• 제어로봇시스템학회:학술대회논문집
• /
• 2004.08a
• /
• pp.1168-1172
• /
• 2004

This paper presents a speed controller based on an adaptive fuzzy algorithm for high performance permanent magnet synchronous motor (PMSM) drives under parameter and load variations. In many speed tracking control systems PI controller has been used due to its simple structure and easy of design. PI controller, however, suffers from the electrical machine parameter variations and disturbances. In order to improve the tracking control performance under load variations, the PI controller parameters are modified during operation by adaptive fuzzy method. This method based on optimal fuzzy logic system has simple structure and computational simplicity. It needs only sample data which is obtained by optimal controller off-line. As the sample data implemented in the adaptive fuzzy system can be modified or extended, a flexible control system can be obtained. Simulation results show the usefulness of the proposed controller.

• Journal of Electrical Engineering and Technology
• /
• v.10 no.2
• /
• pp.529-538
• /
• 2015

Due to the high efficiency and compact mechanical structure, direct drive variable speed generators are used for power conversion in wind turbines. The wind energy conversion system (WECS) considered in this paper consists of a permanent magnet synchronous generator (PMSG), uncontrolled rectifier, dc-dc boost converter controlled with maximum power point tracking (MPPT) and adaptive hysteresis controlled voltage source inverter (VSI). For high utilization of the converter's power capability and stabilizing voltage and power flow, constant DC-link voltage is essential. Step and search MPPT algorithm which senses the rectified voltage ($V_{DC}$) alone and controls the same is used to effectively maximize the output power. The adaptive hysteresis band current control is characterized by fast dynamic response and constant switching frequency. With MPPT and adaptive hysteresis band current control in VSI, the DC link voltage is maintained constant under variable wind speeds and transient grid currents respectively.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
• /
• 2007.11a
• /
• pp.313-318
• /
• 2007

Interior permanent magnet synchronous motor(IPMSM) has become a popular choice in electric vehicle applications, due to their excellent power to weight ratio. This paper proposes maximum torque control of IPMSM drive using adaptive fuzzy neural network controller and artificial neural network(ANN). This control method is applicable over the entire speed range which considered the limits of the inverter's current and voltage rated value. For each control mode, a condition that determines the optimal d-axis current $i_d$ for maximum torque operation is derived. This paper considers the design and implementation of novel technique of high performance speed control for IPMSM using Adaptive-FNN controller and ANN controller. The hybrid combination of neural network and fuzzy control will produce a powerful representation flexibility and numerical processing capability. Also, this paper reposes speed control of IPMSM using Adaptive-FNN and estimation of speed using ANN controller. The back propagation neural network technique is used to provide a real time adaptive estimation of the motor speed. The proposed control algorithm is a lied to IPMSM drive system controlled Adaptive-FNN and ANN controller, the operating characteristics controlled by maximum torque control are examined in detail. Also, this paper proposes the analysis results to verify the effectiveness of the Adaptive-FNN and ANN controller.

• Journal of Electrical Engineering and Technology
• /
• v.12 no.1
• /
• pp.249-255
• /
• 2017

Efficient operation of induction motor at light loads has been getting wide attention recently because the operating of induction motor at light loads occupies big portion of its operating regions in many applications such as environment friendly vehicle. As one of approaches to improve efficiency, Adaptive Maximum Torque Per Amp (Adaptive MTPA) control for induction motor drives has been proposed to achieve a desired torque with the minimum possible stator current. However, the Adaptive MTPA control was validated only at heavy load where, in general, control scheme tends to perform better than at light loads since the error in measurement of sensors is lower and signal to noise is better. Thus, although the performance of a control scheme is good at rated operating point, its performance at light load is somewhat in doubt in practice. This has led to considerable interest in efficiency of Adaptive MTPA control at light loads. This work experimentally demonstrates performance of Adaptive MTPA control at light loads regardless of rotor resistance variation, thus showing its good performance over all operating conditions.

• 제어로봇시스템학회:학술대회논문집
• /
• 1989.10a
• /
• pp.489-493
• /
• 1989

In this paper a new approach to adaptive control using a combination of both direct and indirect methods has been proposed. Based on the estimates of the plant parameters and the current values of the control parameters, closed-loop estimation errors .epsilon.$_{\theta}$(t) and .epsilon.$_{k}$(t) are defined. These in turn are used in the adaptive laws for updating both identification as well as control parameters. The global uniform stability of the overall system is shown by constructing a Lyapunov function.n.

• Journal of Advanced Marine Engineering and Technology
• /
• v.28 no.4
• /
• pp.641-647
• /
• 2004

By most sensorless speed control schemes for induction motor. the control performances in high speed range are good, but it is difficult to obtain satisfactory results in low speed region. This paper proposes a new method controlling the low and the high speed regions separately to attain the stable operation in the overall range. The current error compensation method, in which the controlled stator voltage is applied to the induction motor so that the error between stator currents of the numerical model and the actual motor can be forced to decay to zero as time proceeds. is used in the low speed region In the high speed region. the method with adaptive observer is utilized. This control strategy contains an adaptive state observer for flux estimation. The rotor speed can be calculated from the rotor flux and the motor currents. The experimental results indicate good speed and load responses from the very low speed range to the high, and also show accurate speed changing performance between the low and the high speed range.

• Journal of Institute of Control, Robotics and Systems
• /
• v.18 no.10
• /
• pp.902-911
• /
• 2012

This paper proposes a robust adaptive fuzzy backstepping control scheme for trajectory tracking of an electrically driven nonholonomic mobile robot with uncertainties and actuator dynamics. A complete model of an electrically driven nonholonomic mobile robot described in this work includes all models of the uncertain robot kinematics with a nonholonomic constraint, the uncertain robot body dynamics with uncertain frictions and unmodeled disturbances, and the uncertain actuator dynamics with disturbances. The proposed control scheme uses the backstepping control approach through a kinematic controller and a robust adaptive fuzzy velocity tracking controller. The presented control scheme has a voltage control input with an auxiliary current control input rather than a torque control input. It has two FBFNs(Fuzzy Basis Function Networks) to approximate two unknown nonlinear robot dynamic functions and a robust adaptive control input with the proposed adaptive laws to overcome the uncertainties such as parameter uncertainties and external disturbances. The proposed control scheme does not a priori require the accurate knowledge of all parameters in the robot kinematics, robot dynamics and actuator dynamics. It can also alleviate the chattering of the control input. Using the Lyapunov stability theory, the stability of the closed-loop robot control system is guaranteed. Simulation results show the validity and robustness of the proposed control scheme.

• Journal of the Korean Society for Precision Engineering
• /
• v.19 no.12
• /
• pp.57-63
• /
• 2002

In this paper, the feedforward control with least mean square (LMS) adaptive algorithm is proposed and examined to reduce rotating error by runout of an active magnetic bearing system. Using eddy-current type gap sensor fur control, the electrical runout caused by non-uniform material properties of sensor target produces rotational error amplified in feedback control loop, so this runout should be eliminated to increase rotating accuracy. The adaptive feedforward controller is designed and examined its tracking and stability performances numerically with established frequency response function. The tested grinding spindle system is manufactured with a 5.5 ㎾ internal motor and 5-axis active magnetic bearing system including 5 eddy current gap sensors which have approximately 15 ~ 30 ${\mu}{\textrm}{m}$ of electrical runout. According to the experimental analysis, the error signal in radial bearings is reduced to less than 5 ${\mu}{\textrm}{m}$ when it is rotating up to 50,000 rpm due to applying the feedforward control for first order harmonic frequency, and vibration of the spindle base is also reduced about same frequency.

• International Journal of Precision Engineering and Manufacturing
• /
• v.6 no.2
• /
• pp.19-25
• /
• 2005

In this paper, the feedforward control with least mean square (LMS) adaptive algorithm is proposed and examined to reduce rotating error by runout of an active magnetic bearing system. Using eddy-current type gap sensors for control, the electrical runout caused by non-uniform material properties of sensor target produces rotational error amplified in feedback control loop, so this runout should be eliminated to increase rotating accuracy. The adaptive feedforward controller is designed and examined its tracking performances and stability numerically with established frequency response function. The designed feedforward controller was applied to a grinding spindle system which is manufactured with a 5.5 kW internal motor and 5-axis active magnetic bearing system including 5 eddy current gap sensors which have approximately 15∼30㎛ of electrical runout. According to the experimental results, the error signal in radial bearings is reduced to less than 5 ,Urn when it is rotating up to 50,000 rpm due to applying the feedforward control for first order harmonic frequency, and corresponding vibration of the spindle is also removed.

• Journal of the Korean Society for Precision Engineering
• /
• v.13 no.2
• /
• pp.133-145
• /
• 1996

This paper presents an indirect cutting force measuring system, which uses the current signals from the AC servo drive units of the horizontal machining center, with its applications to the adaptive regulation of the cutting forces in various milling processes and to the on-line monitoring of tool breakage. A typical model for the feed-drive control system of a horizontal machining center is developed to analyze cutting force measurement from the drive motor. The pulsating milling forces can be measured indirectly within the bandwidth of the current feedback control loop of the feed-drive system. It is shown that the indirectly measured cutting force signals can be used in the adaptive controller for cutting force regulation. The whole scheme has been embedded in the commercial machining center and a series of cutting experiments on the face cutting processes are performed. The adaptive controller reveals reliable cutting force regulating capability against the various cutting conditions. It is also shown that the tool breakage in milling can be detected within one spindle revolution by adaptively filtering the current signals. The effect of the cutter run-out has been considered for the reliable on-line detection of tool breakage.