Adaptive Observer of Rotor Position and Flux for Salient Synchronous Motor

2019 ◽  
Vol 20 (2) ◽  
pp. 114-121
Author(s):  
D. N. Bazylev ◽  
A. A. Pyrkin ◽  
A. A. Bobtsov
Keyword(s):  
Permanent Magnets ◽  
Adaptive Estimation ◽  
Angular Position ◽  
Regression Function ◽  
Estimation Algorithm ◽  
Synchronous Motor ◽  
Position Estimation ◽  
Adaptive Observer ◽  
Estimation Errors ◽  
Persistent Excitation

An algorithm of adaptive estimation of rotor flux and angular position for the salient synchronous motor with permanent magnets is presented. A new nonlinear parameterization of the dynamic motor model is proposed. Due to this parameterization the problem of position estimation is translated to the task of identification of unknown constant parameters. During the synthesis of estimation algorithm the currents and voltages of the stator windings, as well as the rotor speed, are assumed to be known signals. Two variants of the adaptive observer based on the standard gradient estimator and the algorithm of the dynamic extension of the regressor are proposed. It is proved that the both versions of the observer provide global exponential convergence of estimation errors to zero if the corresponding regression function satisfies the persistent excitation condition. Also, the latter version of the observer provides global asymptotic convergence if the regression function is square integrable. The results of numerical simulation demonstrate that the algorithm with the dynamic extension of the regressor provides a better quality of estimation transient processes in comparison with the standard gradient estimator.

scholarly journals Adaptive observer of magnetic flux, angular position and velocity for synchronous motor with permanent magnets

2021 ◽  
Vol 1864 (1) ◽  
pp. 012029
Author(s):  
A. Vedyakov ◽  
A. A. Pyrkin ◽  
V. V. Bespalov ◽  
V. A. Antipov ◽  
D. A. Cherginets
Keyword(s):  
Magnetic Flux ◽  
Permanent Magnets ◽  
Angular Position ◽  
Synchronous Motor ◽  
Adaptive Observer

Adaptive Flux Observer for Nonsalient PMSM with Noised Measurements of the Current and Voltage

2019 ◽  
Vol 20 (4) ◽  
pp. 215-218 ◽  
Author(s):  
A. A. 1. Pyrkin ◽  
A. A. Bobtsov ◽  
A. A. Vedyakov ◽  
D. N. Bazylev ◽  
M. M. Sinetova
Keyword(s):  
Measurement Errors ◽  
Adaptive Estimation ◽  
Permanent Magnet Synchronous Motor ◽  
Regression Function ◽  
Estimation Errors ◽  
Persistent Excitation ◽  
Flux Observer ◽  
Nonlinear Parameterization ◽  
Global Exponential Convergence ◽  
Drive Model

An algorithm of adaptive estimation of the magnetic flux for the non-salient permanent magnet synchronous motor (PMSM) for the case when measurable electrical signals are corrupted by a constant offset is presented. A new nonlinear parameterization of the electric drive model based on dynamical regressor extension and mixing (DREM) procedure is proposed. Due to this parameterization the problem of flux estimation is translated to the auxiliary task of identification of unknown constant parameters related to measurement errors. It is proved that the flux observer provides global exponential convergence of estimation errors to zero if the corresponding regression function satisfies the persistent excitation condition. Also, the observer provides global asymptotic convergence if the regression function is square integrable. In comparison with known analogues this paper gives a constructive way of the flux reconstruction for a nonsalient PMSM with guaranteed performance (monotonicity, convergence rate regulation) and, from other hand, a straightforwardly easy implementation of the proposed observer to embedded systems.

A new reaching law for sliding mode observer of controllable excitation linear synchronous motor

2021 ◽  
pp. 014233122110320
Author(s):  
Xiaolei Shi ◽  
Yipeng Lan ◽  
Yunpeng Sun ◽  
Cheng Lei
Keyword(s):  
Sliding Mode ◽  
Dynamic Performance ◽  
Angular Position ◽  
Lyapunov Stability Theory ◽  
Synchronous Motor ◽  
Position Estimation ◽  
Sliding Mode Observer ◽  
Sigmoid Function ◽  
Reaching Law ◽  
Linear Synchronous Motor

This paper presents a sliding mode observer (SMO) with new reaching law (NRL) for observing the real-time linear speed of a controllable excitation linear synchronous motor (CELSM). For the purpose of balancing the dilemma between the rapidity requirement of dynamic performance and the chattering reduction on sliding mode surface, the proposed SMO with NRL optimizes the reaching way of the conventional constant rate reaching law (CRRL) to the sliding mode surface by connecting the reaching process with system states and the sliding mode surface. The NRL is based on sigmoid function and power function, with proper options of exponential term and power term, the NRL is capable of eliminating the effect of chattering on accuracy of the angular position estimation and speed estimation. Compared with conventional CRRL, the SMO with NRL achieves suppressing the chattering phenomenon and tracking the transient process rapidly and accurately. The stability analysis is given to prove the convergence of the SMO through the Lyapunov stability theory. Simulation and experimental results show the effectiveness of the proposed NRL method.

scholarly journals Position Estimation of a PMSM in an Electric Propulsion Ship System Based on High-Frequency Injection

Electronics ◽  
2020 ◽  
Vol 9 (2) ◽  
pp. 276 ◽  
Author(s):  
Hongfen Bai
Keyword(s):  
Permanent Magnet ◽  
High Frequency ◽  
Electric Propulsion ◽  
Permanent Magnet Synchronous Motor ◽  
Estimation Algorithm ◽  
Synchronous Motor ◽  
Position Estimation ◽  
Second Order ◽  
Application Range ◽  
Rotor Position

To improve the operating performance of electric propulsion ships, the permanent magnet synchronous motor is commonly used as the propulsion motor. Additionally, position estimation without sensors can further improve the application range of the propulsion motor and the estimated results can represent the redundancy of measured values from mechanical sensors. In this paper, the high-frequency (HF) injection algorithm combined with the second-order generalized integrator (SOGI) is presented on the basis of analyzing the structure of the electric propulsion ship and the vector control of the motors. The position and rotor speed were estimated accurately by the approximate calculation of q-axis currents directly related to the rotor position. Moreover, the harmonics in the estimated position were effectively reduced by the introduction of the second-order generalized integrator. Then, the rotor position estimation algorithm was verified in MATLAB/Simulink by choosing different low speeds including speed reversal, increasing speed, and increasing load torque. Finally, the correctness of the proposed improved high-frequency injection algorithm based on the second-order generalized integrator was verified by the experimental propulsion permanent magnet synchronous motor (PMSM) system at low speed.

scholarly journals Sensorless vector control of a permanent magnet synchronous motor

2019 ◽  
Vol 91 ◽  
pp. 01007 ◽  
Author(s):  
Ruslan Zhiligotov ◽  
Vyacheslav Shestakov ◽  
Vladymyr Sosnin ◽  
Evgeniy Popkov
Keyword(s):  
Control System ◽  
Vector Control ◽  
Permanent Magnets ◽  
Permanent Magnet Synchronous Motor ◽  
Synchronous Motor ◽  
Adaptive Observer ◽  
Current Position ◽  
Sensorless Vector Control ◽  
Common Control ◽  
Vector Control System

The most common control system for a synchronous motor with permanent magnets is a vector control system. The construction of such a system has a number of difficulties, one of them is the need to have information about the current position of the rotor. Data on the position of the rotor can be obtained using sensors, or include a supervisor in the control system. The article describes an adaptive observer of the position and speed of the rotor of a synchronous motor with permanent magnets. This observer is used in the system of sensorless vector control of the electric drive. The presented version of the observer of the engine state is realized by creating a model in the Matlab Simulink software package. The results of experimental verification of the presented observer at the stand with the use of an engine with a power of 200 W are shown. The aim of the work is to develop an observer that is stable to changing drive parameters. This is achieved by using a relay unit in the view of the observer, which implements the slip mode.

scholarly journals Aircraft position estimation using angle of arrival of received radar signals

2020 ◽  
Vol 9 (6) ◽  
pp. 2380-2387
Author(s):  
Freeha Majeed Amjad ◽  
Ahmad Zuri Sha'ameri ◽  
Kamaludin Mohamad Yusof ◽  
Paulson Eberechukwu
Keyword(s):  
Antenna Arrays ◽  
Estimation Algorithm ◽  
Position Estimation ◽  
Computational Time ◽  
Angle Of Arrival ◽  
Estimation Errors ◽  
Multiple Signal Classification ◽  
Active Research ◽  
Increasing Demand ◽  
Bearing Number

With increasing demand of air traffic, there is a need to optimize the use of available airspace. Effective utilization of airspace relies on quality of aircraft surveillance. Active research is carried out for enhancements in surveillance techniques and various methods are evaluated for future use. This paper evaluates the use of multiple signal classification (MUSIC) based angle of arrival (AOA) estimation along with multiangulation for locating aircrafts from their electromagnetic wave emission. The performance evaluation of the system is presented by evaluating the AOA estimation errors and position estimation (PE) errors. The errors are evaluated by comparing the estimated value to the actual value. An analysis on the system parameters, AOA error and PE error are presented in the end. AOA errors are affected by the AOA value (emitter bearing), number of array elements, SNR and resolution of AOA estimation algorithm. Errors in AOA estimation lead to PE errors. The simulation results show small errors for short ranges. The system performance can be improved at the expense of computational time by using higher MUSIC resolution and larger antenna arrays

scholarly journals Angle Tracking Observer with Improved Accuracy for Resolver-to-Digital Conversion

Symmetry ◽  
2019 ◽  
Vol 11 (11) ◽  
pp. 1347 ◽  
Author(s):  
Haoye Qin ◽  
Zhong Wu
Keyword(s):  
Phase Error ◽  
Angular Position ◽  
Position Estimation ◽  
High Order ◽  
Phase Detector ◽  
Type Ii ◽  
Digital Conversion ◽  
Estimation Errors ◽  
Angle Tracking ◽  
Acceleration Signals

A resolver is an absolute shaft sensor which outputs pair signals with ortho-symmetric amplitudes. Ideally, they are sinusoidal and cosinusoidal functions of the shaft angle. In order to demodulate angular position and velocity from resolver signals, resolver-to-digital conversion (RDC) is necessary. In software-based RDC, most algorithms mainly employ a phase-locked loop (PLL)-based angle tracking observer (ATO) to form a type-II system. PLL can track the detected angle by regulating the phase error from the phase detector which depends on the feature of orthogonal symmetry in the resolver outputs. However, a type-II system will result in either steady-state errors or cumulative errors in the estimation of angular position with constant accelerations. Although type-III ATOs can suppress these errors, they are still vulnerable to high-order acceleration signals. In this paper, an improved PLL-based ATO with a compensation model is proposed. By using dynamic compensation, the proposed ATO becomes a type-IV system and can reduce position estimation errors for high-order acceleration signals. In addition, the parameters of ATO can be tuned according to the bandwidth, noise level and capability of error suppression. Simulation and experimental results demonstrate the effectiveness of the proposed method.

Robust H∞ gain neuro-adaptive observer design for nonlinear uncertain systems

2018 ◽  
Vol 41 (8) ◽  
pp. 2293-2309
Author(s):  
Krifa Abdelkader ◽  
Bouzrara Kais
Keyword(s):  
Nonlinear Approximation ◽  
The State ◽  
Observer Design ◽  
Adaptive Observer ◽  
Projection Algorithm ◽  
Linear Matrix ◽  
Positive Real ◽  
Unknown Parameters ◽  
Estimation Errors ◽  
Persistent Excitation

To guarantee convergent state estimates and exact approximations, it is highly desirable that observers can independently dominate the effects of unmodelled dynamics. Based on adaptive nonlinear approximation, this paper presents a robust H∞ gain neuro-adaptive observer (R H∞GNAO) design methodology for a large class of uncertain nonlinear systems in the presence of time-varying unknown parameters with bounded external disturbances on the state vector and on the output of the original system. The proposed R H∞GNAO incorporates radial basis function neural networks (RBFNNs) to approximate the unknown nonlinearities in the uncertain system. The weight dynamics of every RBFNN are adjusted online by using an adaptive projection algorithm. The asymptotic convergence of the state and parameter estimation errors is achieved by using Lyapunov cogitation under a well-defined persistent excitation condition, and without recourse to the strictly positive real condition. The repercussions of unknown disturbances are reduced by integrating an H∞ gain performance criterion into the proposed estimation approach. The condition imposed by this proposed observer approach, such that all estimated signals are uniformly ultimately bounded, is expressed in the form of the linear matrix inequality problem and warrants the demanded performances. To evaluate the performance of the proposed observer, various simulations are presented.

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