The sensorless control of the permanent magnet synchronous motor (PMSM) has attracted wide attention due to its high reliability, economic and safety benefits. A fast and high-precision rotor-position estimation is inevitable for the implementation of sensorless control. Sliding-mode observer (SMO) is a preferred solution for sensorless control by many industrial companies. This article addresses the comparison of different switching functions employed in the control structure of sensorless field-oriented control with SMO. The switching functions are classified and their influence on the performance of the PMSM is verified for different shaping coefficients (SC). In addition, a statistical evaluation of the switching functions is provided to find the optimal values of SC. An experimental and statistical evaluation validated the substitutability of signum and hyperbolic switching functions and optimal values of SC have been found.

The fault-tolerant control system (FTCS) for a permanent magnet synchronous motor (PMSM) is presented and an analysis of speed sensor faults is proposed in this paper. The detection and compensation of speed sensor faults is based on the simple comparison of the measured signals with the signals estimated by reduced-order sliding mode observer (SMO). The focus of the work is on the presentation of simulation and experimental research for the most common speed sensor failure types: complete signal loss, gain error, and measurement noise. Additionally, an analysis of different operating conditions of the PMSM drive system is presented, which highlights the system’s behaviour under various conditions. The presented algorithm enables the fast detection and compensation of failures with very short detection times, making it a versatile solution for a PMSM drive system and improving its overall reliability.

This paper presents a novel speed sensor fault detection, classification, and compensation mechanism in a permanent magnet synchronous motor (PMSM) drive system. Application is based on state variable observers and shallow neural networks (NN). Classical fault detection mechanism based on state variable observers has been extended with neural networks. This enables improved detection efficiency and increases immunity to false alarms. In addition, the use of neural networks allowed for the classification of the failure type. Three types of failures are considered in the paper: signal loss, scaling error, and signal interference. The detection efficiency of the proposed solution is about 97%. On the other hand, the classification of the worst type of failure—signal loss—was achieved at the level of 100%. Other considered failure types are classified at the level of 80–90%. In addition, tests were carried out for two types of observers—model reference adaptive system and sliding mode observer—to compare the results. The work presents experimental results carried out for various operating conditions of the drive system. The failure classification times in the experimental tests were achieved at a level of less than 30 ms.

Five-phase induction machines (5pIMs) are a viable alternative for a wide range of industrial applications. The penetration of drives with 5pIM into industrial applications is slow because of the complexity of the proposed control algorithms. In standard control of induction machines, the stator current is not controlled directly and options for current limitation are restricted. This paper hence addresses a novel current limitation technique for the control algorithm of 5pIM. In addition, a simple speed sensorless control algorithm based on the slip compensation is introduced. A combination of both algorithms is suitable for low-cost medium-precision drive applications. Experimental results, realized on Texas Instruments F28335 DSP, illustrating the performance of novel current limitation technique and sensorless control, are included.

The sensorless control of the permanent magnet synchronous motor (PMSM) has attracted wide attention due to its economic and safety benefits. A fast and high-precision rotor-position estimation is necessary for the implementation of sensorless control. In low-speed region, high frequency (HF) signal injection methods are mostly adopted. They suffer to bandwidth deterioration as some digital filters must be included in the current feedback loop or the speed observation signal processing. The HF signal injection method based on the injection of voltage pulses is presented in this paper together with its implementation in MATLAB/Simulink. The method is based on the injection of voltage pulses where injection itself is separated from the motor control algorithm. The simulation results show that the proposed method has good dynamic performance for the sensorless control of PMSM.