The doubly fed induction generator (DFIG)-based wind energy conversion systems (WECSs) are prone to certain uncertainties, nonlinearities, and external disturbances. The maximum power transfer from WECS to the utility grid system requires a high-performance control system in the presence of such nonlinearities and disturbances. This paper presents a nonlinear robust chattering free super twisting fractional order terminal sliding mode control (ST-FOTSMC) strategy for both the grid side and rotor side converters of 2 MW DFIG-WECS. The Lyapunov stability theory was used to ensure the stability of the proposed closed-loop control system. The performance of the proposed control paradigm is validated using extensive numerical simulations carried out in MATLAB/Simulink environment. A detailed comparative analysis of the proposed strategy is presented with the benchmark sliding mode control (SMC) and fractional order terminal sliding mode control (FOTSMC) strategies. The proposed control scheme was found to exhibit superior performance to both the stated strategies under normal mode of operation as well as under lumped parametric uncertainties.

A photovoltaic system generates energy that depends on the environmental conditions such as temperature, irradiance and the variations in the load connected to it. To adapt to the consistently increasing interest of energy, the photovoltaic (PV) system must operate at maximum power point (MPP), however, it has the issue of low efficiency because of the varying climatic conditions. To increase its efficiency, a maximum power point technique is required to extract maximum power from the PV system. In this paper, a nonlinear fast and efficient maximum power point tracking (MPPT) technique is developed based on the robust integral backstepping (RIB) approach to harvest maximum power from a PV array using non-inverting DC-DC buck-boost converter. The study uses a NeuroFuzzy network to generate the reference voltage for MPPT. Asymptotic stability of the whole system is verified using Lyapunov stability criteria. The MATLAB/Simulink platform is used to test the proposed controller performance under varying meteorological conditions. The simulation results validate that the proposed controller effectively improves the MPPT in terms of tracking speed and efficiency. For further validation of the proposed controller performance, a comparative study is presented with backstepping controller, integral backstepping, robust backstepping and conventional MPPT algorithms (PID and P&O) under rapidly varying environmental conditions.

In the direct torque control (DTC) of induction motor (IM) drive systems utilizing model predictive torque control (MPTC) in the inner loop and classical proportional integral (PI) control in the outer loop is prone to weaknesses, such as uncertainties, external disturbances, parameter variations, and nonlinear dynamics. A high-performance control system for speed and torque is required to guarantee a smooth and robust control architecture that can withstand such unpredictable effects. In this study, we propose an integral super twisting sliding mode control (ISTSMC) to address the shortcomings of the classical PI used in the outer loop of DTC drive systems. A sliding mode speed observer is also designed and utilized to overcome problems associated with mechanical sensors. The robustness of the proposed control strategy and fast dynamic speed response are compared favorably with a benchmark PI controller and conventional sliding mode control (SMC). The ability of the proposed system to regulate both speed and torque was evaluated through simulations, under various fault perturbations, parameter variations, and load disturbances, conducted in MATLAB/ Simulink. Various performance indices were used to demonstrate the superior performance of the proposed strategy compared to a benchmark PI system and conventional SMC-based MPTC approaches.

The smooth and robust injection of wind power into the utility grid requires stable, robust, and simple control strategies. The super-twisting sliding mode control (STSMC), a variant of the sliding mode control (SMC), is an effective approach employed in wind energy systems for providing smooth power transfer, robustness, inherent chattering suppression and error-free control. The STSMC has certain disadvantages of (a) less anti-disturbance capabilities due to the non-linear part that is based on variable approaching law and (b) time delay created by the disturbance and uncertainties. This paper enhances the anti-disturbance capabilities of STSMC by combining the attributes of artificial intelligence with STSMC. Initially, the STSMC is designed for both the inner and outer loop of a doubly fed induction generator (DFIG) based wind energy conversion system (WECS). Then, an artificial neural network (ANN)-based compensation term is added to improve the convergence and anti-disturbance capabilities of STSMC. The proposed ANN based STSMC paradigm is validated using a processor in the loop (PIL) based experimental setup carried out in Matlab/Simulink.

This article formulates a fully-distributed and delay-tolerant secondary control scheme for droop-controlled AC microgrids. The proposed strategy is inspired by the cooperative control concept of multi-agent systems (MASs). It considers the hierarchical control structure of the distributed energy resource (DER) units. It ensures equal active power sharing between three DER units, where each unit tracks the time-varying average load, with a finite-time convergence. As a result, the frequencies of the DER units are regulated to their nominal values. Furthermore, it offers plug-and-play capability for DER units, demonstrates significant robustness against load disturbances, and successfully tolerates, small as well as large, communication time-delays. Due to the fully-distributed configuration of the proposed control strategy, each DER unit in the test microgrid requires only its own information and information of its neighbors. The benefit is two-fold: not only this configuration assists in minimizing the overall bandwidth requirement, and cost of the corresponding communication network, but also it increases the reliability of the microgrid operation. The performance and effectiveness of the proposed technique is supported by exhaustive numerical simulations performed in Matlab/Simulink on an AC microgrid testbench comprising three DER units. The proposed strategy renders the superior performance in several aspects as compared to the existing developments in the literature in this area.