In order to achieve faster speed tracking ability with lower thrust ripple for the linear induction machine (LIM), one robust speed control strategy using sliding mode direct thrust control (SM-DTC) is firstly proposed based on the space vector modulation (SVM) technique with the secondary flux-linkage orientation. Then, one improved maximum thrust per ampere (MTPA) technique is presented to further minimize the primary current and copper loss under the constant output thrust. Full comparison has been made among the proposed SM-DTC, the conventional direct thrust control (DTC) and field orientation control (FOC) methods in different typical working states. Comprehensive simulation and experiments have been done on the basis of two 3 kw arc induction machines (as one demonstration prototype for the real LIM), which adequately confirm that the proposed method can successfully get faster dynamic response with lower thrust ripple.

In recent decades, there has been a growing interest in the design and development of power loss reduction in electric drive systems. To realize the full potential of the Brushless DC motor (BLDCM), the design methodology of an effective intelligent controller is vital. On the other hand, the Landsman converter is used in a bridgeless configuration to enhance the power factor and minimize the power loss of the BLDCM. In addition, BLDCM utilizes the different intelligent controllers that are used to decrease power loss. The performance of the Landsman converter and CSC converter is analyzed concerning various configurations/stages, and the numerical MATLAB 2016a simulation results are discussed to arrive at the suitable intelligent controller for the BLDC motor, and comparison results are presented. The proposed converter is designed and validated using hardware implementation by minimizing power loss. Effectiveness can be tested and valued for the proposed controller for the various intelligent controllers of BLDCM.

In this article, a new supertwisting sliding mode direct thrust control (NSTSM-DTC) scheme is proposed to improve the dynamic response, robustness ability of the linear induction machine, and overall drive performance. First, a NSTSM algorithm is proposed and implemented in both electromagnetic thrust and primary flux-linkage control loops. The design aspects, implementation process, and stability analysis of the NSTSM based on the DTC method are fully investigated, which can effectively achieve faster dynamic response, smaller steady state speed tracking error, lower electromagnetic thrust ripple, and increase the system robustness against load variation in comparison to those of the conventional control methods. The proposed method is fully confirmed by the comprehensive simulations and experiments based on one prototype of 3 kW arc induction machine.

This article proposes coordinated model predictive control (MPC) techniques for a DC-coupled hybrid microgrid system with solar photovoltaic and wind generated system. To achieve optimum power generation in the microgrid, the finite-control-set MPC (FCS-MPC) controls both PV-wind generated power using a DC-DC converter and a controlled rectifier. The mathematical formulation of the proposed hybrid microgrid system is described, and maximum power point tracking is employed to guarantee that the grid receives the maximum power. Furthermore, the 3-Փ bidirectional two-level inverter is connected between the DC-bus and AC grid which is controlled by the grid side FCS-MPC controller. The FCS-MPC is used in all system control parts, eliminating the use of four proportional controllers (PI) and giving a better dynamic response. Additionally, the outcomes are evaluated in comparison to current techniques. The proposed power management technique is also based on the relationship between the overall demand and the produced power provided by both WDG and PV sources. Due to the unpredictability of the sources, several scenarios, including (i) Fixed radiation and fixed wind speed, (ii) Wind speed variation and constant radiation, and (iii) Changing solar radiation and steady wind speed, are considered to validate the performance of the proposed scheme. The findings are then discussed.

In this study, the analysis and control of a multi-phase linear induction motor loaded with a variable mechanical system are carried out. Mathematical models are established, and simulation results are analyzed for an improved proportional–integral–derivative controller with closed-loop vector control for PLIM. To make the PID controller more responsive to load thrust disturbances, a fuzzy PID load thrust observer was developed. The FPID is similarly based on space-vector modulation DTC technology to regulate the PLIM’s speed, flux, and thrust. The FPID output is used to calculate the reference thrust force, which is compared to the actual thrust value to calculate the second error. To maintain the linear speed of the PLIM at the specified reference values and at different load values, the FPID controller settings are adjusted. Four indicators were used to compare the capabilities of the FPID controller with those of the conventional PID controller in order to evaluate the performance of PLIM in both cases. These indices represent the individual SSE for each operational phase and the total SSE for the entire loading period. According to the simulation results, the FPID works better than a regular PID when used to adjust the operation of DTC-SVM to drive a PLIM to improve the overall system performance. The simulation results using MATLAB Simulink for a PLIM-drive system show that the proposed FPID control provides improved control behavior and operating performance with fast and accurate speed tracking.