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Transient response performance and steady-state operation performance are the two most important performance indicators of a motor drive system. In order to solve these two problems, this study proposes a new induction motor (IM) model, and then designs a new simplified linearization controller method. First, the tangential force that determines the transient process of the motor is represented by electromagnetic torque, and the radial force is represented by reactive torque. Then, the dual-torque model of IM is derived, which not only accurately shows the rotating air-gap magnetic field through the amplitude and rotating angular frequency, but also visually demonstrates the physical essence of the transient process of IM. Then, this study proposes a simplified feedback linearization method without the analysis of zero dynamic. In addition, a time-scale hierarchical control system is designed to reduce the ripple caused by the coupling of different time-scale variables. The experimental results show that the steady-state torque ripple of the proposed method is 65% lower than that of RFOC, and the torque response speed is 10% higher than that of DTC.

The safety of direct torque control (DTC) is strongly reliant on the accuracy and consistency of sensor measurement data. A fault-tolerant control paradigm based on a dual-torque model is proposed in this study. By introducing the vector product and scalar product of the stator flux and stator current vector, a new state variable is selected to derive a new dual-torque model of induction motor; it is combined with a current observer to propose a dual-torque model fault-tolerant control method. This technology calculates torque and reactive torque directly, reducing the system’s reliance on sensors, avoiding sensor-noise interference, and improving torque response speed while suppressing torque ripple. In addition, to improve system dependability and safety, a fault-tolerant control method is devised by combining the model with an adaptive virtual current observer. Ultimately, experiments validate the suggested method’s effectiveness and feasibility.

This study introduces a distributed secondary control method-based adaptive pinning control for inverter-based distributed generations (DGs) in an isolated microgrid (MG) structure with frequency and voltage compensation and power sharing. Without MG centre controller or energy management system, local DGs’ controllers have no global information of the whole communication network, which is the second smallest eigenvalue of the Laplacian matrix. In practice, the large coupling weight gains are mostly selected. However, a sufficient large coupling weight may cause instability. It is difficult to choose the coupling weight in the fully distributed complex network. To solve the above problems, the authors investigate a pinning control for synchronisation using the local adaptive pinning algorithm on coupling weight gains. The proposed method has the advantage that the consensus controller design is independent of the Laplacian matrix associated with the communication network. And the collective dynamics of the communication network can be adjusted to steady states without global information. However, the adaptive pinning control scheme is not suitable for the multi-disturbance situation, which will accumulate the coupling weight and even cause integral saturation. Therefore, an improved strategy is proposed to adapt to the load changing conditions for islanded MGs.

Multiple nearby isolated microgrids (MGs) can be interconnected to become multi-MGs (MMGs) and meet larger bulk power demands, thus improving reliability/security of MMGs and reducing the power supply investment costs. However, a multi-layer control structure and complex communication network are inevitable, which increase communication delays and complicate the control structure. To solve this problem, this article introduces a distributed secondary control (DSC) based on cluster consensus of inhibitory coupling with a power limit scheme. Compared with an inter-cluster communication coupling structure, the communication channels of the proposed scheme are minimised to simplify network topology, decrease the communication delays and control dimensions. The proposed control strategy reaches multi-valued consensus states for accurate active/reactive power sharing in different MGs. Furthermore, active/reactive power overloading in a MG cluster is discussed under an inhibitory coupling configuration. Based on the power limit scheme, each distributed generator (DG) of the overloaded MG is controlled to generate power within the rated power range for high local autonomy. In addition, an adaptive virtual impedance control is introduced to decrease voltage deviations between DGs. The analytical results are verified by a simulation in MATLAB/Simulink.

Tedious adjustment of the weighting factor restricts the wide application of conventional model predictive torque control (MPTC) for induction motors (IMs) in practice. To solve this problem, this study introduces a new variable R (reactive torque) to control the flux of IM, which is the dual of torque T , with radial orientation and in relation to reactive power. Then, a novel MPTC strategy based on variable R and torque T is proposed and named RT-MPC. Compared with conventional MPTC, RT-MPC uses a pair of variables with the same dimensions and time scales instead of the torque and flux amplitude in MPTC. This approach eliminates the weighting factor of the cost function, unifies the time scales of control variables, and avoids prediction of rotor flux at the ( k + 2) instant. Simulation and experimental results show that RT-MPC can avoid the weighting factor, reduce switching frequency, and reduce control complexity. RT-MPC can also maintain excellent dynamic and steady-state performance similar to conventional MPTC. Hence, the proposed method is expected to be more practical.