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The inverter dead time effect is non-negligible for the control performance of sensorless synchronous reluctance motor (SynRM) drives at low speeds. In this paper, a reduced-order observer-based sensorless control method for SynRM drives combined with the adaptive linear neurons (ADALINE)-based dead-time compensation is proposed. The reduced-order observer-based sensorless control method is presented, for which is parameter tuning is easy. On this basis, the dead-time compensation strategy using ADALINE filters is proposed to reduce the voltage harmonics effect on the estimation performance of the reduced-order observer. With ADALINE filters, the sixth current harmonic can be successfully filtered out by compensating the voltage directly or fitting the current to compensate the voltage. In this way, the low-speed estimation performance of the reduced-order observer is improved. The effectiveness of the proposed method is verified on a 3 kW SynRM experimental platform.

Wireless technology is increasingly significant in today’s industrial landscape. Standards like WirelessHART, ZigBee, and ISA100.11a are being widely used. However, despite their widespread use, wireless networks may sometimes be susceptible to packet loss or drops, making closed-loop systems vulnerable and resulting in system failure. To prevent such issues, dead-time compensation is necessary. The conventional techniques of predictive PI are commonly used for this purpose. Still, they must perform optimally for wireless networks with dead time, and set-point variations can affect network stability. To address this, a fractional calculus-based predictive PI compensator is proposed in this paper for wireless networks in process industries to improve the performance of these compensators. Industrial processes that involve wireless measurement and control actions in the pressure process model are used to evaluate the proposed compensator. The wireless network’s performance is assessed for packet loss, reduced throughput, and increased latency, and the proposed compensator outperforms traditional ones to achieve better set-point characteristics.

This paper proposed a dead-time compensation method with fractional-order proportional integral (FOPI) error voltage control. The disturbance voltages caused by the power devices’ dead time and non-ideal switching characteristics are compensated for with the FOPI controller and fed to the reference voltage. In this paper, the actual error voltage is calculated based on the model and actual voltage of the permanent magnet synchronous motor. Considering the parameter error of the permanent magnet synchronous motor and the voltage error caused by the dead-time effect, a FOPI controller is used to calculate the compensation voltage. An improved particle swarm optimization (PSO) algorithm is utilized to design the parameters of the FOPI controller in order to eliminate the dead-time effect, and the optimal fitness function is designed. Compared with other optimization algorithms, the improved PSO algorithm can achieve faster convergence speed in the error voltage controller parameter design. The proposed dead-time compensation method can improve the performance of the current response and eliminate the dead-time effect. This method also eliminates all harmonic disturbances and has a good suppression effect on high-frequency harmonics. The simulation and experimental results show that the dead-time compensation method using optimal FOPI error voltage control makes the current ripple smaller and the response speed faster than that of the traditional optimal integer-order PI control, thus demonstrating the effectiveness and advantages of the proposed method.

The article reviews the results of a number of recent papers dealing with the revision of the simplest approaches to the control of first-order time-delayed systems. The concise introductory review is extended by an analysis of two discrete-time approaches to dead-time compensation control of stable, integrating, and unstable first-order dead-time processes including simple diagnostics of the model used and focusing on the possibility of simplified but reliable plant modelling. The first approach, based on the first historically known dead-time compensator (DTC) with possible dead-beat performance, is based on the reconstruction of the actual process variables and the compensation of input disturbances by an extended state observer (ESO). Such solutions play an important role both in a disturbance observer (DOB) based control and in an active disturbance rejection control (ADRC). The second approach considered comes from the Smith predictor with two degrees of freedom, which combines feedforward control with output disturbance reconstruction and compensation by the parallel plant model. It is shown that these two approaches offer advantageous properties in the case of actuator limitations, in contrast to the commonly used PID controllers. However, when applied to integrating and unstable first-order systems, the unconstrained and possibly unobservable output disturbance signal of the second solution must be eliminated from the control loop, due to the hidden structural instability of the Smith predictor-like solutions. The modified solutions, usually referred to as filtered Smith predictor (FSP), then no longer provide a disturbance signal and thus no longer fully fit into the concept of Industry 4.0, which is focused on further optimization, predictive maintenance in dynamic systems, diagnosis, fault detection and fault identification of dynamic processes and forms the basis for the digitalization of smart production. Nevertheless, the detailed analysis of the elimination of the unstable disturbance response mode is also worth mentioning in terms of other possible solutions. The application of both approaches to the control of a thermal process shows almost equivalent quality, but with different dependencies on the tuning parameters used. It is confirmed that a more detailed identification of the controlled process and the resulting higher complexity of the control algorithms does not necessarily lead to an increase in the resulting quality of the transients, which underlines the importance of the simplified plant modelling for practice.

The advent of renewable energy resources and distributed energy systems herald a new set of challenges of power quality, efficient distribution, and stability in the power system. Furthermore, the power electronic converters integration has been increased in interfacing alternate energy systems and industries with the transmission and distribution grids. Owing to the intermittency of renewable energy resources and the application of power electronic converters the power distribution faces peculiar challenges. The dead-time effects are among the main challenges, which leads to the distortion of third harmonics, phase angle, torque pulsation, and induction motor current, causing severe quality problems for power delivery. To tackle these problems, this paper proposes a novel dead time compensation technique for improving the power quality parameters and improving the efficiency of power converters. The proposed model is simulated in MATLAB and the parametric equations are plotted against the corresponding parametric values. Furthermore, by implementing the proposed strategy, significant improvements are attained in the torque pulsation, speed, and total harmonic distortion of the induction motor. The comparisons are drawn between with and without dead time compensation technique, the former shows significant improvements in all aspects of the power quality parameters and power converters efficiency.