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There are two main types of speed/position sensorless closed‐loop variable‐speed electrical drives: sensorless and quasi‐sensorless drives. In sensorless drives, the classical speed and position sensors (transducers) are absent and are replaced by mathematical‐model‐based and/or artificial‐intelligence‐based estimators. In quasi‐sensorless drives, instead of conventional speed/position sensors, smart sensor bearings are used (e.g. SKF smart sensor bearings). The present paper discusses the latest developments in the field of sensorless and quasi‐sensorless variable‐speed high‐performance drives. Thus, a new family of sensorless and quasi‐sensorless induction motor and permanent magnet synchronous motor drives are also discussed (e.g. new sensorless vector and DTC drives, etc.). Methods which enable the operation of these drives at very low speed and also at zero stator frequency are discussed.

Sensorless interior permanent magnet in-wheel motor (IPMIWM), as an exemplar of modular automation system, has attracted considerable interests in recent years. This paper aims to investigate a novel hybrid control approach for the sensorless IPMIWM from a cyber-physical systems (CPS) perspective.

The control approach is presented based on the hybrid dynamical theory. In the standstill-low (S-L) speed, the rotor position/speed signal is estimated by the method of the high frequency (HF) voltage signal injection. The least square support vector machine (LS-SVM) is used to acquire the rotor position/speed signal in medium-high (M-H) speed operation. Hybrid automata model of the IPMIWM is established due to its hybrid dynamic characteristics in wide speed range. A hybrid state observer (HSO), including a discrete state observer (DSO) and a continuous state observer (CSO), is designed for rotor position/speed estimation of the IPMIWM.

The hardware-in-the-loop testing based on dSPACE is carried out on the test bench. Experimental investigations demonstrate the hybrid control approach can not only identify the rotor position/speed signal with a certain load but also be able to reject the load disturbance. The reliability and the effectiveness of the proposed hybrid control approach were verified.

The proposed hybrid control approach for the sensorless IPMIWM promotes the deep combination and coordination of sensorless IPMIWM drive system. It also theoretically supports and extends the development of the hybrid control of the highly integrated modular automation system.

The purpose of this paper is to investigate the need for a universal method for sensorless controlled induction motor drive diagnosis. The increasing number of sensorless control systems in industrial applications require a universal method for the drive diagnosis, which provides reliable diagnostic reasoning independent of control system structure and state variables measurement or estimation method.

Simulations and experimental investigation has been done with assumptions of multiscalar control system as a generalized vector control method, voltage source inverter application, sensorless control system based on selected speed observer structure and squirrel cage induction motor. Broken rotor symptoms are analyzed in the state variables and control system variables using DSP processing without outside measurement devices.

Symptoms of rotor asymmetry caused by broken rotor in the state and control variables was identified and symptoms amplitudes were compared. Based on the simulation and experimental results a new diagnosis method was proposed.

For early broken rotor detection there is a need to identify variables most sensitive to rotor asymmetry. In closed‐loop operation broken rotor symptom signals amplitudes are changed due to control system influence and in sensorless control due to used estimator frequency characteristics. The proposed method assumption is to aggregate symptoms in variables that altogether give results for broken rotor range regardless of applied control system structure or state variable estimator.

This paper shows control system influence to rotor fault symptom amplitudes in the state and control system variables. Identified phenomena is used for a new diagnosis method development.

This paper aims to present a novel position sensorless control scheme with fault-tolerance ability for switched reluctance motor at low speed.

First, the detection pulses are injected in the freewheeling and idle intervals of each phase. Second, the aligned position of each phase can be detected by comparing the consecutive rise time of detection current. Third, the whole-region rotor position and real-time rotational speed can be updated four times for the improvement of detection accuracy. Finally, the fault-tolerant control strategy is performed to enhance the robustness and reliability of proposed sensorless scheme under faulty conditions.

Based on proposed sensorless control strategy, the estimated rotor position is in good agreement with the actual rotor position and the maximum rotor position error is 1.5°. Meanwhile, the proposed sensorless scheme is still effective when the motor with multiphase loss and the maximum rotor position error is 1.9°. Moreover, the accuracy of the rotor position estimation can be ensured even if the motor is in an accelerated state or decelerated state.

The proposed sensorless method does not require extensive memory, complicated computation and prior knowledge of the electromagnetic properties of the motor, which is easy to implement. Furthermore, it is suitable for different control strategies at low speed without negative torque generation.

Direct Torque Control (DTC) of induction motor drives is a well-established technique owing to features such as fast dynamic and insensibility to motor parameters. However, conventional DTC scheme, based on comparators and the switching table, suffers from large torque and flux ripples. To improve DTC performance, this study aims to propose and implement a sensorless finite-state predictive torque control using extended Kalman Filter in dSPACE environment.

This paper deals with the design of an extended Kalman filter for estimating the state of an induction motor model and for sensorless control of systems using this type of motor as an actuator. A complex-valued model is adopted that simultaneously allows a simpler observability analysis of the system and a more effective state estimation.

Simulation and experimental results reveal that the drive system, associated with this technique, can effectively reduce flux and torque ripples with better dynamic and steady state performance. Further, the proposed approach maintains a constant switching frequency.

The proposed speed observer have been developed and implemented experimentally under different operating conditions such as parameter variation, no-load/load disturbances and speed variations in different speed operation regions.

The purpose is to present a sensorless control method by which high‐resolution rotor position information is estimated and used for phase‐advancing operation of a high‐speed permanent magnet (PM) brushless DC (BLDC) motor.

The proposed sensorless control approach uses hardware to observe the flux vector which is excited by rotor magnets. It can provide the rotor position which is the same as the phase angle of the observed flux vector.

High‐resolution rotor position signal of the BLDC motor for dynamic phase‐advancing control cannot be directly obtained from the conventional Hall‐effect sensors, or via the traditional back‐EMF‐based sensorless control strategies in which the back‐EMF may be even undetectable at high‐speed. The proposed rotor‐flux‐observer (RFO)‐based sensorless control method overcomes these problems, and meanwhile provides high‐resolution rotor position information for the phase‐advancing purpose.

The RFO‐based sensorless control is traditionally applied to PM brushless ac (BLAC) operations, where the motor voltage vector can be calculated from the inverter switching status. However, this is not readily applicable to a BLDC motor since the voltage of the floating phase cannot be calculated. Moreover, during high‐speed operation, the microprocessor may not be sufficiently fast to calculate the high‐resolution rotor position. Therefore, in this paper, it is proposed to use hardware to observe the rotor‐flux‐vector. The microprocessor only samples the vector's α‐ and β‐components and calculates the phase angle, hence, its burden is low. The proposed method is validated with a 1.8 kW 85,000 rpm BLDC motor system.

This study aims to design and implement a novel tilt integral sliding mode controller and observer for sensorless speed control of a permanent magnet synchronous motor (PMSM).

A control strategy combining the tilt integral derivative (TID) with sliding mode control (SMC) is proposed to determine the tilt integral sliding mode manifold. Using this manifold, tilt integral sliding mode controller (TISMC) and observer (TISMO) are designed. The stabilities are verified by using Lyapunov method. To prove the effectiveness and robustness of proposed methods, sensorless speed control of PMSM is performed for various operating conditions such as constant and variable speed references, load disturbance injection, parameter perturbation, whereas sensor noises are not taken into account. The performance of proposed method is compared with TID controller, proportional integral derivative controller and conventional SMO.

Simulation results demonstrate that TISMC and TISMO have better performance in all operating conditions. They are robust against parameter uncertainties and disturbances. TISM based sensorless control of PMSM is well guaranteed with superior performance.

The proposed method has not been tackled in the literature. By combining TID and SMC, novel tilt integral sliding manifold is presented and used in designing of the controller and observer. It is proven by Lyapunov method that errors converge to zero.

The purpose of this study is to improve the control performance of wind energy conversion systems (WECSs) by proposing a new sensorless, robust control strategy based on a Smith predictor active disturbance rejection control (SP-ADRC) associated with a speed/position estimator.

The estimator consists of a sliding mode observer (SMO) in combination with a phase-locked loop (PLL) to estimate the permanent magnet synchronous generator (PMSG) rotor position and speed. At the same time, the SP-ADRC is applied to the speed control loop of the variable-speed WECS control system to adapt strongly to dynamic characteristics under parameter uncertainties and disturbances.

Numerical simulations are conducted to evaluate the speed tracking performances under various wind speed profiles. The results show that the proposed sensorless speed control improves the accuracy of rotor speed and position estimation and provides better power tracking performance than a regular ADRC controller under fast wind speed variations.

This paper offers a new approach for designing sensorless, robust control for PMSG-based WECSs.

A new sensorless, robust control is proposed to improve the stability and tracking performance of PMSG-based WECSs. The SP-ADRC control attenuates the effects of parameter uncertainties and disturbances and eliminates the time-delay impact. The sensorless control design based on SMO and PLL improves the accuracy of rotor speed estimation and reduces the chattering problem of traditional SMO. The obtained results support the theoretical findings.

The puspose of this paper, a novel systematic design of fractional order proportional integral derivative (FOPID) controller-based speed control of sensorless brushless DC (BLDC) motor using multi-objective enhanced genetic algorithm (EGA). This scheme provides an excellent dynamic and static response, low computational burden, the robust speed control.

The EGA is a meta-heuristic-inspired algorithm for solving non-linearity problems such as sudden load disturbances, modeling errors, power fluctuations, poor stability, the maximum time of transient processes, static and dynamic errors. The conventional genetic algorithm (CGA) and modified genetic algorithm (MGA) are not very effective in solving the above-mentioned problems. Hence, a multi-objective EGA optimized FOPID (EGA-FOPID) controller is proposed for speed control of sensorless BLDC motor under various conditions such as constant load conditions, varying load conditions, varying set speed (Ns) conditions, integrated conditions and controller parameters uncertainty.

This systematic design of the multi-objective EGA-FOPID controller is implemented in MATLAB 2020a with Simulink models for optimal speed control of the BLDC motor. The overall performance of the EGA-FOPID controller is observed and evaluated for computational burden, time integral performance indexes, transient and steady-state characteristics. The hardware experiment results confirm that the proposed EGA-FOPID controller can precisely change the BLDC motor speed is desired range with minimal effort.

The conventional real time issues such as nonlinearity characteristics, poor controllability and stability.

It is clearly evident that out of these three intelligent controllers, the EGA optimized FOPID controller gives enhanced performance by minimizing the time domain parameters, performance Indices error and convergence time. Also, the hardware experimental setup and the results of the proposed EGA-FOPID controller are presented.

It shows the effectiveness of the proposed controllers is completely verified by comparing the above three intelligent optimization algorithms. It is clearly evident that out of these three intelligent controllers, the EGA optimized FOPID controller gives enhanced performance by minimizing the time domain parameters, performance Indices error and convergence time. Also, the hardware experimental setup and the results of the proposed EGA-FOPID controller are presented.

The purpose of this paper is to present a complete solution for speed sensorless AC drive with voltage source inverter, induction machine, and motor choke. Major problems with adjustable speed drives are underlined and the use of motor choke is justified. An AC drive with motor choke can work only if specific modifications in the control algorithms are done.

The goal of the paper is to present new nonlinear vector control method for induction motor drive. In the control system, the presence of motor choke is taken into account. The choke changes the structure of the predictive controller and state observer. The new concept of integrating the predictive controller with electromagnetic forces observer is presented. The paper presents theoretical description of the system as well the simulation and experimental verification.

The paper shows that the suggested decoupled AC drive control system is operating better than a system without decoupling. The system with motor choke requires modifications in the current controller and observer system. With omitting the motor choke a speed sensorless drive cannot work properly.

The solution is oriented for industrial applications because in numerous industrial dives the motor choke is utilized. However, with motor choke many sophisticated control algorithms cannot work properly. The concept presented in the paper solves such practical problems.

The paper presents a completely new decoupled field‐oriented control system with load angle controller, predictive current controller and state observer for AC drive with motor choke.