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Showing 1-25 of 11,225 resultsfor "Index Terms":Online Estimation
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Online Parameter Estimation for Temporal Spectrum Sensing
We develop a computationally efficient online parameter estimation algorithm for temporal spectrum sensing of a cognitive radio channel using a hidden bivariate Markov model. The online estimator is based on a block-recursive parameter estimation algorithm developed by Rydén for hidden Markov models. This approach requires the score function only. We develop an efficient method for computing the s...Show More
An Improved Sensorless Control Scheme for PMSM with Online Parameter Estimation
2021 IEEE 16th Conference on Industrial Electronics and Applications (ICIEA)
Year: 2021 | Conference Paper |
Cited by: Papers (6)
This paper proposes an improved sliding mode observer based on super-twisting algorithm (STA-SMO) for sensorless control scheme of permanent magnet synchronous motors. An α-β axis stator current observer is built according to the back electromotive force (EMF) model after the back EMF error signal is obtained. The chattering phenomenon inherent in the traditional STA-SMO is eliminated by restricti...Show More
Online Parameter Estimation of the Polarization Curve of a Fuel Cell With Guaranteed Convergence Properties: Theoretical and Experimental Results
Carlo A. Beltrán;Alexey Bobtsov;Romeo Ortega;Diego Langarica-Córdoba;Rafael Cisneros;Luis H. Díaz-Saldierna
In this article, the problem of online parameter estimation of a proton exchange membrane fuel cell (PEMFC) polarization curve, that is, the static relation between the voltage and the current of the PEMFC is addressed and solved. The task of designing this estimator—even off-line—is complicated by the fact that the uncertain parameters enter the curve in a highly nonlinear fashion, namely in the ...Show More
Monte Carlo Methods for Channel, Phase Noise, and Frequency Offset Estimation With Unknown Noise Variances in OFDM Systems
FranÇois Septier;Yves Delignon;Atika Menhaj-Rivenq;Christelle Garnier
In this paper, we address the problem of orthogonal frequency-division multiplexing (OFDM) channel estimation in the presence of phase noise (PHN) and carrier frequency offset (CFO). In OFDM systems, PHN and CFO cause two effects: the common phase error (CPE) and the intercarrier interference (ICI) which severely degrade the accuracy of the channel estimate. In literature, several algorithms have ...Show More
Recursive Nonparametric Estimation for Time Series
This paper considers online kernel estimation for both short- and long-range dependent time series data. Utilizing the predictive dependence measure of Wu, we carefully study the asymptotic properties of recursive kernel density and regression estimators for a general class of stationary processes. In particular, we prove that the proposed estimators have the asymptotic normality and the correspon...Show More
An on-line DC-link Capacitance Estimation method for Motor Drive System Based on Intermittent Active Control Strategy
2021 IEEE Energy Conversion Congress and Exposition (ECCE)
Year: 2021 | Conference Paper |
Cited by: Papers (4)
The condition monitoring of the direct-current (DC)-link capacitors is critical for operating reliability of the inverter-based motor drive system. Therefore, in industry applications, reliable preventive maintenance of the power electronics devices in motor drive systems is required. The previous proposed DC-link capacitance monitoring technologies are inadaptable for applications due to the requ...Show More
Inertia constant and damping coefficient are the most important parameters in the frequency and stability studies of interconnected power systems. Online determination of such parameters has a great implementation in power system operation, security, and control. In this paper, a new method is proposed for online estimation of both the inertia and damping constants. The proposed method makes use o...Show More
Online Parameter Estimation Technique for Adaptive Control Applications of Interior PM Synchronous Motor Drives
Dong Quang Dang;Muhammad Saad Rafaq;Han Ho Choi;Jin-Woo Jung
This paper proposes an online parameter estimation method based on a discrete-time dynamic model for the interior permanent-magnet synchronous motors (IPMSMs). The proposed estimation technique, which takes advantage of the difference in dynamics of motor parameters, consists of two affine projection algorithms. The first one is designed to accurately estimate the stator inductances, whereas the s...Show More
On-line parameter estimation for improved sensorless control of synchronous motors
2012 XXth International Conference on Electrical Machines
Year: 2012 | Conference Paper |
Cited by: Papers (4)
An on-line synchronous motor parameter estimation technique is introduced. The motor is driven sensor-lessly with a Kalman filter. A second Kalman filter, that works in parallel with the main one, estimates the motor model parameters. Thanks to the parameter estimation, the accuracy of the Kalman filter estimations of position and speed increase and thus the global performance of the drive. Theore...Show More
Online Estimation Method of Badminton Players' Grip Position Error Based on Particle Filtering
2021 6th International Conference on Smart Grid and Electrical Automation (ICSGEA)
Year: 2021 | Conference Paper |
Cited by: Papers (1)
In order to solve the problems of low accuracy and long time consumption of traditional badminton players' grip position error estimation methods, a new online estimation method of badminton players' grip position error based on particle filter was proposed in this paper. Infrared array sensor is used to collect badminton players' grip posture images, and the collected images are de-noised and seg...Show More
Robust Online CSI Estimation in a Complex Environment
Channel state information (CSI) estimation is one of the key techniques for improving the performance of wireless communication systems. Meanwhile, the fifth generation wireless communication systems require higher accuracy and lower latency for CSI estimation. In this paper, the methods of noise modeling and online learning are combined to improve the accuracy and reduce the latency. The complex ...Show More
An Online Estimation Approach for the Aggregate Model of District Heating Network
2023 IEEE 7th Conference on Energy Internet and Energy System Integration (EI2)
Year: 2023 | Conference Paper |
An accurate yet concise district heating network (DHN) model is essential for the dispatch of the integrated energy system (IES). Owing to the changes in the operation conditions, such as the topology changes and mass flow rate adjustments, the parameters of the DHN model may change during operation. Hence, the accurate online parameter estimation of the DHN is the basis of the real-time analysis ...Show More
On-Line State Estimation of 2-qubit Quantum Systems
2019 27th Mediterranean Conference on Control and Automation (MED)
Year: 2019 | Conference Paper |
In this paper, the online estimation of 2-qubit states is studied based on the quantum continuous weak measurement and compressed sensing (CS) theory. The stochastic master equation is used to describe the dynamic evolution of the system. The weak measurement operator acting on the system and the dynamic equation of the measurement operator over time are derived. The number of measurements is redu...Show More
Current Injection-Based Online Parameter and VSI Nonlinearity Estimation for PMSM Drives Using Current and Voltage DC Components
To develop a high-performance and reliable permanent-magnet synchronous machine (PMSM) drive for electric vehicle (EV) applications, accurate knowledge of the PMSM parameters is of significance. This paper investigates online estimation of PMSM parameters and voltage source inverter (VSI) nonlinearity using current injection method in which magnetic saturation is also considered. First, a novel dc...Show More
Blind estimation of hidden Markov models
1997 IEEE International Symposium on Circuits and Systems (ISCAS)
Year: 1997 | Conference Paper |
In this paper, an on-line blind parameter estimation scheme for hidden Markov models (HMMs) is developed. The parameters to be estimated in the paper include state transition probabilities, observation vector and measurement noise density. Some implementation aspects of the proposed blind estimation algorithm are discussed. Computer simulations show that our algorithm can converge to the true valu...Show More
Enhancement of parameter estimation accuracy using current shaping in PM machine drive
2015 9th International Conference on Power Electronics and ECCE Asia (ICPE-ECCE Asia)
Year: 2015 | Conference Paper |
Cited by: Papers (2)
The accurate value of the electric machine parameters is required to design an efficient current controller and torque controller in the permanent magnet synchronous machine (PMSM) drive system. The values of these parameters are not constant but vary with the operation condition. The stator winding resistance and rotor flux linkage are affected by the temperature. Inductances are changed accordin...Show More
Time Delay Control of an AUV with Unknown Dynamics Using Position Measurements
2019 27th Iranian Conference on Electrical Engineering (ICEE)
Year: 2019 | Conference Paper |
In this paper, a control system is designed for dynamic positioning of an AUV with unknown dynamics, subject to external disturbances and without velocity measurements. The uncertainties and external disturbances are compensated for by online estimation based on time delay estimation method. To obtain AUV velocities, a robust exact differentiator is considered such that high sampling rates for vel...Show More
Exam Cheating Detection System with Multiple-Human Pose Estimation
2021 IEEE International Conference on Computing (ICOCO)
Year: 2021 | Conference Paper |
Cited by: Papers (4)
Cheating in exams is a persistent problem that contributes to academic dishonesty. In this paper we explore a variety of related work proposed as a solution for exam cheating, then we propose an exam cheating detection system that works for both on-site and online examinations. The proposed system applies Human Pose Estimation that includes both single-user and multiple-user tracking algorithms. B...Show More
Sensor bias jump detection and estimation with range only measurements
2015 IEEE International Conference on Information and Automation
Year: 2015 | Conference Paper |
A target can be positioned by wireless communication sensors. In practical system, the range based sensors may have biased measurements. The biases are mostly constant value, but they may jump abruptly in some special scenarios. An on-line bias change detection and estimation algorithm is presented in this paper. This algorithm can detect the jump bias based on Chi-Square Test, and then estimate t...Show More
A comparative study of various methods for parameter estimation of PMSM
2017 International Conference on Energy, Communication, Data Analytics and Soft Computing (ICECDS)
Year: 2017 | Conference Paper |
Cited by: Papers (7)
Parameter of machine can change due to temperature, saturation effects and other environmental effects. So the estimation of various parameters is very essential for the accurate operation of control algorithm for the machine. This paper discusses various methods of parameter estimation for permanent magnet synchronous motor (PMSM). PMSM is selected due to high performance, high efficiency, high t...Show More
Electrolytic Capacitor Degradation Monitoring using an On-line Parameter Estimation Scheme involving Sliding Mode Differentiators and a Kalman Filter
2019 21st European Conference on Power Electronics and Applications (EPE '19 ECCE Europe)
Year: 2019 | Conference Paper |
Cited by: Papers (4)
An indication of electrolytic capacitor gradual degradation may be obtained by observing an increase in the equivalent series resistance (ESR) and a decrease in capacitance over time. On-line condition monitoring of these two electrical parameters allows for early detection of the capacitor ageing that can reduce catastrophic failure and their costly consequences. In this paper, a parameter estima...Show More
Robust adaptive finite-time parameter estimation for linearly parameterized nonlinear systems
Jing Na;Muhammad Nasiruddin Mahyuddin;Guido Herrmann;Xuemei Ren
Proceedings of the 32nd Chinese Control Conference
Year: 2013 | Conference Paper |
Cited by: Papers (6)
This paper studies a novel adaptive parameter estimation framework for linearly parameterized nonlinear systems. Appropriate parameter error information is derived by defining auxiliary filtered variables and used to drive the parameter adaptation, which guarantees exponential error convergence. The proposed method is further improved via a sliding mode approach to achieve finite-time (FT) error c...Show More
An Online Compensation Method of VSI Nonlinearity for Dual Three-Phase PMSM Drives Using Current Injection
Compensation of voltage-source-inverter (VSI) nonlinearity is of great importance in parameter identification and position sensorless control method for motor drives. In this letter, a simple online compensation method has been proposed for the dual three-phase permanent-magnet synchronous motor (PMSM) drives. The key is to observe the change of voltage references contained VSI nonlinearity after ...Show More
On-line parameter estimation of an induction machine using a recursive least-squares algorithm with multiple time-varying forgetting factors
2010 IEEE International Conference on Power and Energy
Year: 2010 | Conference Paper |
Cited by: Papers (14)
This paper proposes a recursive least-squares (RLS) algorithm with multiple time-varying forgetting factors for on-line parameter estimation of an induction machine (IM). The regressive mathematical model of the IM is also introduced which is simple and appropriate for online parameter estimation. The estimator inputs using the proposed RLS algorithm are easily measurable variables such as the sta...Show More
Neural-network-based Power System State Estimation with Extended Observability
This paper proposes a neural-network-based state estimation (NNSE) method that aims to achieve higher time efficiency, improved robustness against noise, and extended observability when compared with the conventional weighted least squares (WLS) state estimation method. NNSE consists of two parts, the linear state estimation neural network (LSE-net) and the unobservable state estimation neural net...Show More
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