• International Journal of Control, Automation, and Systems
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• v.3 no.4
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• pp.612-619
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• 2005

A robust adaptive speed sensorless induction motor direct torque control (DTC) using a neural network (NN) is presented in this paper. The inherent lumped uncertainties of the induction motor DTC system such as parametric uncertainty, external load disturbance and unmodeled dynamics are approximated by the NN. An additional robust control term is introduced to compensate for the reconstruction error. A control law and adaptive laws for the weights in the NN, as well as the bounding constant of the lumped uncertainties are established so that the whole closed-loop system is stable in the sense of Lyapunov. The effect of the speed estimation error is analyzed, and the stability proof of the control system is also proved. Experimental results as well as computer simulations are presented to show the validity and efficiency of the proposed system.

• Proceedings of the Korea Concrete Institute Conference
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• 2002.10a
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• pp.361-364
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• 2002

This paper discusses the influencing factors such as coring position, height to diameter ratio of core specimen(h/d) and coring torque on the strength estimation of concrete by small site coring method in order to verify the validities of small size core method. According to results, as for the influence of drilling position, when core specimens are obtained from the place parallel to placing direction, compressive strength of core specimens are higher than those perpendicular to placing direction. This is due to the loss of the area of core specimen perpendicular to plating direction by bleeding. And in case of $\phi$ 24mm core specimen, when vertical drilling against placing direction is taken. compressive strength of core specimen obtained at the bottom of the structure is higher than that at the top of the structure. As for the influence of height to depth ratio, as h/d ratio increases compressive strength shows to be decreased. As for the influences of rotation speed of drilling machine, as its speed goes up, compressive strength decreases, regardless of core diameter.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.1407-1410
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• 1997

Advanced sensor design and filtering technology have been studied to obtain information for condition monitoring and diagnostics inmachining processes. To develope and economic monitoring system in end milling processes, indirect and reliable type of cutting force estimators were required. In this paper, an estimation method of cutting forces during end milling processes was studied through the measurement of current signals obtained from spindle and feeddrive motors. Cutting force and torque models were derived from the cutting geometry in down milling processes. Relationships between motor currents and cutting forces were also developed in the form of AC and DC components from the developed force models. The validity of the cutting force estimator was confirmed by the experiments under various cutting conditions.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.803-806
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• 1997

In this paper, a force estimation method is proposed for the sensorless force control. For this, a disturbance observer is applied to each joint of an n degrees of freedom manipulator to obtain a simple equivalent robot dynamics(SERD) being represented as an n independent double integrator system. To estimate the output of disturbance observer in the absence of external force, the observer estimator is designed, where the uncertain parameters of the robot manipulator are adjusted by gradient method to minimize the output between the disturbance observer and the observer estimator. When the external force is exerted, the external force is estimated using the difference between the output of disturbance observer which include the external torque signal and that of observer estimator. And then, a force controller is designed for force feedback control employing the estimated force signal. To verify the effectiveness of the proposed force estimation method, several numerical examples are illustrated for the 2-axis planar type robot manipulator.

• Proceedings of the KIEE Conference
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• 2006.10d
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• pp.50-52
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• 2006

This paper Proposes a new method of on-line estimation for rotor resistance of the induction motor in the indirect vector controlled drive, using artificial neural network (ANN). The back propagation algorithm is used for training of the neural networks. The error between the desired state variable of an induction motor and actual state variable of a neural network model is back propagated to adjust the weight of a neural network model, so that the actual state variable tracks the desired value. The performance of rotor resistance estimator and torque and flux responses of drive, together with these estimators, are investigated variations rotor resistance from their nominal values. The rotor resistance are estimated analytically, using the proposed ANN in a vector controlled induction motor drive.

• Proceedings of the KSR Conference
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• 2004.06a
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• pp.626-631
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• 2004

In electric motor coaches, the rolling stocks move by the adhesive effort between rail and driving wheel. Generally, the adhesive effort is defined by the function of both the weight of electric motor coach and the adhesive effort between rails and driving wheel. The characteristics of adhesive effort is strongly affected by the conditions between rails and driving wheel. When the adhesive effort decreases suddenly, the electric motor coach has slip phenomena. This paper proposes a re-adhesion control algorithm which uses the maximum adhesive effort by instantaneous estimation of adhesion force using load torque disturbance observer. Based on this estimated adhesive effort, the re-adhesion control is performed to obtain the maximum transfer of the tractive effort.

• Journal of international Conference on Electrical Machines and Systems
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• v.3 no.3
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• pp.289-297
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• 2014

This paper proposed a novel high performance sensorless control scheme for IPMSM based on an extended nonlinear state observer. The gain-matrix of the observer has been derived by using state linearization method. Steady state errors in estimated rotor position and speed due to parameter inaccuracy have been analyzed, and an equivalent flux error is defined to represent the overall effect of parameter errors contributing to the wrong convergence of the estimated rotor speed as well as rotor position. Then, an online compensation strategy was proposed to limit the estimation errors in rotor position and speed. The effectiveness of the extended nonlinear state observer is validated through simulation and experimental test.

• Journal of Mechanical Science and Technology
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• v.15 no.9
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• pp.1248-1256
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• 2001

In this study, a test bed for vehicle longitudinal control is developed using a chassis dynamometer and real time 3-D graphics. The proposed test bed system consists of a chassis dynamometer on which test vehicle can run longitudinally, a video system that shows virtual driver view, and computers that control the test vehicle and realize the real time 3-D graphics. The purpose of the proposed system is to test vehicle longitudinal control and warning algorithms such as Adaptive Cruise Control(ACC), stop and go systems, and collision warning systems. For acceleration and deceleration situations which only need throttle movements, a vehicle longitudinal spacing control algorithm has been tested on the test bed. The spacing control algorithm has been designed based on sliding mode control and road grade estimation scheme which utilizes the vehicle engine torque map and gear shift information.

• Proceedings of the KIPE Conference
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• 1998.07a
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• pp.225-229
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• 1998

If there is a mismatch between the controller programmed rotor time constant and the actual time constant of motor, the decoupling between the flux and torque is lost in an indirect rotor field oriented control. This paper presents a new estimation scheme for rotor time constant using artificial neural networks. The parameters of induction motor model organize 2 layer neural to be weight between neuron, which is proposed new in this paper. This method makes networks simple, so its brings not only the improvement in speed but simplification in calculation. Furthermore, it is possible to estimated rotor time constant real time through on-line learning without using off-line learning. The digital simulation and the experimental results to verify the effectiveness of the new method are described in this paper.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.25 no.2
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• pp.192-197
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• 2001

Recent requirements for the fast and accurate motion in industrial robot manipulators need more advanced control techniques. To satisfy the requirements, importance of the force control is being continuously increased and the expensive force sensor is often installed to obtain the contact force information in practice. This information is indispensable for the force control of maintaining the desired contact force. However, the sensor cost is too high to be used in industrial applications. In this paper, it is proposed to estimate the contact force occurred between the end-effector of robots and environment in 3-D. The contact force monitoring system is developed based on the static and dynamic models of 3 DOF robot manipulators, where the contact force is described with respect to the link torque. The Extended Kalman Filter is designed and its performance is verified in simulations.