This paper proposes a reference model following control system using fuzzy logic controller and genetic algorithm. A fuzzy logic controller is designed such that plant output follows the output generated by a reference model. In this paper, First-order and second-order reference model with no overshoot and fast rise time is designed. Experiment results show the effectiveness of the proposed controller in tracking property and robustness.

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.2299-2301
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• 2000

In this paper, the design of PID controller using Neural networks for the control of non-linear system is presented. First, non-linear system is identified using BPN(Backpropagation Network) algorithm. This identified model is connected to the PID controller and the parameters of PID controller are updated to the direction of reducing the difference between the identified model output and model reference output in arbitrary input signal. Therefore, identified model output tracks the model reference output in an acceptable error range and the parameters of controller are updated adaptively. The output of the system has a good performance in case of both noisy and noiseless model reference and we can control the system stable in off-line when the dynamics of the system is changed.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.763-766
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• 1996

A model helicopter is an unstable, multi-input multi-output nonlinear system exposed to strong disturbances and its system parameters change continually. In this paper, Time Delay Control(TDC) is adopted for these reasons. TDC uses past observation of the system's response and the control input to directly modify the control action rather than adjusting the controller gains leading to a model independent robust controller. TDC can force the plant to follow an appropriate reference model, but the reference model cannot be chosen arbitrarily. In this paper the procedure of choosing a reference model and the performance of the controller are presented.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10a
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• pp.342-345
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• 1996

This paper is dealing with a design of linear controller so that the plant output is regulated to follow a reference model output when the plant equation is described by a class of nonlinear time-varying control systems.

• Journal of Electrical Engineering and Technology
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• v.10 no.6
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• pp.2427-2433
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• 2015

This paper presents an observer-based robust controller for constant reference tracking of linear time invariant systems with polytopic model uncertainties. To this end, this paper not only designs a robust integral controller gain but also suggests how to determine the robust observer gain and the observer model used in the observer. Since the observer model selection is not obvious due to the polytopic uncertainties, particular attention needs to be paid to that. This paper computes the robust controller and observer gains first. Then, the observer model is selected in a way that the whole closedloop is stable and LMIs are used in the middle of choosing the gains and observer model. Simulation examples show that the proposed observer-based feedback control successfully achieves robust reference tracking.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.700-703
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• 1997

A robust controller for a 6 DOF magnetically levitated fine manipulator is presented. The proposed controller consists of following two parts : a model reference controller (MRC) and a H$_{\infty}$ controller (HIC). First, the MRC stabilizes the motion of the manipulator. Then, the motion of the manipulator follows that of the reference model. Second, the HIC minimizes errors generated from the MRC due to noise and disturbance since the HIC is a kind of robust controller. The experiments of position control and tracking control are carried out by use of the proposed controller under the conditions of free disturbances and forced disturbances. Also, the experiments using PID controller are carried out under the same conditions. The results from above two controllers are compared to investigate the control performances. As the results, it is observed that the proposed controller has similar position accuracy but better tracking performances comparing to the PID controller as well as good disturbance rejection effect due to the robust characteristics of the controller. In conclusion, it is verified that the proposed controller has the simple control structure, the good tracking performances and good disturbance rejection effect due to the robust characteristics of the controller..

• Journal of Electrical Engineering and Technology
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• v.11 no.2
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• pp.405-415
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• 2016

This paper presents a model predictive control for shunt active power filters in synchronous reference frame using space vector pulse-width modulation (SVPWM). The three phase load currents are transformed into synchronous rotating reference frame in order to reduce the order of the control system. The proposed current controller calculates reference current command for harmonic current components in synchronous frame. The fundamental load current components are transformed into dc components revealing only the harmonics. The predictive current controller will add robustness and fast compensation to generate commands to the SVPWM which minimizes switching frequency while maintaining fast harmonic compensation. By using the model predictive control, the optimal switching state to be applied to the next sampling time is selected. The filter current contains only the harmonic components, which are the reference compensating currents. In this method the supply current will be equal to the fundamental component of load current and a part of the current at fundamental frequency for losses of the inverter. Mathematical analysis and the feasibility of the suggested approach are verified through simulation results under steady state and transient conditions for non-linear load. The effectiveness of the proposed controller is confirmed through experimental validation.

• Journal of the Korean Institute of Telematics and Electronics
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• v.22 no.2
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• pp.31-35
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• 1985

This paper presents novel designs of a digital minimum-time controller and a digital adaptive controller using reference no del for single input-single out put linear time-invariant plants with known parameters. The proposed digital minimum-time controller which has a deadbeat response is designed to make the transfer function of this controller equal to that of reference model, and the proposed digital adaptive controller is designed by applying the adaptation method to the proposed digital minimum-time controller. The designs of these two controllers are very simple and easy, and all types of input signal with any reference models are controllable. These dffectivenesses have been demon-strated by computer simulations carried out for a third-order plant.