L. Salvatore

A new EKF-based algorithm for flux estimation in induction machines

A reduced-order algorithm for estimating the rotor flux components of induction motors with schemes such as field-oriented control is described. The algorithm is based on the extended Kalman filter (EKF) theory and estimates the desired quantities online using only measurements of the stator voltages and currents and the rotor speed. The online adaptation of the inverse rotor time constant makes it possible to obtain very accurate estimates of rotor flux components, in spite of temperature and magnetic saturation effects. The algorithm order reduction decreases the computational complexity and makes the proposed estimator superior to others based on EKF theory. >

End Effects in Linear Tubular Motors and Compensated Position Sensorless Control Based on Pulsating Voltage Injection

The sensorless position control of permanent-magnet (PM) synchronous motors can be successfully implemented by superimposing a high-frequency voltage signal on the control voltage. In this paper, the position estimation is obtained by means of a high-frequency sinusoidal voltage signal injected along the estimated -axis. Several methods proposed in the literature obtain the position estimation by tracking the zero condition of the high-frequency current component. We propose a new approach that also exploits the -axis high-frequency current component and allows working with injected voltage signal of reduced amplitude, thus reducing noise and additional losses. The main contribution of this paper relies in the compensation of the motor end effects due to the finite length of the tubular motor armature. These effects must be taken into account in the motor modeling because they cause an error in the position estimation that varies with the motor position. The modeling of the phenomenon and a proper compensation technique are proposed in this paper. Last, a simplified integral-type controller is used to estimate motor position instead of the commonly adopted proportional-integral controller plus integrator, and this requires a low-effort design. Experiments on a linear tubular PM synchronous-motor prototype are presented to validate the theoretical analysis and evidence the feasibility of the proposed sensorless technique.

On-line genetic design of anti-windup unstructured controllers for electric drives with variable load

In this paper, we describe an evolutionary design procedure for discrete-time anti-windup controller for electrical drives. Using a genetic algorithm devised to test and compare controllers of different orders, we search for the discrete anti-windup controller achieving the optimal compromise of weighted cost and performance indices. The search is performed on-line, on the physical hardware, by continuously downloading and testing new solutions on a microprocessor running the control algorithms in real time. The controller obtained through genetic search significantly outperforms alternative schemes obtained with conventional design techniques.

Running DFT-Based PLL Algorithm for Frequency, Phase, and Amplitude Tracking in Aircraft Electrical Systems

Phase-locked loop (PLL) algorithms are commonly used to track sinusoidal components in currents and voltage signals in three-phase power systems. Despite the simplicity of those algorithms, problems arise when signals have variable frequency or amplitude, or are polluted with harmonic content and measurement noise, as can be found in aircraft ac power systems where the fundamental frequency can vary in the range 360-900 Hz. To improve the quality of phase and frequency estimates in such power systems, a novel PLL scheme based on a real-time implementation of the discrete Fourier transform (DFT) is presented in this paper. The DFT algorithm calculates the amplitudes of three consecutive components in the frequency domain. These components are used to determine an error signal which is minimized by a proportional-integral loop filter in order to estimate the fundamental frequency. The integral of the estimated frequency is the estimated phase of the fundamental component, and this is fed back to the DFT algorithm. The proposed algorithm can therefore be considered to be a PLL in which phase detection is performed via a DFT-based algorithm. A comparison has been made of the performances of a standard PLL and the proposed DFT-PLL using computer simulations and through experiments.

Sensorless Position Control of Permanent-Magnet Motors With Pulsating Current Injection and Compensation of Motor End Effects

The sensorless position control of permanent-magnet motors is successfully implemented by superimposing a high-frequency voltage signal on the voltage reference or adding a high-frequency current signal to the current reference. The former approach is usually preferred because of its simplicity, although the latter one may allow better performance. This paper presents a new algorithm for the sensorless control of low-saliency permanent-magnet synchronous motors based on high-frequency sinusoidal current signal injection into the d-axis. Different from the related literature, the position information is derived by analyzing the measured high-frequency currents. The amplitude of the d-axis voltage reference is also exploited to improve performance. A proportional-integral (PI) controller plus a resonant term (PI-RES) is adopted to ensure the accurate tracking of both the dc and high-frequency components of the d -axis current reference. The main advantages of the proposed approach are the increased accuracy and sensitivity with respect to the approach based on voltage injection, the insensitiveness to inverter nonlinearities that are compensated by the current regulation loop, the actual control on the injected current value, and the practical absence of acoustic noise. Experiments on a linear tubular permanent-magnet synchronous motor prototype have been carried out to verify the aforementioned advantages. This paper also presents a discussion of the parameters of the PI-RES.

A new fuzzy logic-based controller design method for DC and AC impressed-voltage drives

This paper deals with the design of fuzzy logic-based controllers (FLBC) for DC and AC electric drives. Industrial drives employ the cascaded PI control with a subordinated current control loop to make sure that the current does not exceed the admissible value and improve dynamic performances. The nonlinear FLBC characteristics permit one to achieve the performances of the cascaded control using only one control loop. This is feasible by a suitable choice of the scaling factors together with the rules of the fuzzy controller. The authors propose a minimum number of rules and the criteria, based on physical considerations, to determine the input and output gains instead of using the trial and error procedure. The designed FLBC is able to control the speed of a DC drive as well as the rotor speed and flux of a vector-controlled induction motor drive. Computer simulations show the effectiveness of the new fuzzy-controller design method. The reduced number of rules and membership functions and the application flexibility together with the possible implementation on low cost /spl mu/Ps lead the authors to think that the proposed tuning criteria will be widely adopted.

Improved rotor speed estimation using two Kalman filter-based algorithms

This paper proposes the application of two new Kalman filter-based algorithms to realise a speed-sensorless vector control of induction motor drives. The first one is a linear Kalman filter (LKF)-based algorithm that estimates the equivalent disturbance torque, which is compensated by the injection of a feedforward signal. The latter is an extended Kalman filter (EKF)-based algorithm used to obtain a correct implementation of sensorless vector control, since it estimates both the rotor flux components and speed. The mathematical EKF-model is accurate because of the equivalent-disturbance compensation obtained from the LKF-based observer. The rotor speed estimate is very good in the whole velocity range including zero value. The results show the effectiveness of the proposed control scheme.

Comparison of spectral estimation techniques applied to induction motor broken bars detection

This paper presents a performance comparison among some of the most effective spectral estimation techniques applied to the fault diagnosis of induction machines. The diagnostic test is based on the analysis of the current space vector during motor starting via short-time analysis, using a sliding window and different spectral estimation algorithms. Differently from most of the diagnostic techniques already proposed in the technical literature, the approach, presented in this work, is effective regardless of the load condition of the machine. Algorithms based on the FFT or optimal band-pass filters (nonparametric methods), on the estimation of a linear time-invariant model of the signal (parametric methods), and on the eigenanalysis of the autocorrelation matrix (high-resolution methods) have been used to process the motor current space-vector. Experiments prove that both parametric and high-resolution methods overcome the FFT-based approaches, keep only the principal frequency components of the signal and decrease the noise influence, thus permitting a better interpretation of the current vector spectrum and an automatic fault detection procedure.

EKF-and wavelet-based algorithms applied to harmonic detection for active shunt filters

This work presents a performance comparison among algorithms able to estimate in real-time the fundamental component of the current absorbed from the supply by a nonlinear load. This fundamental component can be used to calculate the current reference for an active shunt filter (ASF). The effectiveness of ASFs in reducing the harmonic contents of the supply currents is strictly related to the ability of an algorithm to give a reliable and accurate estimate of the harmonic contents of the load current both at steady-state and in transient conditions. We have considered algorithms based on the use of a synchronous rotating frame (SRF), wavelet analysis, and Kalman filter theory. In order to overcome the problem related to the choice of the covariance matrices of the Kalman filter-based algorithm we propose to use a genetic algorithm (GA) to perform an off-line automatic search for optimal parameters. Experimental results are presented considering a three-phase induction motor drive as nonlinear load.

Adaptive sliding-mode observer for field oriented sensorless control of SPMSM

This paper proposes a new scheme to guarantee speed sensorless control and optimal field orientation of surface permanent magnet synchronous motors (SPMSMs) even if parameter deviations occur and initial rotor position is unknown. A novel adaptive sliding-mode observer is used for field oriented speed sensorless control. First the induced e.m.f. components are observed using the sliding-mode technique with an adaptive switching gain. Then a low-pass filter with an adaptive amplitude compensator, that works as derivative observer, is used to get rid of the chattering noise of estimated e.m.f. components and to calculate rotor speed and position. The current components in rotor reference frame are estimated from the active and reactive electromagnetic torques calculated in both the stationary reference frame and the estimated rotor one. The latter is also used as control reference frame. Inverter, filters and observer cause unavoidable and unpredictable time-delay in rotor position estimation, so that the control reference frame is delayed as to the actual rotor one. As a consequence, field orientation and maximum torque/current ratio do not occur when the desired field oriented current references are imposed in the control reference frame. An original field orientation PI controller is used to provide the appropriate current references in the control reference frame. Test results are presented to prove the approach effectiveness.