The Experts below are selected from a list of 1512 Experts worldwide ranked by ideXlab platform
Kan Liu - One of the best experts on this subject based on the ideXlab platform.
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Position-Offset-Based Parameter Estimation Using the Adaline NN for Condition Monitoring of Permanent-Magnet Synchronous Machines
IEEE Transactions on Industrial Electronics, 2015Co-Authors: Kan Liu, Zi-qiang ZhuAbstract:This paper proposes how to use the addition of Rotor position offsets as perturbation signals for the parameter estimation of permanent-magnet synchronous machines (PMSMs), which can be used for the condition monitoring of Rotor permanent magnet and stator winding. During the proposed estimation, two small position offsets are intentionally added into the drive system, and the resulting voltage variation will be recorded for the estimation of Rotor Flux Linkage. With the aid from estimated Rotor Flux Linkage, the stator winding resistance can be subsequently estimated at steady state. This method is experimentally verified on two prototype PMSMs (150 W and 3 kW, respectively) and shows good performance in monitoring the variation of Rotor Flux Linkage and winding resistance.
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online estimation of the Rotor Flux Linkage and voltage source inverter nonlinearity in permanent magnet synchronous machine drives
IEEE Transactions on Power Electronics, 2014Co-Authors: Kan Liu, Z Q ZhuAbstract:This paper proposes a method for online estimating the Rotor Flux Linkage and voltage-source inverter (VSI) nonlinearity of permanent magnet synchronous machine (PMSM) drives. Thermocouples are employed for measuring the temperature variation of the stator winding in order to obtain the actual value of stator winding resistance. An Adaline estimator is used for online estimation of distorted voltage Vdead due to VSI nonlinearity. Both are subsequently used for the estimation of the Rotor Flux Linkage. The proposed method is experimentally validated on a PMSM drive system and shows good performance in tracking the variation of the Rotor Flux Linkage and compensating the VSI nonlinearity.
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Influence of Nonideal Voltage Measurement on Parameter Estimation in Permanent-Magnet Synchronous Machines
IEEE Transactions on Industrial Electronics, 2012Co-Authors: Kan Liu, Zi-qiang Zhu, Qiao Zhang, Jing ZhangAbstract:This paper investigates the influence of nonideal voltage measurements on the parameter estimation of permanent-magnet synchronous machines (PMSMs). The influence of nonideal voltage measurements, such as the dc bus voltage drop, zero shift in the amplifier, and voltage source inverter nonlinearities, on the estimation of different machine parameters is investigated by theoretical and experimental analysis. For analysis, a model-reference-adaptive-system-based estimator is first described for the parameter estimation of the q-axis inductance, stator winding resistance, and Rotor Flux Linkage. The estimator is then applied to a prototype surface-mounted PMSM to investigate the influence of nonideal voltage measurement on the estimation of various machine parameter values. It shows that, at low speed, the inverter nonlinearity compensation has significant influence on both the Rotor Flux Linkage and winding resistance estimations while, at high speed, it has significant influence only on the winding resistance estimation and has negligible influence on the Rotor Flux Linkage estimation. In addition, the inverter nonlinearity compensation will not influence the q-axis inductance estimation when it is under id = 0 control. However, the dc bus voltage drop due to the load variation and zero shift in the amplifier will significantly influence the q-axis inductance estimation.
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BIC-TA - Multi-parameter estimation of non-salient pole permanent magnet synchronous machines by using evolutionary algorithms
2010 IEEE Fifth International Conference on Bio-Inspired Computing: Theories and Applications (BIC-TA), 2010Co-Authors: Kan Liu, Zi-qiang Zhu, Qiao Zhang, Jing Zhang, Anwen ShenAbstract:This paper describes how to apply evolutionary algorithms (EA) for multi-parameter estimation of non-salient pole permanent magnet synchronous machines (PMSM). The encoding of estimated parameters is firstly described and the design of a penalty function associated with a proposed error analysis for PMSM multi-parameter estimation is then introduced. The PMSM stator winding resistance, dq-axis inductances and Rotor Flux Linkage can be estimated by maximizing the proposed penalty function through evolutionary algorithms such as immune clonal algorithm (ICA), quantum genetic algorithm (QGA) and genetic algorithm (GA). The experimental results show that the proposed strategy has good convergence in simultaneously estimating winding resistance, dq-axis inductances and Rotor Flux Linkage. In addition, the convergence speed of ICA in estimation is compared with GA and QGA, which verifies that the ICA has better performances in global searching. The ability of proposed method for tracking the parameter variation is verified by winding resistance step change and temperature variation experiments at last.
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Influence of inverter nonlinearity on parameter estimation in permanent magnet synchronous machines
The XIX International Conference on Electrical Machines - ICEM 2010, 2010Co-Authors: Kan Liu, Zi-qiang Zhu, Qiao Zhang, Jing Zhang, Anwen ShenAbstract:This paper investigates the influence of inverter nonlinearity on the parameter estimation in permanent magnet synchronous machines (PMSM). An estimator based on model reference adaptive system (MRAS) is firstly described for simultaneously estimating the stator winding resistance and Rotor Flux Linkage, together with injection of a pulse of i d
Gorazd Štumberger - One of the best experts on this subject based on the ideXlab platform.
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Induction machine control for a wide range of drive requirements
Energies, 2019Co-Authors: B. Grcar, Anton Hofer, Gorazd ŠtumbergerAbstract:In this paper, a method for induction machine (IM) torque/speed tracking control derived from the 3-D non-holonomic integrator including drift terms is proposed. The proposition builds on a previous result derived in the form of a single loop non-linear state controller providing implicit Rotor Flux Linkage vector tracking. This concept was appropriate only for piecewise constant references and assured minimal norm of the stator current vector during steady-states. The extended proposition introduces a second control loop for the Rotor Flux Linkage vector magnitude that can be either constant, programmed, or optimized to achieve either maximum torque per amp ratio or high dynamic response. It should be emphasized that the same structure of the controller can be used either for torque control or for speed control. Additionally, it turns out that the proposed controller can be easily adapted to meet different objectives posed on the drive system. The introduced control concept assures stability of the closed loop system and significantly improves tracking performance for bounded but arbitrary torque/speed references. Moreover, the singularity problem near zero Rotor Flux Linkage vector length is easily avoided. The presented analyses include nonlinear effects due to magnetic saturation. The overall IM control scheme includes cascaded high-gain current controllers based on measured electrical and mechanical quantities together with a Rotor Flux Linkage vector estimator. Simulation and experimental results illustrate the main characteristics of the proposed control.
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IM Torque Control Schemes Based on Stator Current Vector
IEEE Transactions on Industrial Electronics, 2014Co-Authors: B. Grcar, Gorazd Štumberger, Anton Hofer, Peter CafutaAbstract:This paper proposes an induction machine torque control derived from the model in the stator current vector reference frame. The required torque is produced by simultaneously manipulating the magnitude and the rotation speed of the stator current vector, thus forcing the Rotor Flux Linkage vector to change implicitly in such a way that overall stability is preserved. Additional control features include maximal torque-per-ampere ratio in steady state and almost perfect command tracking even if the machine is magnetically saturated. The control adopts a cascaded structure and is based on a partial dynamic inversion of the reduced model that assures existence and uniqueness of the inverse mapping between the required torque, the Rotor Flux Linkage vector, and the stator current vector. Singularity at zero Rotor Flux Linkage represents no restriction for the control performance in the admissible machine operating range. The implementation of the proposed control requires the estimation of the torque-producing Rotor Flux component and cascaded stator current controllers. Experimental results confirm the key expectations and show the potential and benefits of the proposed control schemes.
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Non-Holonomy in Induction Machine Torque Control
IEEE Transactions on Control Systems Technology, 2011Co-Authors: B. Grcar, Gorazd Štumberger, Peter Cafuta, Aleksandar M. Stankovic, Anton HoferAbstract:In this brief, induction machine (IM) torque control is studied as an example of a 3-D non-holonomic integrator including drift terms. By expanding Brockett's controller derived for the driftless systems, a control structure is proposed that provides simultaneous modulation of both the amplitude and the frequency of the sinusoidal stator current vector. Although not explicitly controlled or programmed, the Rotor Flux Linkage vector is implicitly forced to track natural periodic orbits satisfying non-holonomic constraints of the IM. The proposed control assures high dynamics in the torque response, maximal torque per amp ratio during transients and in steady-state and global asymptotic stability. The overall IM control scheme includes cascaded high-gain current controllers based on measured electrical and mechanical quantities together with Rotor Flux Linkage vector estimator. Simulation and experimental results illustrate the main characteristics of the proposed control.
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Torque control of an induction machine based on partial dynamic inversion
2009 Chinese Control and Decision Conference, 2009Co-Authors: B. Grcar, Gorazd Štumberger, Peter Cafuta, Jozef Ritonja, Anton HoferAbstract:In the paper induction machine (IM) torque control is studied as an example of a three-dimensional non-holonomic integrator that includes drift terms. By expanding Brockett's controller derived for the driftless systems, a control structure is proposed that guarantees natural adjustment of both the amplitude and the frequency modulation of the sinusoidal stator current vector. The Rotor Flux Linkage vector is implicitly forced to track natural periodic orbits satisfying non-holonomic constraints of the IM. Main features of the proposed control include fast dynamics of the torque response, maximal torque per amp ratio for nominal parameters, exponential stability, and robustness regarding expected parameter variations. The overall IM control scheme requires cascaded high-gain current controllers together with Rotor Flux Linkage vector estimation. Simulation and experimental results illustrate the main characteristics of the proposed control with the emphasis on the quality of the generated machine torque and estimated Rotor Flux Linkage orbits.
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Rotor Flux Linkage oriented control of induction motor with included magnetic saturation
IEE Proceedings - Electric Power Applications, 2005Co-Authors: P. Ljusev, Gorazd Štumberger, Drago DolinarAbstract:The vector control of an induction motor in the Rotor Flux Linkage oriented reference frame, with magnetic saturation included, is considered. The magnetic saturation is represented by the non-linear magnetising curve of the iron core. The Rotor Flux Linkage model and the voltage decoupling in the traditional vector control scheme are modified to account for the magnetic saturation of the iron core. The mixed ‘stator current – Rotor Flux Linkage’ model of the saturated induction machine is used in the control design, simulation and experimental realisation. Experimental results show that the proposed control with the included saturation offers a number of benefits, such as reduced stator current and smaller speed tracking error.
Zi-qiang Zhu - One of the best experts on this subject based on the ideXlab platform.
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Position-Offset-Based Parameter Estimation Using the Adaline NN for Condition Monitoring of Permanent-Magnet Synchronous Machines
IEEE Transactions on Industrial Electronics, 2015Co-Authors: Kan Liu, Zi-qiang ZhuAbstract:This paper proposes how to use the addition of Rotor position offsets as perturbation signals for the parameter estimation of permanent-magnet synchronous machines (PMSMs), which can be used for the condition monitoring of Rotor permanent magnet and stator winding. During the proposed estimation, two small position offsets are intentionally added into the drive system, and the resulting voltage variation will be recorded for the estimation of Rotor Flux Linkage. With the aid from estimated Rotor Flux Linkage, the stator winding resistance can be subsequently estimated at steady state. This method is experimentally verified on two prototype PMSMs (150 W and 3 kW, respectively) and shows good performance in monitoring the variation of Rotor Flux Linkage and winding resistance.
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Influence of Nonideal Voltage Measurement on Parameter Estimation in Permanent-Magnet Synchronous Machines
IEEE Transactions on Industrial Electronics, 2012Co-Authors: Kan Liu, Zi-qiang Zhu, Qiao Zhang, Jing ZhangAbstract:This paper investigates the influence of nonideal voltage measurements on the parameter estimation of permanent-magnet synchronous machines (PMSMs). The influence of nonideal voltage measurements, such as the dc bus voltage drop, zero shift in the amplifier, and voltage source inverter nonlinearities, on the estimation of different machine parameters is investigated by theoretical and experimental analysis. For analysis, a model-reference-adaptive-system-based estimator is first described for the parameter estimation of the q-axis inductance, stator winding resistance, and Rotor Flux Linkage. The estimator is then applied to a prototype surface-mounted PMSM to investigate the influence of nonideal voltage measurement on the estimation of various machine parameter values. It shows that, at low speed, the inverter nonlinearity compensation has significant influence on both the Rotor Flux Linkage and winding resistance estimations while, at high speed, it has significant influence only on the winding resistance estimation and has negligible influence on the Rotor Flux Linkage estimation. In addition, the inverter nonlinearity compensation will not influence the q-axis inductance estimation when it is under id = 0 control. However, the dc bus voltage drop due to the load variation and zero shift in the amplifier will significantly influence the q-axis inductance estimation.
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BIC-TA - Multi-parameter estimation of non-salient pole permanent magnet synchronous machines by using evolutionary algorithms
2010 IEEE Fifth International Conference on Bio-Inspired Computing: Theories and Applications (BIC-TA), 2010Co-Authors: Kan Liu, Zi-qiang Zhu, Qiao Zhang, Jing Zhang, Anwen ShenAbstract:This paper describes how to apply evolutionary algorithms (EA) for multi-parameter estimation of non-salient pole permanent magnet synchronous machines (PMSM). The encoding of estimated parameters is firstly described and the design of a penalty function associated with a proposed error analysis for PMSM multi-parameter estimation is then introduced. The PMSM stator winding resistance, dq-axis inductances and Rotor Flux Linkage can be estimated by maximizing the proposed penalty function through evolutionary algorithms such as immune clonal algorithm (ICA), quantum genetic algorithm (QGA) and genetic algorithm (GA). The experimental results show that the proposed strategy has good convergence in simultaneously estimating winding resistance, dq-axis inductances and Rotor Flux Linkage. In addition, the convergence speed of ICA in estimation is compared with GA and QGA, which verifies that the ICA has better performances in global searching. The ability of proposed method for tracking the parameter variation is verified by winding resistance step change and temperature variation experiments at last.
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Influence of inverter nonlinearity on parameter estimation in permanent magnet synchronous machines
The XIX International Conference on Electrical Machines - ICEM 2010, 2010Co-Authors: Kan Liu, Zi-qiang Zhu, Qiao Zhang, Jing Zhang, Anwen ShenAbstract:This paper investigates the influence of inverter nonlinearity on the parameter estimation in permanent magnet synchronous machines (PMSM). An estimator based on model reference adaptive system (MRAS) is firstly described for simultaneously estimating the stator winding resistance and Rotor Flux Linkage, together with injection of a pulse of i d
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Modeling and simulation of parameter identification for PMSM based on EKF
2010 International Conference on Computer Mechatronics Control and Electronic Engineering, 2010Co-Authors: Xiaoliang Jiang, Pindong Sun, Zi-qiang ZhuAbstract:In this paper, on the basis of vector control, Extended Kalman Filter (EKF) was employed to estimate stator winding resistance, Rotor Flux-Linkage due to permanent magnet and temperature rise in stator winding and Rotor magnet of AC PMSM. Identification model of different parameter was established in rotating reference frame and MATLAB/SIMULINK was used to do simulation experiments. The theoretical analysis and identification models were confirmed to be correct and effective by the simulation results.
Heath F. Hofmann - One of the best experts on this subject based on the ideXlab platform.
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Rotor Resistance Estimation for Induction Machines Using Carrier Signal Injection With Minimized Torque Ripple
IEEE Transactions on Energy Conversion, 2019Co-Authors: Amin Hasanzadeh, David M. Reed, Heath F. HofmannAbstract:This paper presents a technique for estimating the Rotor resistance of an induction machine over the machine's entire speed and torque range. This technique is based on injecting a relatively low-frequency carrier signal into the reference of the Rotor Flux Linkage magnitude and extracting the induction machine's response to the carrier signal, which is then used in a model reference adaptive system. This paper also presents a technique to minimize the torque ripple generated by the carrier signal. This technique utilizes the Rotor Flux Linkage reference in conjunction with a proportional-integral-resonant feedback plus feedforward control to generate references for the direct and quadrature axis stator currents. This paper also improves tracking of the torque and Rotor Flux Linkage in direct field-oriented control of the induction machine through employing electromotive force and resistive compensation methods for tracking q-axis and d-axis reference stator currents, respectively. Simulation and experimental results demonstrate the effectiveness of the technique over the entire operating range.
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Direct field-oriented control of an induction machine using an adaptive Rotor resistance estimator
2010 IEEE Energy Conversion Congress and Exposition, 2010Co-Authors: David M. Reed, Heath F. HofmannAbstract:This paper presents a new adaptive Rotor resistance estimator for induction machines. Stability and convergence of the proposed technique are rigorously analyzed, and regions of convergence are clearly shown. Furthermore, Rotor Flux Linkage estimators are implemented using the trapezoidal rule for improved accuracy and stability. These estimators are then incorporated into a direct field-oriented controller and thoroughly tested on experimental hardware. The resulting controller achieves a satisfactory level of performance over a wide range of operating conditions while eliminating the detuning caused by Rotor resistance variations.
Jing Zhang - One of the best experts on this subject based on the ideXlab platform.
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Influence of Nonideal Voltage Measurement on Parameter Estimation in Permanent-Magnet Synchronous Machines
IEEE Transactions on Industrial Electronics, 2012Co-Authors: Kan Liu, Zi-qiang Zhu, Qiao Zhang, Jing ZhangAbstract:This paper investigates the influence of nonideal voltage measurements on the parameter estimation of permanent-magnet synchronous machines (PMSMs). The influence of nonideal voltage measurements, such as the dc bus voltage drop, zero shift in the amplifier, and voltage source inverter nonlinearities, on the estimation of different machine parameters is investigated by theoretical and experimental analysis. For analysis, a model-reference-adaptive-system-based estimator is first described for the parameter estimation of the q-axis inductance, stator winding resistance, and Rotor Flux Linkage. The estimator is then applied to a prototype surface-mounted PMSM to investigate the influence of nonideal voltage measurement on the estimation of various machine parameter values. It shows that, at low speed, the inverter nonlinearity compensation has significant influence on both the Rotor Flux Linkage and winding resistance estimations while, at high speed, it has significant influence only on the winding resistance estimation and has negligible influence on the Rotor Flux Linkage estimation. In addition, the inverter nonlinearity compensation will not influence the q-axis inductance estimation when it is under id = 0 control. However, the dc bus voltage drop due to the load variation and zero shift in the amplifier will significantly influence the q-axis inductance estimation.
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online multiparameter estimation of nonsalient pole pm synchronous machines with temperature variation tracking
IEEE Transactions on Industrial Electronics, 2011Co-Authors: Qiao Zhang, J T Chen, Jing ZhangAbstract:The ill-convergence of multiparameter estimation due to the rank-deficient state equations of permanent-magnet synchronous machines (PMSMs) is investigated. It is verified that the PMSM model for multiparameter estimation under id = 0 control is rank deficient for simultaneously estimating winding resistance, Rotor Flux Linkage, and winding inductance and cannot ensure them to converge to the correct parameter values. A new method is proposed based on injecting a short pulse of negative id current and simultaneously solving two sets of simplified PMSM state equations corresponding to id = 0 and id ≠ 0 by using an Adaline neural network. The convergence of solutions is ensured, while the minimum |id| is determined from the error analysis for nonsalient-pole PMSMs. The proposed method does not need the nominal value of any parameter and only needs to sample the winding terminal currents and voltages, and the Rotor speed for simultaneously estimating the dq-axis inductances, the winding resistance, and the Rotor Flux Linkage in nonsalient-pole PMSMs. Compared with existing methods, the proposed method can eliminate the estimation error caused by the variation of Rotor Flux Linkage and inductance as a result of state change due to the injected d-axis current in the surface-mounted PMSM. The method is verified by experiments, and the results show that the proposed method has negligible influence on output torque and Rotor speed and has good performance in tracking the variation of PMSM parameters due to temperature variation.
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BIC-TA - Multi-parameter estimation of non-salient pole permanent magnet synchronous machines by using evolutionary algorithms
2010 IEEE Fifth International Conference on Bio-Inspired Computing: Theories and Applications (BIC-TA), 2010Co-Authors: Kan Liu, Zi-qiang Zhu, Qiao Zhang, Jing Zhang, Anwen ShenAbstract:This paper describes how to apply evolutionary algorithms (EA) for multi-parameter estimation of non-salient pole permanent magnet synchronous machines (PMSM). The encoding of estimated parameters is firstly described and the design of a penalty function associated with a proposed error analysis for PMSM multi-parameter estimation is then introduced. The PMSM stator winding resistance, dq-axis inductances and Rotor Flux Linkage can be estimated by maximizing the proposed penalty function through evolutionary algorithms such as immune clonal algorithm (ICA), quantum genetic algorithm (QGA) and genetic algorithm (GA). The experimental results show that the proposed strategy has good convergence in simultaneously estimating winding resistance, dq-axis inductances and Rotor Flux Linkage. In addition, the convergence speed of ICA in estimation is compared with GA and QGA, which verifies that the ICA has better performances in global searching. The ability of proposed method for tracking the parameter variation is verified by winding resistance step change and temperature variation experiments at last.
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Influence of inverter nonlinearity on parameter estimation in permanent magnet synchronous machines
The XIX International Conference on Electrical Machines - ICEM 2010, 2010Co-Authors: Kan Liu, Zi-qiang Zhu, Qiao Zhang, Jing Zhang, Anwen ShenAbstract:This paper investigates the influence of inverter nonlinearity on the parameter estimation in permanent magnet synchronous machines (PMSM). An estimator based on model reference adaptive system (MRAS) is firstly described for simultaneously estimating the stator winding resistance and Rotor Flux Linkage, together with injection of a pulse of i d
