Finite control set-model predictive torque control (FCS-MPTC) has fast dynamic response because this algorithm directly selects the optimal voltage vector by its cost function for induction machine drives fed by voltage source inverter (VSI). However, belonging to open-loop control paradigm, FCS-MPTC has torque tracking error due to inevitable load disturbance and mismatched model parameters in reality. In traditional FCS-MPTC, the outer loop, i.e. speed loop, adopts classic proportional integral (PI) controller, abbreviated as PI-MPTC. The lumped disturbance is only suppressed by PI controller. However, pole placement of PI controller is usually designed by cut-and-trial, which is difficult to simultaneously achieve optimal dynamic performance and optimal suppression of lumped disturbance. In this paper, FCS-MPTC with mismatched parameters is firstly analyzed. Secondly, the deficiencies of traditional PI controller are introduced. Thirdly, disturbance feedforward compensation based-model predictive torque control (DFCB-MPTC) of induction machine is proposed to compensate lumped disturbance and improve the performance of system. Furthermore, an simplified stator flux observer is proposed, which gain matrix is independent of rotor speed. Experimental results verify the feasibility of the proposed DFCB-MPTC. Compared with traditional PI-MPTC, The proposed DFCB-MPTC has better dynamic performance, steady performance and stronger robustness.

High-altitude ventilator has been utilized to blow the air into airship airbags to achieve flight control of the stratospheric airship. Owing to the thin air in the stratosphere, high-altitude ventilator induction motor operates at high-speed light-load condition. The traditional minimum stator current operation (TMSCO) is employed to minimize conduction and switching losses below the rated speed. This paper extends this concept to the field weakening region, and puts forward the extended minimum stator current operation (EMSCO) to obtain high efficiency at any speed. The EMSCO criterion is formalized as constrained optimization problem which is solved by breaking down into subproblems. The proposed EMSCO maps the torque reference onto the optimal field current and torque current references. In addition, optimal duty cycle-model predictive current control (ODC-MPCC) is proposed to reduce the current ripple and computation burden compared with traditional model predictive current control(TMPCC). In ODC-MPCC, the novel cost function based on deadbeat voltage vector reduces the computation burden. The proposed ODC-MPCC of induction motor with EMSCO is verified effectively by simulation and experiment, which is compared with the traditional control strategy of induction motor.

Phase-locked loops (PLLs) are widely popular in applications of grid synchronization for single- and three-phase utility power systems. However, these PLL-based methods are usually designed for constant frequency grids and these schemes only have fast dynamics and good accuracy in a small local region (i.e., phase locked region). When applying these PLLs in the grids of more electric aircraft (MEA), in which the grid frequency varies in a wide range (360 Hz-800 Hz), both the dynamic response and the steady-state accuracy of PLLs reduce significantly. In light of this, this paper presents a global convergence method to estimate the frequency, positive- and negative-sequence components of grid voltage in MEA power systems. By analyzing the relationship between the DC-offset component, the grid voltage and their derivatives, a mathematic model with the unknown parameters, which are the DC-offset component and the grid frequency, is established. Accordingly, a global estimator is proposed to estimate the grid voltage parameters accurately. A Lyaponov-based argument ensures that the proposed estimator is global convergent and it has the capability to eliminate the DC offset effect completely. The experimental results are provided to verify the effectiveness of the proposed estimator.

Due to the star connection of the windings, the impact of the third harmonic which does not exist in three-phase permanent magnet synchronous motor (PMSM) cannot be ignored in five-phase PMSM. So the conventional sensorless control methods for three-phase PMSM cannot be applied for five-phase PMSM directly. To achieve the sensorless control for five-phase PMSM, an iterative sliding mode observer (ISMO) is proposed with the consideration of the third harmonic impact. First, a sliding mode observer (SMO) is designed based on the fivephase PMSM model with the third harmonic to reduce the chattering and obtain the equivalent signal of the back electromotive force (EMF). Then, an adaptive back EMF observer is built to estimate the motor speed and rotor position, which eliminates the low-pass filter and phase compensation module and improves the estimation accuracy. Meanwhile, by iteratively using the SMO in one current sampling period to adjust the sliding mode gains, the sliding mode chattering and estimation errors of motor speed and rotor position are further reduced. Besides, the stability of the SMO and the adaptive back EMF observer are demonstrated in detail by Lyapunov stability criteria. Experiment results verify the effectiveness of the proposed observer for sensorless control of five-phase PMSM.

Taking advantage of the high reliability, multiphase permanent magnet synchronous motors (PMSMs), such as five-phase PMSM and six-phase PMSM, are widely used in fault-tolerant control applications. And one of the important fault-tolerant control problems is fault diagnosis. In most existing literatures, the fault diagnosis problem focuses on the three-phase PMSM. In this paper, compared to the most existing fault diagnosis approaches, a fault diagnosis method for Interturn short circuit (ITSC) fault of five-phase PMSM based on the trust region algorithm is presented. This paper has two contributions. (1) Analyzing the physical parameters of the motor, such as resistances and inductances, a novel mathematic model for ITSC fault of five-phase PMSM is established. (2) Introducing an object function related to the Interturn short circuit ratio, the fault parameters identification problem is reformulated as the extreme seeking problem. A trust region algorithm based parameter estimation method is proposed for tracking the actual Interturn short circuit ratio. The simulation and experimental results have validated the effectiveness of the proposed parameter estimation method.