801 research outputs found

    A globally exponentially stable position observer for interior permanent magnet synchronous motors

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    The design of a position observer for the interior permanent magnet synchronous motor is a challenging problem that, in spite of many research efforts, remained open for a long time. In this paper we present the first globally exponentially convergent solution to it, assuming that the saliency is not too large. As expected in all observer tasks, a persistency of excitation condition is imposed. Conditions on the operation of the motor, under which it is verified, are given. In particular, it is shown that at rotor standstill---when the system is not observable---it is possible to inject a probing signal to enforce the persistent excitation condition. {The high performance of the proposed observer, in standstill and high speed regions, is verified by extensive series of test-runs on an experimental setup

    A Nonlinear Sliding Mode Controller for IPMSM Drives with an Adaptive Gain Tuning Rule

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    This paper presents a nonlinear sliding mode control (SMC) scheme with a variable damping ratio for interior permanent magnet synchronous motors (IPMSMs). First, a nonlinear sliding surface whose parameters change continuously with time is designed. Actually, the proposed SMC has the ability to reduce the settling time without an overshoot by giving a low damping ratio at the initial time and a high damping ratio as the output reaches the desired setpoint. At the same time, it enables a fast convergence in finite time and eliminates the singularity problem with the upper bound of an uncertain term, which cannot be measured in practice, by using a simple adaptation law. To improve the efficiency of a system in the constant torque region, the control system incorporates the maximum torque per ampere (MTPA) algorithm. The stability of the nonlinear sliding surface is guaranteed by Lyapunov stability theory. Moreover, a simple sliding mode observer is used to estimate the load torque and system uncertainties. The effectiveness of the proposed nonlinear SMC scheme is verified using comparative experimental results of the linear SMC scheme when the speed reference and load torque change under system uncertainties. From these experimental results, the proposed nonlinear SMC method reveals a faster transient response, smaller steady-state speed error, and less sensitivity to system uncertainties than the linear SMC metho

    A Nonlinear Sliding Mode Controller for IPMSM Drives with an Adaptive Gain Tuning Rule

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    This paper presents a nonlinear sliding mode control (SMC) scheme with a variable damping ratio for interior permanent magnet synchronous motors (IPMSMs). First, a nonlinear sliding surface whose parameters change continuously with time is designed. Actually, the proposed SMC has the ability to reduce the settling time without an overshoot by giving a low damping ratio at the initial time and a high damping ratio as the output reaches the desired setpoint. At the same time, it enables a fast convergence in finite time and eliminates the singularity problem with the upper bound of an uncertain term, which cannot be measured in practice, by using a simple adaptation law. To improve the efficiency of a system in the constant torque region, the control system incorporates the maximum torque per ampere (MTPA) algorithm. The stability of the nonlinear sliding surface is guaranteed by Lyapunov stability theory. Moreover, a simple sliding mode observer is used to estimate the load torque and system uncertainties. The effectiveness of the proposed nonlinear SMC scheme is verified using comparative experimental results of the linear SMC scheme when the speed reference and load torque change under system uncertainties. From these experimental results, the proposed nonlinear SMC method reveals a faster transient response, smaller steady-state speed error, and less sensitivity to system uncertainties than the linear SMC metho

    Application of Sliding Mode Controller and Linear Active Disturbance Rejection Controller to a PMSM Speed System

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    Permanent magnet synchronous motor (PMSM) is a popular electric machine in industry for its small volume, high electromagnetic torque, high reliability and low cost. It is broadly used in automobiles and aircrafts. However, PMSM has its inherent problems of nonlinearity and coupling, which are challenges for control systems design. In addition, the external disturbances such as load variation and noises could degrade the systems performance. Both sliding mode control (SMC) and active disturbance rejection control (ADRC) are robust against disturbances. They can also compensate the nonlinearity and couplings of the PMSM. Therefore, in this thesis, we apply both SMC and ADRC to a PMSM speed system. Our control goal is to drive the speed outputs of the PMSM speed system to reference signals in the presences of nonlinearity, disturbance, and parameter variations. Simulation results verify the effectiveness of SMC and ADRC on the speed control for PMSM systems in spite of the presences of external disturbance and internal system uncertaintie

    Surface Permanent Magnet Synchronous Motors’ Passive Sensorless Control: A Review

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    Sensorless control of permanent magnet synchronous motors is nowadays used in many industrial, home and traction applications, as it allows the presence of a position sensor to be avoided with benefits for the cost and reliability of the drive. An estimation of the rotor position is required to perform the field-oriented control (FOC), which is the most common control scheme used for this type of motor. Many algorithms have been developed for this purpose, which use different techniques to derive the rotor angle from the stator voltages and currents. Among them, the so-called passive methods have gained increasing interest as they do not introduce additional losses and current distortion associated instead with algorithms based on the injection of high-frequency signals. The aim of this paper is to present a review of the main passive sensorless methods proposed in the technical literature over the last few years, analyzing their main features and principles of operation. An experimental comparison among the most promising passive sensorless algorithms is then reported, focusing on their performance in the low-speed operating region

    Speed control of an SPMSM using a tracking differentiator-PID controller scheme with a genetic algorithm

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    In this paper, a tracking differentiator-proportional integral and derivative (TD-PID) control scheme is proposed to control the speed of a surface mount permanent magnet synchronous motor (SPMSM). The TD is used to generate the necessary transient profile for both the reference and the output speed, which are compared with each other to produce the error signals that feed into the PID controller. In addition to the TD unit parameters, the PID controller’s parameters are tuned to achieve the optimum new multi-objective performance index, comprised of the integral of the time absolute error (ITAE), the absolute square of the control energy signal (USQR), and the absolute value of the control energy signal (UABS) and utilizing a genetic algorithm (GA). A nonlinear model of the SPMSM is considered in the design and the performance of the proposed TD-PID scheme was validated by comparing its performance with that of a traditional PI controller in a MATLAB environment. Different case studies were tested to show the effectiveness of the proposed scheme, results including peak overshoot, energy consumption, control signal chatter, and 30% improvement in the OPI, with variable reference speeds, load torque, and parameters uncertainties. Illustrate the proposed scheme's success compared with PI controller

    Global identification of electrical and mechanical parameters in PMSM drive based on dynamic self-learning PSO

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    A global parameter estimation method for a PMSM drive system is proposed, where the electrical parameters, mechanical parameters and voltage-source-inverter (VSI) nonlinearity are regarded as a whole and parameter estimation is formulated as a single parameter optimization model. A dynamic learning estimator is proposed for tracking the electrical parameters, mechanical parameters and VSI of PMSM drive by using dynamic self learning particle swarm optimization (DSLPSO). In DSLPSO, a novel movement modification equation with dynamic exemplar learning strategy is designed to ensure its diversity and achieve a reasonable tradeoff between the exploitation and exploration during the search process. Moreover, a nonlinear multi-scale based interactive learning operator is introduced for accelerating the convergence speed of the Pbest particles; meanwhile a dynamic opposition-based learning (OBL) strategy is designed to facilitate the gBest particle to explore a potentially better region. The proposed algorithm is applied to parameter estimation for a PMSM drive system. The results show that the proposed method has better performance in tracking the variation of electrical parameters, and estimating the immeasurable mechanical parameters and the VSI disturbance voltage simultaneously

    Sensorless Passive Control Algorithms for Medium to High Power Synchronous Motor Drives

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    This study is focused on the definition of sensorless algorithms for Surface-Mounted Permanent Magnet Synchronous Motors (SM-PMSM) and Electrically Excited Synchronous Motors (EESM). Even if these types of motors are rather different from a constructive point of view, they have some common issues regarding sensorless drives. Indeed, SM-PMSMs, which are usually used for low-medium power applications, have a low rotor anisotropy, therefore it is complicated to use sensorless active methods (which are based on high-frequency voltage injection), due to the low signal to noise ratio. On the other hand, active methods on high-power EESM have the drawback of high torque ripple. For these reasons, both for SM-PMSM and EESM, it is interesting to define and use sensorless passive algorithms (i.e., based on observers and estimators). The drawback of such algorithms is that their performance deteriorates significantly in the low-speed region. The aim of this thesis is to define a robust sensorless passive algorithm that could work in a wide speed region and that could start the motor from standstill even with a high load torque. The initial objective of the work is to find, among the various algorithms proposed in the technical literature, the most promising one. For this purpose, four different algorithms are selected. They are chosen considering the most recent articles presented in the technical literature on high reputable journals. Since many improvements are proposed in the literature for the different algorithms, the most recent ones are candidates for being the ones with higher performance. Even if the experimental tests of the four different algorithms are shown in the literature, it is difficult to evaluate a priori which offers the best performance. As a matter of facts, for each algorithm different tests are carried out (e.g., different speed and torque profiles). In addition to that, motor sizing and features are different. Moreover, the test bench characteristics can significantly affect sensorless performance. As an example, inverter features and non-linearities (e.g., switching frequency, dead times, parasitic capacitance) and current measures (e.g., noise, linearity, bias) play a key role in the estimation of rotor position. The added value of this thesis is to perform a fair comparison of the four algorithms, performing the same tests with the same test bench. Additional tests are performed on the most performing algorithm. Even if this sensorless technique is already proposed in the technical literature, a methodology for observer gain tuning is not shown, which is proposed, instead, in this thesis. Moreover, the algorithm is enhanced by adding a novel management of direct axis current, which ensures the stability during fast transient from medium-high speed to low speed. The algorithm is tested with different test benches in order to verify the control effectiveness in various operating conditions. As a matter of facts, it is tested at first in the University of Genoa PETRA Lab on two different test benches. The first test bench is composed of two coupled motors, in which the braking motor could realize different torque profiles (linear torque, quadratic torque and constant torque), whereas in the second test bench the motor is coupled with an air compressor, which is a demanding load since high and irregular torque is applied at standstill. After the test at the University of Genoa, the algorithm is implemented in Phase Motion Control and Physis drive and tested on a six-meter diameter fan. Regarding the EESMs, for these type of motor is necessary to estimate the stator flux amplitude and angle. Indeed, the stator angle is usually used to perform the Park transformations in the FOC scheme and the stator flux amplitude is used to control the excitation current. In this study, the RFO is adapted for estimating the stator flux of an EESM. Regarding the control for EESM, it is tested on a simulative model for high-power motors provided by NIDEC ASI and tested on a small-scale test bench at the University of Genoa
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