Sensorless direct torque control for salient-pole PMSM based on extended Kalman filter fed by AC/DC/AC converter

Benchabane, Fateh; Titaouine, A.; Bennis, Ouafae; Yahia, K.; Taibi, Djamel; Guettaf, Abderrazak

doi:10.1007/s11708-012-0190-1

Cited by 12 publications

(5 citation statements)

References 18 publications

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“…The general form of the PMSM model in a system with dq coordinates rotating with the rotor can be expressed as follows: The reference model was prepared using Matlab-Simulink environment. Then the C-code was generated, using tools proa possibility to use an observer which estimates the position using any method: using signal injections or the observers, e.g., based on back EMF estimation, using Luenberger and modified Luenberger observers [26], based on various realizations of Kalman filter [27][28] [29][30], using sliding mode observers [31][32] [33] and artificial neural networks [34]. As mentioned above, the control system utilizes the Luenberger observer.…”

Section: The New Control Structurementioning

confidence: 99%

A new sensorless speed control structure for PMSM using reference model

Urbański¹

2017

Bulletin of the Polish Academy of Sciences Technical Sciences

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Abstract. In the paper a new sensorless control structure for the PMSM drive is presented. Such a structure is especially recommended for speed in the range of single revolutions per second (excluding standstill). The method uses a back EMF observer for position estimation. However, there is no need to estimate the speed. This is a big advantage because of possible irregularity of estimated back EMF in this speed range, which makes the calculation of speed difficult or impossible. The proposed structure is similar to the model following control, but the reference model attempts to track the motor operating point. The main idea is to utilize as a reference a model of the whole drive, including speed and current controllers and motor model. Such a model produces reference voltage for the real inverter. However, an extra unit -called rotator -is needed to provide precise control of direct axis current, which is sensitive to the improper position of the voltage vector. The rotator acts as a kind of compensator for error of position estimation. range. This is confirmed by experimentally obtained waveforms shown in Fig. 1 and Fig. 2. This is the idle speed, using a constant value of reference current on q axis. These waveforms were obtained for a traditional field oriented control (FOC) method of the PMSM (using a similar structure as is shown in Fig. 4), with a cascade control structure using a closed speed control loop (which was disconnected for the test) with inner current control loops containing separate controllers on d and q axes, rotating synchronously with the rotor. The overall structure of control utilizes the sine and cosine of the estimated position and calculated speed value instead of measured values.To obtain smooth output values from the observer, the reference voltage is used instead of measured ones. This simplification gives good results

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Section: The New Control Structurementioning

confidence: 99%

A new sensorless speed control structure for PMSM using reference model

Urbański¹

2017

Bulletin of the Polish Academy of Sciences Technical Sciences

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“…However it did not discuss the choice of noise matrices Q and R. Akrad et al 12 designed a faulttolerant controller for PMSM drive based on two virtual sensors with one being a two-stage extended Kalman filter and a maximum-likelihood voting algorithm. It also did not mention how to determine Q and R. Benchabane et al 13 used the EKF for the speed, rotor position, and load torque estimation based on the feedback of an indirect power electronic converter which is controlled by a sliding mode technique. Shi et al 14 used a self-adaption Kalman observer (SAKO) to observe speed and load torque precisely and timely, and they used a variable gain matrix to estimate and correct the observed position, speed, and load torque to solve the large speed error and time delay problem when PMSM runs at low speeds.…”

Section: Introductionmentioning

confidence: 99%

Speed control of sensorless PMSM drive based on EKF optimized by variable scale chaotic particle swarm optimization

Zhao,

Yang

et al. 2024

Measurement and Control

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To investigate the parameter characteristics of permanent magnet synchronous motor (PMSM) speed sensorless vector control system and capture the noise matrices quickly and accurately in the speed estimation process of the extended Kalman filter for PMSM, The recursive least square method with forgetting factor is proposed to determine the actual parameters of the system, and then a new variable-scale chaotic particle swarm optimization (VCPSO) algorithm is put forward to accurately obtain the system noise matrix and the measurement noise matrix. The simulation results show that noise matrix optimization of extended Kalman filter by employing VCPSO algorithm under actual motor parameters is better than those employing standard PSO or chaotic PSO algorithms with faster speed and higher accuracy.

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“…The role of the inverter is to make the stator phases switch, depending on the rotor position so that the PMSMs operate with varying speed. The inverters are acted by using the controllers, but these require rotor speed, rotor position and load torque measurements (El Magri et al, 2010;Benchabane et al, 2012). It is known that mechanical sensor-based solutions are costly and not sufficiently reliable.…”

Section: Introductionmentioning

confidence: 99%

Sensorless online measurements: application to variable speed drive systems

Tahir

2018

COMPEL

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Purpose Sensorless online measurements, application of variable speed drives has been given a great attention, especially over the past few years. In most of the previous literates dealing with permanent magnet synchronous motor (PMSM) drives, the combination of inter-sampled behavior with high gain design approach has not been discussed yet. This paper aims to discuss this feature in-depth. Design/methodology/approach The study contains a different approach for an observer running with surface-mounted permanent magnet synchronous machine drives to implement sensorless control. Design of sampled data observer methodology for one kind of AC machine having non-linear model and backed by an elegant formal stability convergence analysis using the tools of Lyapunov stability techniques was highly recommended in scientific contributions, and it is yet needed to be solved. Findings In this study, a solution to observation problem is covered and developed by combining ideas from the high-gain design approach and inter-sample predictor based on stator voltage measurements. The output state currents are accessible only at the sampling instant to solve the problem of states observation at continuous-time mode. This allows to reducing the usage of online appliances, improving reliability of control design and saving costs. Practical implications The proposed observer is capable of guaranteeing an acceptable closed loop dynamic response over a wide range of operation region and industrial process for random initial conditions. Originality/value The output state predictor has been interred in constructing the innovation correct term to prove the robustness of the proposed observer against attenuated sampling interval. To validate the theoretical results introduced by the main fundamental theorem and prove the observer stability convergence, the proposed observer is demonstrated through a sample study application to variable speed permanent magnet synchronous machine drive.

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Sensorless direct torque control for salient-pole PMSM based on extended Kalman filter fed by AC/DC/AC converter

Cited by 12 publications

References 18 publications

A new sensorless speed control structure for PMSM using reference model

A new sensorless speed control structure for PMSM using reference model

Speed control of sensorless PMSM drive based on EKF optimized by variable scale chaotic particle swarm optimization

Sensorless online measurements: application to variable speed drive systems

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