Stability analysis of sensorless speed control of IPMSM

Abstract

In the speed control of an interior permanent magnet synchronous motor (IPMSM), for stability reasons, the closed-loop pole positions should be on the left-hand side of the S-plane, and for fast response requirements these poles should have a small time constant. Unfortunately, the motor poles have a very long time constant, which makes the system response very slow. To solve this problem, the zeros of PI controllers are used to compensate the motor poles. As the motor operates, the temperature increases, which changes the parameters of the motor and, accordingly, the motor poles change their position so the PI controller cannot compensate these poles. To solve this problem, many parameter estimation algorithms have been used to detect new parameter values and adapt the PI controller gains so that to compensate the motor poles continually. These parameter estimation algorithms complicate and add cost to the system. This paper demonstrates that, for a temperature up to 70 • C, the system is capable of giving fast response and stable operation by using a good design of the PI controller regardless of the parameter changes.

Sensorless Control of Permanent Magnet Synchronous Motor Based on Optimization of Non-Singular Fast Terminal Sliding Mode Observer, 138-144.

“…These algorithms can replace the mechanical sensors and obtain real-time rotor position information, thus enabling a sensorless control of PMSM [1]. In the field of sensorless control of PMSM, researchers have put forward many advanced theories and methods, such as model reference adaptive method [2]- [4], sliding mode observer (SMO) method [5]- [7] and neural network method [8]- [9]. In the three-phase PMSM control system, the error between given and feedback currents is used to reconstruct the reverse electromotive force (EMF) of the motor and estimate the rotor speed, which is called sliding mode control.…”

Partial observer canonical form for multi-output nonlinear forced system: a new method

“…The development of modern manufacturing industry guided by intelligent manufacturing is inseparable from the basic manufacturing equipment and integrated manufacturing system. For example, complex sensor networks are widely used in power grid, transportation system and industrial objects (Estrin et al, 1999;Akyildiz et al, 2002;Deng et al, 2015Deng et al, , 2017Hao et al, 2012;Li and Tong, 2016); and permanent magnet synchronous motor (PMSM) technology is widely used in modern power electronics technology, microchip technology and advanced control theory (Bae et al, 2001;Altaey and Kulaksiz, 2017;Schoonhoven and Uddin, 2016). However, the control system in the industrial plants, whether it is the sensor network or the servo system represented by the PMSM, is inseparable from the accurate measurement and estimation of the state in the system.…”