Spend your few moment to read a book even only few pages. Reading book is not obligation and force for everybody. When you don't want to read, you can get punishment from the publisher. Read a book becomes a choice of your different characteristics. Many people with reading habit will always be enjoyable to read, or on the contrary. For some reasons, this techniques for noise robustness in automatic speech recognition tends to be the representative book in this website.

Techniques for Noise Robustness in Automatic Speech Recognition

Rotor position and speed estimation methods are consolidated to reduce the cost and volume of permanent magnet synchronous motor (PMSM) sensorless control drives while maintaining high performance. Advanced nonlinear algorithms require accurate design for precise estimation tracking throughout the entire PMSM operation range. This paper presents a broad review of the main high-speed estimation methods for sensorless PMSM drives. First, the stability constraints and design methodologies of the main estimation techniques presented in the literature are discussed. In the second part, it is investigated the new observer design trends, which are used under non-ideal conditions, such as robustness to distortions, the effects of parameter variation, sensorless parameter estimation, and low sampling-frequency-to-speed ratio operation. Future trends on the design of observers for high-speed sensorless PMSM drives are also discussed.

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Observers for High-Speed Sensorless PMSM Drives: Design Methods, Tuning Challenges and Future Trends

To heighten the position estimation accuracy of sensorless control of interior permanent magnet synchronous motor (IPMSM), an improved full-order sliding mode observer (FSMO) based on novel phase-locked loop (PLL) is proposed in this article. By contrast with the traditional FSMO, the improved FSMO (IFSMO) with piecewise power function has merits of higher estimation accuracy and more chattering suppress capability, which is beneficial to the position sensorless drives. Based on that, to pledge the rotor position observation precision of the IFSMO during wide speed range, a variable sliding mode gain related to the rotor speed is designed. However, due to the inverter nonlinearity and rotor spatial harmonics, the extended back electromotive force contains high-order harmonics, which will reduce the estimation accuracy of PLL and cause notable position error. Therefore, a novel PLL with complex bandpass filter as the preprocessing stage that features high estimation accuracy, high filtering capability, and fast dynamic response is proposed. Meanwhile, the linearized model and parameter design of the proposed PLL is developed, and hence the stability of the designed PLL is analyzed by the derived linearized model. The availability of the proposed sensorless strategy is verified via experiments on 2-kW IPMSM drive. 

Estimated Position Error Suppression Using Novel PLL for IPMSM Sensorless Drives Based on Full-Order SMO

The encoder influences reliability and cost of permanent magnet synchronous motor (PMSM) operated solar water pump (WP). It is even sensitive to electromagnetic noise and temperature, which thereby reduces its accuracy. To overcome these problems, an encoderless PMSM control by using adaptive hybrid generalized integrator (AHGI) based sliding mode observer (SMO) for the solar WP system is presented in this paper. The widely used low pass filter based SMO produces phase-shift, attenuation and dominant lower order harmonics (DLOH). This decreases the position estimation accuracy. Besides, the need for tracking dynamic system frequency further exacerbates its performance. The developed AHGI structure eliminates these drawbacks and provides an accurate estimate of position over a wide speed range. A harmonic decoupling network, a hybrid generalized integrator and an adaptive frequency tracker constitute AHGI, which respectively performs dominant harmonic signal generation, DLOH elimination and frequency tracking. The improvement in behavior of AHGI over the existing methods is analyzed by transfer functions, Bode plots and back electromotive force helices. Meanwhile an incremental conductance algorithm for PV array maximum power control is used. The developed structure is experimentally validated on a laboratory prototype and a comparison with the existing methods is also made.

Adaptive Hybrid Generalized Integrator Based SMO for Solar PV Array Fed Encoderless PMSM Driven Water Pump

This article proposes a compensation method of position estimation error for high-speed surface-mounted permanent magnet synchronous motors based on robust inductance estimation. The proposed method relies on the variation of the estimated $\delta$ -axis back back-electromotive force when a small current is injected into the $\gamma$ axis. The inductance estimation error is limited within ${\bf \pm \!5\%}$ when the nominal resistance and inductance vary $\bf \pm 30\%$ of their real values. With the estimated inductance, the position estimation error can be well compensated. Compared with the conventional current-injection method, the proposed method has enhanced robustness against the system noises. Benefiting from this, it is effective to estimate the inductance with a small injected current ( $ \bf 0.5\%$ of the rated current), where the conventional methods fail. Finally, the effectiveness of the proposed method is validated by simulation and experiment results on a 100 kr/min (1.67 kHz) high-speed permanent magnet synchronous machines accurately with 10-kHz sampling frequency.

Compensation Method of Position Estimation Error for High-Speed Surface-Mounted PMSM Drives Based on Robust Inductance Estimation

In the back electromotive force (EMF)-based sensorless control of interior permanent magnet synchronous motor (IPMSM), the inverter nonlinearity and flux linkage spatial harmonics will possibly give rise to (6 k ± 1)th harmonics in the estimated back EMF, especially the fifth and seventh harmonics. Those harmonics will consequently introduce (6 k )th harmonic ripples to the estimated rotor position, especially the sixth harmonic component. In order to solve this problem, a bilinear recursive least squares (BRLS) adaptive filter is proposed and integrated into a sliding-mode position observer to suppress the dominant harmonic components in the estimated back EMF and as a result, the accuracy of the estimated rotor position can be greatly improved. A unique feature of the BRLS adaptive filter is its ability to track and suppress the specified harmonic components in different steady state and dynamic operational conditions. The proposed method can compensate for harmonic ripples caused by the inverter nonlinearity and machine spatial harmonics at the same time; this method is also robust to machine parameter variation, and the BRLS algorithm itself is machine parameter independent. The implementation of the proposed BRLS filter in the sensorless control of IPMSM is explained in details in this paper. The enhanced drive performances using the BRLS filter have been thoroughly validated in different steady state and dynamic operational conditions on a 1.5-kW IPMSM sensorless drive.

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Enhanced Position Sensorless Control Using Bilinear Recursive Least Squares Adaptive Filter for Interior Permanent Magnet Synchronous Motor

In this article, an innovative hybrid position estimation strategy along with the minimum voltage vector injection (MVVI) method and the back electromotive force (back EMF) based method is proposed for interior permanent magnet synchronous motors (IPMSMs) in full-speed regions. At zero- and low-speed, the MVVI method based on rotor saliency is used for position estimation; the inverter voltage error is counteracted in estimating the rotor position, minimizing the inverter nonlinearity effect without introducing external errors. For IPMSMs at the initial state, this article proposes to utilize the high frequency d-axis current excited by injection voltage itself directly for the polarity detection. The position estimation at low-speed based on the MVVI method has such advantages as no requirement for filters, fast convergence, and reliability of magnetic polarity detection. In addition, a smooth transition blends the MVVI method and the back EMF based method is proposed, and a compensation term based on q-axis feedback current is added on the error of both the reference and feedback speed to reject the load-disturbance within the low speed and transition region. Experimental results show that the proposed hybrid sensorless control strategy exhibits excellent performance in the full speed range for both steady-state and dynamic operations.

Wenli Pan

Papers

Enhanced Position Sensorless Control Using Bilinear Recursive Least Squares Adaptive Filter for Interior Permanent Magnet Synchronous Motor

Hybrid Position Estimation Strategy With a Smooth Transition for IPMSM Sensorless Drives in the Wide Speed Range