This study proposes a way of designing a reliable voltage controller for buck DC/DC converter in which the terminal attractor approach is combined with an enhanced reaching law-based Fast Terminal Synergetic Controller (FTSC). The proposed scheme will overcome the chattering phenomena constraint of existing Sliding Mode Controllers (SMCs) and the issue related to the indefinite time convergence of traditional Synergetic Controllers (SCs). In this approach, the FTSC algorithm will ensure the proper tracking of the voltage while the enhanced reaching law will guarantee finite-time convergence. A Fuzzy Neural Network (FNN) structure is exploited here to approximate the unknown converter nonlinear dynamics due to changes in the input voltage and loads. The Fuzzy Neural Network (FNN) weights are adjusted according to the adaptive law in real-time to respond to changes in system uncertainties, enhancing the increasing the system’s robustness. The applicability of the proposed controller, i.e., the Adaptive Fuzzy-Neural Fast Terminal Synergetic Controller (AFN-FTSC), is evaluated through comprehensive analyses in real-time platforms, along with rigorous comparative studies with an existing FTSC. A dSPACE ds1103 platform is used for the implementation of the proposed scheme. All results confirm fast reference tracking capability with low overshoots and robustness against disturbances while comparing with the FTSC.

This paper discusses the use of the concept of classical and predictive direct power control for shunt active power filter. These strategies are used to improve the active power filter performance by compensation of the reactive power and the elimination of the harmonic currents drawn by non-linear loads. A theoretical analysis followed by a simulation using Matlab/Simulink software for the studied techniques have been established. Moreover, two tests bench have been carried out using the dSPACE card 1104 for the classic and predictive DPC control in order to evaluate the studied methods in real time. Obtained results are presented and compared in the present paper to confirm the superiority of predictive technique. To overcome the pollution problems caused by the consumption of fossil fuels, renewable energies are the alternatives recommended to ensure green energy. In the same context, the tested predictive filter can be easily supplied by a renewable energy source that will give its impact to enhance the power quality.

Direct torque control of asynchronous motors has good dynamic performance of torque and flux. However, the use of hysteresis controllers leads to a variable switching frequency. This lack of control over frequency is the origin of torque and flux ripples. To overcome these problems, this article proposes modified fuzzy direct torque control for an induction motor. In addition, a three-phase pulse width modulation rectifier controlled by the fuzzy direct power control is used. This rectifier draws a sinusoidal current from the grid and operates with a power factor close to unity. The pulse width modulation rectifier feeds the inverter of the direct torque control, ensuring a speed control loop. The proposed direct torque control–direct power control method is investigated based on theoretical analysis, computer simulation, and experimental validation that provide acceptable results.