This paper extends the method of signal injection to accommodate nonperiodic excitation. The proposed extension builds on two key elements from the periodic case: (1) the decomposition of the system into low- and high-frequency components using higher-order averaging, and (2) the extraction of the virtual output through a demodulation process.

This work develops a novel unified observer for flux estimation in ac machines. It has been demonstrated that a unified adaptive flux observer based on the active flux concept can be implemented for both Permanent Magnet Synchronous Machines (PMSMs) and Induction Machines (IMs). Using the well-known “Voltage Model” (VM) in addition to the modified “Current Model” (CM), a full-order adaptive flux observer can be designed. This unified state observer is essentially the same for all ac machines, in which only the stator resistance and equivalent inductance are needed. The stability conditions of this novel flux observer scheme based on the proposed model have been derived analytically using the Lyapunov theory. Digital simulations in MATLAB/Simulink are given to illustrate the theoretical results for both PMSMs and IMs. Finally, experimental tests were done on both IMs and PMSMs to validate the proposed unified observer's performance.

This work proposes a unified back Active Electromotive Force (AEMF) observer for AC machines based on the SuperTwisting Algorithm (STA). This study aims to create a universal observer structure that could drive Synchronous Machines (SMs) and Induction Machines (IMs) without modifying the observer structure. It is shown that the proposed unified observer can be applied to SMs and IMs with minimum machine parameters, negating the need for machine-type knowledge, or at the very least, the rotor flux model. The active EMF, a generalized version of the original back EMF, is used to achieve this. The Lyapunov theory guarantees the convergence of the proposed observer. Finally, to confirm our theoretical results, the proposed observer was validated on a Permanent Magnet SM (PMSM) and IM using MATLAB/Simulink simulations and experimental tests conducted on a real test bench.

A new unified adaptive flux observer for induction machines (IMs) and permanent magnet synchronous machines (PMSMs) is proposed in this work. The proposed unified observer is created using both the well-known “Voltage Model” (VM) and the “Flux Model” (FM) in the estimated rotating synchronous frame. Under the time-scale separation assumption between the rotor flux dynamics and the stator current dynamics in the estimated rotor synchronous frame, the rotor flux can be considered a slowly varying signal for which an adaptation law has been designed. We showed that the proposed unified observer can be applied to IMs and PMSMs with minimum knowledge of motor parameters, requiring only information on the stator resistance and $dq$ axis inductances. The stability of the proposed observer is proven using the Lyapunov theory based on the presented unified model. Finally, numerical simulations in MATLAB/Simulink and experimental tests on an IM and a PMSM are provided to illustrate the theoretical results.

This article presents a model of a Synchronous Reluctance Motor (SynRM) at standstill, including magnetic hysteresis, to study its impact on High-Frequency (HF) signal injection. So that it can easily be simulated, the model is rewritten under state-form. The parameters of the model are identified, based on experimental data, using a customized fitting procedure adapted to hysteresis curves. The proposed model explains the impact of magnetic hysteresis on HF signal injection and reproduces accurately the experiments.

This paper presents a comparison study between the Rotor Field-Oriented Control (RFOC) and Stator Field-Oriented Control (SFOC) for Permanent-Magnet Synchronous Motors (PMSMs). Both methods fall within the well-known Field-Oriented Control (FOC) category. To evaluate both methods for PMSM control, different methodologies should be provided, beginning with the control design, the Maximum Torque Per Ampere (MTPA) strategy, and the flux weakening approach. Finally, a comparison between both methods based on simulation results for a 2.2 kW motor model is presented.

We show that the gradient observer proposed in Bernard & Praly, IFAC 2017 for PMSMs, can be used to estimate the stator flux of SynRMs, using only electrical measurements and the knowledge of the resistance. This sensorless observer ensures global convergence of the flux estimate provided the rotation speed and the current norm remains away from zero and the current and voltages are bounded, without requiring the knowledge of the magnetic model. Its robustness with respect to resistance errors is shown, with explicit expression of the resulting steady state error. This observer operates dynamically, in normal conditions, without any constraint on the load, and without any mechanical information. In a second step, we propose to exploit the knowledge of a magnetic inductance model (containing magnetic saturation) to estimate the rotor position from the flux estimate. The performance of this estimation in open-loop is illustrated on experimental data on a SynRM.

This paper proposes a new method to estimate the rotor flux of a Permanent-Magnet Synchronous Motor (PMSM) at standstill. This method works on motors that have enough magnetic saliency so that the reluctance torque can cancel the magnet-alignment torque. A nonlinear controller is designed to achieve standstill operation. The stability of this controller is studied using both the linearized model and nonlinear control theory. It is proven that the desired operating condition, where the rotor flux can be estimated, is locally asymptotically stable. Thanks to its bifurcation property, the proposed controller ensures zero speed for any type of PMSM, which is not the case for all existing methods. Furthermore, the estimation accuracy is made independent of the motor loading using a compensation procedure. The theoretical results are verified in simulation on an 11kW motor model.

We propose a procedure to demodulate analog signals encoded by a multicarrier modulator, with slowly-varying carrier shapes. We prove that the asymptotic demodulation error can be made arbitrarily small. The intended application is the “sensorless” control of AC electric motors at or near standstill, through the decoding of the PWM-induced current ripple.

We show how the rotor position of a PWM-fed PMSM can be recovered, even at low velocity or standstill, from the measured currents. The method is based on the excitation created by the PWM, without the need for an external probing signal. One originality of the approach is that we directly process the bitstream output by a Sigma-Delta modulator, hence do not require special derivative current sensors nor fast multibit ADCs, thereby opening the way for an effective implementation in an industrial drive.

Continuous-time Sigma-Delta (CT-ΔΣ) modulators are oversampling Analog-to-Digital converters that may provide higher sampling rates and lower power consumption than their discrete counterpart. Whereas approximation errors are established for high-order discrete time ΔΣ modulators, theoretical analysis of the error between the filtered output and the input remain scarce. This paper presents a general framework to study this error: under regularity assumptions on the input and the filtering kernel, we prove for a second-order CT-ΔΣ that the error estimate may be in o(1/N)2, where N is the oversampling ratio. The whole theory is validated by numerical experiments.

We demonstrate how the rotor position of a PWM-controlled PMSM can be recovered from the measured currents, by suitably using the excitation provided by the PWM itself. This provides the benefits of signal injection, in particular the ability to operate even at low velocity, without the drawbacks of an external probing signal. We illustrate the relevance of the approach by simulations and experimental results.

We show that for PWM-operated devices, it is possible to benefit from signal injection without an external probing signal, by suitably using the excitation provided by the PWM itself. As in the usual signal injection framework conceptualized in [1], an extra "virtual measurement" can be made available for use in a control law, but without the practical drawbacks caused by an external signal.

Signal injection was conceptualized in [1] as a method to make available an extra "virtual measurement", hence to simplify the design of a control law in particular when the system observability degenerates at a steady-state region of interest. In this paper, we show that the approach of [1] can be extended to produce yet others virtual measurements, thanks to an analysis based on third-order averaging.

This paper introduces a set of estimators for a wide class of multiplexed signal. The signals of interest are decomposed on independent periodic signals with a shared frequency. This latter set of signals is as general as possible; that is, not necessarily orthogonal or sinusoidal. By an adequate linear combination of low-pass filters, we extract each of the components of the multiplexed signal with an arbitrary accuracy. Applications of this demodulation procedure include sensorless control of electrical machines using signal injection with the extraction of the ripple.

Output LC filters are commonly used to filter the high frequency harmonics induced by PWM switching. Their effect is generally disregarded, as nonmodeled dynamics are handled by control law robustness. We show that the output filter can easily be modeled and be taken into account in the control design. We provide numeric stability analysis of control laws with or without current feedback. We also prove that it is more favorable to feed back the drive current than to feed back the motor current.

This paper proposes a method based on signal injection to obtain the saturated current-flux relations of a PMSM from locked-rotor experiments. With respect to the classical method based on time integration, it has the main advantage of being completely independent of the stator resistance; moreover, it is less sensitive to voltage biases due to the power inverter, as the injected signal may be fairly large.