This study introduces a $k$ -step look-ahead active concurrent learning-based dual control of exploration and exploitation (KSLCL-DCEE) framework designed to address the challenges of auto-optimization in systems with unknown references and environments, inherently balancing parameter estimation and optimal reference tracking. The KSLCL-DCEE algorithm incorporates two loops that employ future gradients of the cost function to generate the subsequent control command by looking ahead $k$ -steps: the inner loop generates $k$ -step look-ahead gradients (i.e., estimated reference trajectory), while the outer loop utilizes the gradient at the $k$ th step to generate the dual control commands which act on a general linear system. Active concurrent learning with a modified learning rate in the initial period is introduced to relax the reliance on the condition of persistent excitation and achieve faster convergence. A comprehensive stability analysis of KSLCL-DCEE is provided. The effectiveness and performance of KSLCL-DCEE are demonstrated through numerical studies and applications on photovoltaic (PV) arrays.

High-precision smooth speed regulation in permanent magnet synchronous motors (PMSMs) is challenged by torque ripple, parameter mismatches, and load fluctuations. Considering the uncertain nature of these disturbances, neural network (NN)-based methods provide superior applicability compared to internal model approaches due to their frequency-independent characteristics. However, most of these methods utilize feedforward NNs designed via asymptotic stability theory, which exhibit severe output distortions stemming from abrupt error surges and prolonged convergence times under varying operating conditions. To address these issues, this article proposes a robust speed control framework that integrates a recurrent NN (RNN) with fixed-time sliding-mode control (FTSMC), theoretically guaranteeing closed-loop fixed-time stability even under input saturation. Specifically, the RNN employs an internal recurrent loop to leverage historical context, thereby reducing the network output's susceptibility to instantaneous error spikes and alleviating transient distortions. Furthermore, incorporating FTSMC principles into the weight update law design accelerates the network's learning process, ensuring accurate approximation of periodic disturbances while shortening the transient period. Extensive experimental results validate the effectiveness of the proposed scheme across diverse operating scenarios.

The inverter nonlinearity induces current harmonics and mismatches between permanent magnet synchronous machine reference voltages and terminal voltages, which will degrade the sensorless drive system performance, especially at the low-speed range. In this paper, a radial basis function neural network (RBFNN)-based voltage compensator is proposed to suppress the current ripple. Without the requirement of any additional hardware or complex signal analysis procedure and processing algorithm, the RBFNN is self-tuned to directly generate the compensation voltage with the objective to minimize the current tracking error, so as to improve the active flux modeling accuracy and reduce position and speed estimation fluctuation.

In this paper, the influence of full-pitch and shortpitch windings on the torque and power factor of permanentmagnet vernier (PMV) machines is studied.It is well known that the short-pitch (SP) winding has shorter end windings but with a lower winding factor.Thus, to achieve the largest torque, the full-pitch (FP) winding is preferred in PMV machines.However, it is found in this study that the SP winding, rather than the FP winding, is a better choice to achieve higher output torque of PMV machine at a high power factor level under the same PM consumption.The advantages of SP winding are even more obvious at higher electric loading and higher power factor levels.The theoretical analysis indicates that both torque and power factors are influenced by the winding factor, providing the possibility of better performance of the SP winding than the FP winding.This is further confirmed by the optimization results after performing the multi-objective optimization considering torque, power factor, and PM consumption.Finally, a prototype is manufactured and tested to validate the analysis.

Active disturbance rejection control (ADRC) is promising for permanent magnet synchronous machine (PMSM) speed regulation system. However, the control performance of ADRC scheme is generally affected by the measurement noise introduced by position sensors. To solve this problem, a high-order nonlinear extended stated observer (NESO) is proposed in this paper to directly estimate the motor speed. The bode diagrams of the high-order NESO based measurement noise suppression system obtained by frequency-sweep approach are illustrated to show its frequency domain characteristics. Taking full advantage of nonlinear control and high-order observer techniques, the proposed strategy can maintain satisfactory noise suppression performance without sacrificing the robustness of PMSM system. Comprehensive experimental results are conducted to verify the superior properties of the proposed control strategy.

The existing dead beat-direct torque and flux control under M-T framework (DB-DTFC-MT) strategy achieves fast dynamic response as well as robustness. But by nature, the DB control strategy only uses proportional control which is not able to eliminate the steady-state error when a disturbance happens. To be more specifically, one of the remaining issues in DB-DTFC-MT is when a disturbance caused by motor parameters variation happens, there will be an obvious steady-state error in the torque as well as flux control loops causing deterioration to the control performance. In this paper, active disturbance rejection control (ADRC) technique containing two extended state observers are adopted in DB-DTFC-MT strategy. The designed DB-ADRC strategy is able to estimate as well as compensate the disturbances resulting in the voltage vectors. Hence, the robustness of DB-DTFC-MT to motor parameters mismatch is further improved. The designed control scheme is verified on a real-time control platform in reliance on dSPACE MicroLabBox with a surface mounted permanent magnet synchronous motor.

This paper presents a high power-factor permanent magnet vernier machine (PMVM) employing hybrid concentrated-winding (CW). The hybrid winding, carrying both delta- and star-winding sets, allows for low harmonic tooth-wound coil and satisfied winding factor for PMVM with high gear ratio. Therefore, the torque density of the PMVM can be enhanced with reduced end-winding length and more compact structure. More importantly, the mutual inductances between the three phases and the coils that comprise each phase are reduced to a large extent in the hybrid winding, without deteriorating the output torque capability. As a result, the presented PMVM possesses a lower ratio of inductance to PM flux linkage due to the low-harmonic and low-coupling winding, and hence, improved power factor. Two benchmark PMVMs with identical gear ratio have been optimized for comparison. Further finite element results verify that the proposed CW PMVM presents superior performance in terms of end-winding length, torque density, power factor, and efficiency. It is revealed the proposed hybrid CW PMVM can improve the torque density to 23Nm/L from 21Nm/L and 14Nm/L, with the consideration of end-winding volume, and power factor to 0.86 from 0.72.

This paper investigates the two-slot pitch winding vernier machine by stator shifting technique (SST). It shows that the conventional two-slot pitch winding vernier machine can be generated by SST with a special stator shift angle. This paper contributes to exploring other shift angles and their influences on machine performances. Analysis results indicate that different shift angles have a great effect on the armature winding magnetomotive force (MMF) harmonic contents and the flux modulation effect. Consequently, the phase inductance, power factor, core losses, and torque capability will be affected. A single-layer 24-slot/10-pole vernier machine is investigated for verification, and the results show that with an appropriate shift angle, the power factor is improved from 0.6 to 0.7, the iron losses are reduced by 24.5%, and the efficiency is improved by 0.7%, with a slight torque drop of 2.9%.