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

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

Linear robust output−feedback control for permanent−magnet synchronous motors with unknown load

International audienceWe solve the problem of set-point (respectively, tracking) control of a permanent-magnet synchronous motor via linear time-invariant (respectively, time varying) control. Our control approach is based on the physical properties of the machine: inherent stability and robustness to external disturbances. Our analysis is carried out under mild conditions, using cascaded systems theory. For all cases: constant operating point, trajectory tracking, and with known and unknown load, we show uniform global asymptotic stability of the closed-loop system with a linear controller that uses only velocity measurements. Furthermore, we explore natural extensions of our results to improve robustness with respect to external disturbances and parametric uncertainties

Genetic algorithm optimized robust nonlinear observer for a wind turbine system based on permanent magnet synchronous generator

© 2022 ISA. Published by Elsevier Ltd. All rights reserved. This is the accepted manuscript version of an article which has been published in final form at https://doi.org/10.1016/j.isatra.2022.02.004This paper presents an optimal control scheme for a Permanent Magnet Synchronous Generator (PMSG) coupled to a wind turbine operating without a position sensor. This sensorless scheme includes two observers: The first observer uses the flux to estimate the speed. However, an increase in the temperature or a degradation of the permanent magnet characteristics will result in a demagnetization of the machine causing a drop in the flux. The second observer is therefore used to estimate these changes in the flux from the speed and guaranties the stability of the system. This structure leads to a better exchange of information between the two observers, eliminates the problem of encoder and compensates for the demagnetization problem. To improve the precision of the speed estimator, the gain of the non-linear observer is optimized using Genetic Algorithm (GA) and the speed is obtained from a modified Phase Locked Loop (PLL) method using an optimized Sliding Mode Controller (SMC). Furthermore, to enhance the convergence speed of this observer scheme and improve the performance of the system a Fast Super Twisting Sliding Mode Control (FSTSMC) is introduced to reinforce the SMC strategy. A series of simulations are presented to show the effectiveness and robustness of proposed observer scheme.Peer reviewe

Adaptive control of sinusoidal brushless DC motor actuators

Electrical Power Assisted Steering system (EPAS) will likely be used on future automotive power steering systems. The sinusoidal brushless DC (BLDC) motor has been identified as one of the most suitable actuators for the EPAS application. Motor characteristic variations, which can be indicated by variations of the motor parameters such as the coil resistance and the torque constant, directly impart inaccuracies in the control scheme based on the nominal values of parameters and thus the whole system performance suffers. The motor controller must address the time-varying motor characteristics problem and maintain the performance in its long service life. In this dissertation, four adaptive control algorithms for brushless DC (BLDC) motors are explored. The first algorithm engages a simplified inverse dq-coordinate dynamics controller and solves for the parameter errors with the q-axis current (iq) feedback from several past sampling steps. The controller parameter values are updated by slow integration of the parameter errors. Improvement such as dynamic approximation, speed approximation and Gram-Schmidt orthonormalization are discussed for better estimation performance. The second algorithm is proposed to use both the d-axis current (id) and the q-axis current (iq) feedback for parameter estimation since id always accompanies iq. Stochastic conditions for unbiased estimation are shown through Monte Carlo simulations. Study of the first two adaptive algorithms indicates that the parameter estimation performance can be achieved by using more history data. The Extended Kalman Filter (EKF), a representative recursive estimation algorithm, is then investigated for the BLDC motor application. Simulation results validated the superior estimation performance with the EKF. However, the computation complexity and stability may be barriers for practical implementation of the EKF. The fourth algorithm is a model reference adaptive control (MRAC) that utilizes the desired motor characteristics as a reference model. Its stability is guaranteed by Lyapunov’s direct method. Simulation shows superior performance in terms of the convergence speed and current tracking. These algorithms are compared in closed loop simulation with an EPAS model and a motor speed control application. The MRAC is identified as the most promising candidate controller because of its combination of superior performance and low computational complexity. A BLDC motor controller developed with the dq-coordinate model cannot be implemented without several supplemental functions such as the coordinate transformation and a DC-to-AC current encoding scheme. A quasi-physical BLDC motor model is developed to study the practical implementation issues of the dq-coordinate control strategy, such as the initialization and rotor angle transducer resolution. This model can also be beneficial during first stage development in automotive BLDC motor applications

Recent Advances in Robust Control

Robust control has been a topic of active research in the last three decades culminating in H_2/H_\infty and \mu design methods followed by research on parametric robustness, initially motivated by Kharitonov's theorem, the extension to non-linear time delay systems, and other more recent methods. The two volumes of Recent Advances in Robust Control give a selective overview of recent theoretical developments and present selected application examples. The volumes comprise 39 contributions covering various theoretical aspects as well as different application areas. The first volume covers selected problems in the theory of robust control and its application to robotic and electromechanical systems. The second volume is dedicated to special topics in robust control and problem specific solutions. Recent Advances in Robust Control will be a valuable reference for those interested in the recent theoretical advances and for researchers working in the broad field of robotics and mechatronics

Adaptive control of the interior permanent magnet synchronous motors

Thesis contains: pages – 117, drawings – 38, tables – 23. The goal of the of the thesis lies in development of the control methods of the IPMSM with the purpose of its research and improvement of efficiency and performance of the electromechanical system. In this thesis, analytical review of the inductance determination methods for the IPMSM is presented. After that two tests for inductance determination of the interior permanent magnet synchronous motors are proposed, analyzed and experimentally verified. Four methods are proposed to use to obtain static and dynamic inductances from the tests data. Speed and position control algorithms are derived basing on the non saturated model of the motor and its effectiveness was researched by means of experiment and simulation for small saturated motors. After that position control algorithm with adaptation to the mechanical parameters is designed and tested via simulation. Stability is proved using the second Lyapunov method. Derived algorithms provide asymptotic tracking of the controlled coordinates, and decoupling of the direct current component and mechanic coordinate control subsystems.Магістерська дисертація містить: 117 сторінок, 38 рисунків, 23 таблиці. Метою роботи є розробка та розвиток методів керування явнополюсними синхронними двигунами з постійними магнітами, спрямований на покращення ефективності електромеханічної системи. В роботі представлено аналітичний огляд методів визначення індуктивностей IPMSM. Запропоно та експериментально впроваджено два тести для визначення індуктивностей. Отримані в тестах данi пропонується обробити чотирьма методами для отримання значень статичної та динамічної індуктивностей. Розроблено алгоритми керування швидкістю та подоженням на основі моделі, що не враховує насичення. Ефективність алгоритмів досліджена шляхом моделювання та експериментально для двигуна з низьким рівнем насичення. Після цього синтезовано алгоритм керування положенням з адаптацією до механічних параметрів. Стабільність системи доведена за допомогою другого методу Ляпунова. Отримані алгоритми забезпечують асимптотичне відпрацювання контрольованих координат та розв’язку підсистеми керування прямою компонентою струму та підсистемою керування механічними координатами