• 동력기계공학회지
• /
• 제19권4호
• /
• pp.89-96
• /
• 2015

This paper investigates some strategies to overcome the chattering problem of the conventional sliding mode observer (SMO) and to improve the rotor position estimation performance for full range sensorless control of a PMSM. An adaptive observer gain based on the Lyapunov's stability criterion and a cascade low pass filter with advanced phase delay compensation were proposed to reduce the chattering problem and to strengthen the filtering capability of the SMO. Several cases studies through experiments were carried out to confirm conventional SMO's problems and effectiveness of the proposed strategies. The experimental results show that the proposed method gives precise estimation on speed and rotor position when the motor rotates on 2% of its rated speed.

• 터널과지하공간
• /
• 제4권1호
• /
• pp.55-62
• /
• 1994

The hydraulic fracturing in a field site was performed for the measurement of in-situ stresses. For the estimation of the effect of a preexisting inclined fracture, the test on a preexisting fracture zone was also conducted. From the measurements at three shallow depths, the ratios of max. to min. horizontal stress showed the range of 1.19-1.56 and the K values showed the range of 2.62-3.86. In case of a preexisting fracture with the inclination of 15 degrees, the stresses calculated as upper bound values by considering it. It seemed from this that the inclination less than 15 degrees had small effect on the stress calculation.

• 전기학회논문지
• /
• 제62권6호
• /
• pp.750-755
• /
• 2013

In-wheel motor system gets the driving force from direct-driven motor in the wheel of electric vehicle. It is known as good system for vehicles, from an efficiency, packaging, handling and safety. This paper describes motor and inverter technologies, system configuration and control algorithms for in-wheel type electric vehicle. It is necessary to control on an interrelation perspective because this system drives two motors at same time. In system design, IPMSM(Interior Permanent Magnet Synchronous Motor) including a wide operating range and high-speed rpm is used and flux weakening control is performed in constant power range. Under the torque command from the host controller, auto control box, inverter's output torque is calculated with using torque estimation technique and applied to actual vehicle driving system. It is verified that the configuration and the algorithm are suitable for the in-wheel motor system.

• ETRI Journal
• /
• 제40권1호
• /
• pp.101-110
• /
• 2018

In wireless positioning systems using range measurements non-line-of-sight (NLOS) links cause estimation errors. Several studies have attempted to improve the positioning performance by mitigating these NLOS errors. These studies, however, have focused on the performance of a dataset consisting of three or more links. Therefore, measurement errors induced by links are averaged, and a reliable link is not fully utilized in the dataset. This paper proposes a Link Reliability based on Range Measurement (LRRM) scheme, which specifies the relative reliability of each link using residuals. The link reliability becomes the input to a Link Residual Weighting (LRW) scheme, which is also proposed as a weighted positioning scheme. Moreover, LRRM and LRW constitute new turbo positioning, where the estimation errors are reduced considerably by iterative updates.

• 대한전기학회:학술대회논문집
• /
• 대한전기학회 2004년도 하계학술대회 논문집 B
• /
• pp.794-796
• /
• 2004

In the evaluation of performance for the algorithm of sensorless speed control, the ability of speed control in low speed range and starting is important points. First of all, stability of low speed control is highly required in the application which needs high performance in speed control. For this requirement, this paper represents simple method to estimate the rotor position by comparing reference linkage flux with it's estimation. In the estimation of linkage flux, this paper uses voltage-current model for increasing the performance of speed control in low speed range.

• 대한전기학회:학술대회논문집
• /
• 대한전기학회 2003년도 하계학술대회 논문집 D
• /
• pp.2088-2090
• /
• 2003

A practical recursive weighted least square(WLS) solution is proposed to solve the passive ranging problem. Apart from the previous works based on the extended Kalman filter(EKF), to ensure the convergency at long-range, the proposed scheme makes use of line-of-sight(LOS) rate instead of bearing information. The influence of LOS rate measurement errors is investigated and it is asserted that the WLS estimates contain bias and scale factor errors. Together with simple compensation algorithm, the estimation errors of proposed filter can be reduced dramatically.

• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 1996년도 Proceedings of the Korea Automatic Control Conference, 11th (KACC); Pohang, Korea; 24-26 Oct. 1996
• /
• pp.153-156
• /
• 1996

A new filtering algorithm for radar tracking is developed based on the fact that correct evaluation of the measurement error covariance can be made possible by doing it with respect to the Cartesian state vector. The new filter may be viewed as a modification of the extended Kalman filter where the variance of the range measurement errors is evaluated in an adaptive manner. The structure of the proposed filter allows sequential measurement processing scheme to be incorporated into the scheme, and this makes the resulting algorithm favorable in both estimation accuracy and computational efficiency.

• Journal of Ubiquitous Convergence Technology
• /
• 제2권2호
• /
• pp.78-87
• /
• 2008

Received signal strength indicator (RSSI) is used as one of the ranging techniques to locate dynamic sensor nodes in wireless sensor network. Before it can be used for position estimation, RSSI values must be converted to distances using path loss model. These distances among sensor nodes are combined using trilateration method to find position. This paper presents an idea which attempts to integrate both path loss model and trilateration as one algorithm without going through RSSI-distance conversion. This means it is not simply formulas combination but a whole new model was developed. Several advantages were found after integration: it is able to reduce processing load, and ensure that all values do not exceed the maximum range of 16-bit signed or unsigned numbers due to antilog operation in path loss model. The results also show that this method is able to reduce estimation error while inaccurate environmental parameters are used for RSSI-distance conversion.

• 한국지능시스템학회:학술대회논문집
• /
• 한국퍼지및지능시스템학회 2003년도 추계 학술대회 학술발표 논문집
• /
• pp.99-102
• /
• 2003

A new interacting multiple model (IMM) method using genetic algorithm (GA)-based intelligent input estimation(IIE) is proposed to track a maneuvering target. In the proposed method, the acceleration level for each sub-model is determined by IIE-the estimation of the unknown acceleration input by a fuzzy system using the relation between maneuvering filter residual and non-maneuvering one. The GA is utilized to optimize a fuzzy system fur a sub-model within a fixed range of acceleration input. Then, multiple models are composed of these fuzzy systems, which are optimized for different ranges of acceleration input. In computer simulation for an incoming ballistic missile, the tracking performance of the proposed method is compared with those of the input estimation(IE) technique and the adaptive interacting multiple model (AIMM) method.

• 대한전기학회:학술대회논문집
• /
• 대한전기학회 2004년도 추계학술대회 논문집 전기기기 및 에너지변환시스템부문
• /
• pp.176-178
• /
• 2004

Precise control of interior permanent magnet synchronous motor(IPMSM) over wide speed range is an engineering challenge. This paper considers the design and implementation of novel technique of speed estimation and control for IPMSM using hybrid intelligent control. The hybrid combination of neural network and adaptive fuzzy control will produce a powerful representation flexibility and numerical processing capability. Also, this paper is proposed speed control of IPMSM using adaptive neural network fuzzy(A-NNF) and estimation of speed using artificial neural network(ANN) controller. The back propagation neural network technique is used to provide a real time adaptive estimation of the motor speed.