• 제어로봇시스템학회:학술대회논문집
• /
• 2005.06a
• /
• pp.275-280
• /
• 2005

The principal context of this research is the approach to an artificial neural network algorithm which solves multivariable nonlinear equation systems by estimating the state of line power flow. First a dynamical neural network with feedback is used to find the minimum value of the objective function at each iteration of the state estimator algorithm. In second step a two-layer neural network structures is derived to implement all of the different matrix-vector products that arise in neural network state estimator analysis. For hardware requirements, as they relate to the total number of internal connections, the architecture developed here preserves in its structure the pronounced sparsity of power networks for which state the estimator analysis is to be carried out. A principal feature of the architecture is that the computing time overheads in solution are independent of the dimensions or structure of the equation system. It is here where the ultrahigh-speed of massively parallel computing in neural networks can offer major practical benefit.

• Proceedings of the KIEE Conference
• /
• 2001.07e
• /
• pp.47-52
• /
• 2001

This paper presents a high-performance control system for Reluctance Synchronous Motor (RSM) drives with direct torque control (DTC). The system consist of stator flux observer, rotor position/speed estimator, torque estimator, two hysteresis band controllers, an optimal switching look-up table, IGBT voltage source inverter, and F240/C31DSP controller by using fully integrated control software. The stator flux observer is based on the combined voltage and current model with stator flux feedback adaptive control that inputs are current and voltage sensing of motor terminal with estimated rotor angle for wide speed range. The rotor position is estimated by the observed stator flux-linkage space vector. The estimated rotor speed can be determinated by differentiation of the rotor position used only in the current model part of the flux observer for a low speed operating area. To prove the suggested control algorithm, we have a simulation and testing at actual experimental system. The developed digitally high-performance position sensorless control system are shown a good motion control response characteristic results and high performance features using 1.0Kw RSM.

• Proceedings of the KIEE Conference
• /
• 2000.07b
• /
• pp.1136-1139
• /
• 2000

The paper describes a new and rigorous mathematical model for the rotor field oriented system with induction motor which uses the estimated speed and rotor flux based on a Model Reference Adaptive System, as well as the real-time approach. The estimated speed and rotor flux is used for the speed and flux feedback control. The stability and the convergence of the estimator are improved on the basis of hyperstability theory for non-linear systems. The real-time controller and estimator are implemented with a sampling period of $926{\mu}s$ using a dual TMS320C44 floating-point digital signal processor. The validity of the proposed method is verified by simulation, and also, the sensorless control was tested on the propulsion system simulator, used for the development of Korean High-Speed Railway Train (KHSRT) [5].

• The Transactions of the Korean Institute of Power Electronics
• /
• v.10 no.2
• /
• pp.186-193
• /
• 2005

This paper presents a strategy to drive built in-type spindle induction motor which is used as CNC(Computer Numerical Control) in the industry. Gopinath model flux estimator which is composed of current model to be profitable in the low speed range and voltage model to be profitable in the high speed range is used for rotor flux estimation. Moreover this paper presents to drive the spindle motor in the high speed range by using the flux weakening control. High speed operation of spindle motor in the field weakening region is verified through simulations and experiments.

• Proceedings of the KIPE Conference
• /
• 1996.06a
• /
• pp.1-4
• /
• 1996

The purpose of this treatise is to estimate speed of an induction motor and realize a robust speed control system with estimated speed in field-weakening region. A speed estimation is based on Model Reference Adaptive System(MRAS) technique and two flux estimator are designed to be robust against parameter variation. The MRAS-based overall control scheme has been implemented on 7.5kW Spindle induction motor control system. And it is verified that the proposed control scheme is very stable and robust in field-weakening region.

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 2006.05a
• /
• pp.245-248
• /
• 2006

A particle filter is one of the most famous filters. The reason why the particle filter is widely used is that particle deals with the state estimation problem for not only linear models with Gaussian noise but also the non-linear models with non-Gaussian noise and it receives great attention from many engineering fields. In the point of view state estimator, particle filter is feedforward observer. According to the characteristic of dynamic system, the feedforward observer can estimate real state. However, the speed of convergence of feedforward observer between the actual state and the estimated state cannot be satisfied. Since the particle filter is a sort of feedforward observer, the convergence speed of particle filter is slow, and the particle filter cannot estimate actual state like particle collapse problem. In order to overcome the limitation of particle filter as a kind of feedfoward estimator, we propose a new particle filter which has feedback term, called particle filter with feedback. Our proposed method is analyzed theoretically and studied by computer simulation. Comparisons are made with other filtering mehod.

• The Transactions of the Korean Institute of Electrical Engineers B
• /
• v.51 no.10
• /
• pp.573-580
• /
• 2002

This paper presents neural load disturbance observer that used to deadbeat load torque observer and regulation of the compensation gain by parameter estimator As a result, the response of PMSM follows that of the nominal plant. The load torque compensation method is compose of a neural deadbeat observer. To reduce of the noise effect, the post-filter, which is implemented by MA process, is proposed. The parameter compensator with RLSM(recursive least square method) parameter estimator is suggested to increase the performance of the load torque observer and main controller. The proposed estimator is combined with a high performance neural torque observer to resolve the problems. As a result, the proposed control system becomes a robust and precise system against the load torque and the parameter variation. A stability and usefulness, through the verified computer simulation and experiment, are shown in this paper.

• International Journal of Computer Science & Network Security
• /
• v.23 no.5
• /
• pp.121-127
• /
• 2023

A 500 km/h linear motor high speed terrestrial transportation service is planned to launch 2027 in Japan. In order to support 5G service in the train, the Sub-carrier spacing frequency of 30 kHz is planned to be used instead of common 15 kHz sub-carrier spacing to mitigate Doppler effect in such high-speed transportation. In addition, to increase the cell size of 5G mobile system, plural Base Station antenna will transmit the identical Down Link (DL) signal to form the expanded cell size along the train rail. In this situation, forward and backward antenna signals will be Doppler shifted by reverse direction respectively and the receiver in the train might suffer to estimate accurate Channel Transfer Function (CTF) for its demodulation. In this paper, Delay and Doppler Profiler (DDP) based Channel Estimator is proposed and it is successfully implemented in signal processing simulation system. Then the simulated performances are compared with the conventional Time domain linear interpolated estimator. According to the simulation results, QPSK modulation can be used even under severe channel condition such as 500 km/h, 2 path reverse Doppler Shift condition, although QPSK modulation can be used less than 200 km/h with conventional Channel estimator.

• Proceedings of the KIPE Conference
• /
• 1997.07a
• /
• pp.161-165
• /
• 1997

For high performance ac drives, the speed sensorless vector control and the stator flux orientation concept have received increasing attention. This paper presents a new method of estimation the speed of AC induction machine(IM). To improve the speed estimation characteristics, accurate stator resistance variation is considered. The effectiveness of the proposed method is verified computer simulation.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.56 no.7
• /
• pp.1241-1249
• /
• 2007

Lately, many approaches of speed sensorless control method for Interior Permanent Magnet Synchronous Motor(IPMSM) ha, been developed. This paper proposes a novel sensorless algorithm for speed estimation of IPMSM. First of all, proposes sensorless method estimates flux of rotor using foundational voltage equation of IPMSM and then estimates position and speed of rotor using Phase Locked Loop(PLL). Proposed sensorless algorithm demonstrated through simulation using Matlab simulink and experiment.