This paper presents the design, implementation, and comparative analysis of three current control strategies for a 0.2 MW three-phase Neutral Point Piloted (NPP) T-type inverter connected to the grid. The study compares Proportional–Integral (PI) controller, a first-order Sliding Mode Controller (SMC), and a Pseudo–Second–Order Super–Twisting Sliding Mode Controller (STSMC), all applied to the inner current control loop. The inverter is modeled with an RL output filter for current shaping and grid interfacing. While PI controllers offer simplicity, they suffer from limited disturbance rejection and tracking performance. Classical SMC improves robustness but introduces chattering. The proposed STSMC reduces chattering while preserving the benefits of SMC. Simulation results in MATLAB/Simulink assess each controller’s performance in terms of power injection and harmonic compliance with IEEE 519. The study highlights the superior transient and steady-state behavior of higher-order SMC methods.

DC microgrids (DCMG) enable efficient integration of renewable energy systems (RES) and energy storage systems (ESS). However, stability under constant power loads and disturbances remains challenging. Existing studies often overlook how control strategies concretely improve stability. This paper focuses on the dc/dc boost converter within the ESS and investigates how the introduction of a disturbance observer can improve overall system performance. A comprehensive model of the DCMG, including the RES, ESS, and electric vehicle (EV) loads, is established. Control strategies and observer design are presented, followed by a stability analysis using the minor loop gain methods. Simulation results validate the theoretical analysis and demonstrate improved dynamic response and robustness of the overall system.

The problem of learning-based control for robots has been extensively studied, whereas the security issue under malicious adversaries has not been paid much attention to. Malicious adversaries can invade intelligent devices and communication networks used in robots, causing incidents, achieving illegal objectives, and even injuring people. This article first investigates the problems of optimal false data injection attack scheduling and countermeasure design for car-like robots in the framework of deep reinforcement learning. Using a state-of-the-art deep reinforcement learning approach, an optimal false data injection attack scheme is proposed to deteriorate the tracking performance of a robot, guaranteeing the tradeoff between the attack efficiency and the limited attack energy. Then, an optimal tracking control strategy is learned to mitigate attacks and recover the tracking performance. More importantly, a theoretical stability guarantee of a robot using the learning-based secure control scheme is achieved. Both simulated and real-world experiments are conducted to show the effectiveness of the proposed schemes.

In the high frequency boost power factor correction (PFC) converter, it is necessary to obtain the phase of the grid side voltage. However, in some cost-sensitive applications, there is only a sensor to detect the rectified voltage. This paper proposes a digital phase locked loop (PLL) scheme with a frequency predistortion digital bandpass filter to obtain the rectified voltage phase. Based on analyzing the frequency domain response characteristics of the digital bandpass filter, the continuous bandpass filter is digitized by bilinear transformation with frequency predistortion. On this basis, the rectified voltage is filtered to obtain its fundamental component as the PLL input. Then the grid side voltage phase is obtained at the output side, so the in-phase PFC reference current signal can be generated. Experiments have been carried out on the platform of the 70kHz PFC converter to verify the effectiveness of the strategy.

This paper is concerned with the controller design for grid-connected inverter facing parameter variation and stochastic perturbation. Considering these two factors, a stochastically perturbed linear parameter varying (LPV) system for the inverter is formulated, upon which the stability analysis and controller synthesis have been conducted. Parameter dependent sufficient conditions have been obtained to guarantee the asymptotical and exponential mean square stability, with which the asymptotical and exponential controllers are designed respectively. A two-level three-phase inverter is used to verify the effectiveness of proposed theories. Simulation results show that both the controllers are effective under parameter variation and stochastic perturbation, and the exponential controller performs better than the asymptotical controller.

In this paper, a disturbance observer based control strategy is proposed to regulate the dc-link voltage of three-phase two-level pulse-width-modulation active-front-end rectifiers. In the voltage regulation loop, a linear disturbance observer is designed to improve the system performance. The load connected to the dc-link capacitor is considered as an external disturbance and the observer is used to estimate its value. The estimated disturbance is compensated to the PI controller. Simulations are carried out to verify the effectiveness and advantage of the proposed control strategy. Three different loads have been provided to test the robustness of the control strategy. Simulation results show that the proposed control strategy improves the transient response of the dc-link voltage, meanwhile maintains the steady-state performance in term of the output current total harmonic distortion, and has strong robustness against the external load variation.

In this article, a novel distributed fuzzy load frequency control (LFC) approach is investigated for multiarea power systems under cross-layer attacks. The nonlinear factors existing in turbine dynamics and governor dynamics as well as the uncertain parameters therein are modeled and analyzed under the interval type-2 (IT2) Takagi–Sugeno (T–S) fuzzy framework. The cross-layer attacks threatening the stability of power systems are considered and modeled as an independent Bernoulli process, including denial-of-service (DoS) attacks in the cyber layer and phasor measurement unit (PMU) attacks in the physical layer. By using the Lyapunov theory, an area-dependent Lyapunov function is proposed and the sufficient conditions guaranteeing the system’s asymptotically stability with the area control error (ACE) signals satisfying$\mathcal {H}_{\infty }$performance are deduced. In simulations, we adopt a four-area power system to verify the resiliency enhancement of the presented distributed fuzzy control strategy against random cross-layer DoS attacks. Results show that the designed resilient controller can effectively regulate the load frequency under different cross-layer DoS attack probabilities.

This article proposes a sliding-mode-observer (SMO)-based control strategy to regulate the dc-link voltage for a three-phase two-level active front end (AFE). The SMO is designed for the voltage control loop to estimate the external load which is abruptly connected to the AFE dc-link and consequently causes the dc-link voltage fluctuation. The estimated load value is used to compensate the voltage loop controller, therefore, the voltage loop gains more robustness against the load perturbation and its disturbing effect is greatly reduced. The effectiveness and advantage of the proposed control strategy has been verified through theoretical analysis, simulations, and the real-application experiments conducted on a 5 KVA laboratory AFE. The results show that the proposed control strategy provides obvious improvement of the dc-link voltage control performance comparing with the conventional PI controller and demonstrates stronger robustness against the operating point variations caused by the changes in external load and dc-link capacitance.

With the participation of a significant number of plug-in electric vehicles (PEVs), it is really challenging to achieve economic-effective in load frequency control (LFC) while sustaining satisfiable system performance. To tackle this challenge, a new distributed economic model predictive control (DEMPC) strategy is proposed for the LFC with the large-scale PEV participation. In the light of the vulnerability of LFC to false data injection (FDI) attacks, a model-based χ2intrusion detection unit is integrated with the proposed DEMPC. This model-based intrusion detection unit can not only monitor the FDI attacks, but also generate a model-based state prediction for the DEMPC once the data is identified as compromised. Then, an event-triggering mechanism is presented to reduce the computation and communication burdens of each area controller. Simulation studies of a four-area power system are conducted and the results validate the effectiveness of the proposed intrusion detection unit and event-triggering conditions for the DEMPC.

This paper proposes a dynamic sliding mode control (SMC) approach to the robust voltage regulation of dc-dc boost converters by using interval type-2 fuzzy neural networks (IT2FNNs). First, uncertainties caused by the perturbation of the input inductor and the output capacitor are represented with some bounded approximation errors, by the utilization of a Takagi-Sugeno (T-S) fuzzy modeling approach. Based on the represented model of the boost converter, a new type of sliding surface is designed depending on the duty cycle and reference inputs of the converter. Then, a dynamic SMC law is designed, by considering that the perturbation of the uncertain parameters, including input inductor, output capacitor, load resistor, and input voltage, is bounded. Meanwhile, we adopt an exponential plus power approaching law in the sliding mode controller for fast reachability of the sliding surface and a small chattering in the duty cycle input. Moreover, in terms of the considered uncertainties, a novel IT2FNN-based dynamic SMC law is derived, by applying simplified ellipsoidal-type membership functions in the type-2 fuzzy neural network. To improve the capacity to manage the uncertainties, some online learning algorithms for the updating of the IT2FNN are designed by a gradient descent method (GDM), without the requirement of the boundedness of the uncertainties. The resulting tracking error system is synthesized to be bounded stable based on the designed IT2FNN-based dynamic SMC. Finally, the effectiveness of the proposed adaptive IT2FNN-based dynamic SMC method is verified by some comparative simulation results.

This paper presents voltage regulation and current tracking control strategies for three phase two-level grid-connected power converters. By using power-invariant Park's transformation, an averaged mathematical model of power converters is obtained in dq synchronous reference frame. Then a novel control strategy using adaptive control and H∞technique is proposed to regulate the dc-link output voltage as well as track a desired current reference for three-phase power rectifiers. More specifically, an efficient adaptive controller is established in the external loop for regulating dc-link output voltage in the presence of external disturbances. A set of H∞controllers are designed in the internal loop to force the input currents track their desired values. Finally, simulation results obtained from the proposed control method are presented, analyzed, and compared with that of sliding mode control, and the superiority of the proposed control laws is verified.

In this article, a linear extended state observer (LESO) based second-order sliding mode (SOSM) control strategy with the direct power control is proposed for a three-phase neutral-point-clamped (NPC) power converter connected to a dc microgrid. Comparing with the PI control method, the proposed approach implements the advanced SOSM controller into the voltage regulation loop and instantaneous power tracking loop to enhance the dynamic and steady state performance. Furthermore, saturation function is applied in the SOSM method to weaken the chattering phenomenon. On the other hand, since the dc load is regarded as an external disturbance, an efficient LESO is designed in the voltage regulation loop to reject this disturbance. The design process of the proposed control strategy is shown based on the continuous averaged model of the NPC converter. Finally, comparison experiments among PI, LESO-based PI, and proposed LESO-based SOSM control strategies are implemented, which validate the superiority of the proposed approach.

In this paper, one new distributed load frequency regulation approach is proposed for smart power system operation under two specific practical constraints, including the limited communication resource and speed droop parametric uncertainty. To address these two constraints, the co-design of event-triggering communication scheme and distributed model-based controller is studied. Instead of using zero-order holders, the proposed model-based scheme is able to extend the maximum allowable time interval and thus reduce communication bandwidth usage. In the meantime, the proposed co-design scheme is able to get the model-based control parameters and event-triggering condition metrics simultaneously. This can loosen the conservation in the choice of control gains and event-triggering parameters faced by existing approaches where the control gains are fixed in prior. Comparisons on the multiple-area system confirm that this designed load frequency regulation method significantly reduces the number of required data transmissions without sacrificing the dynamic performance of the frequency and tie-line power. It is also shown that the proposed approach has great robustness to speed droop coefficient uncertainty.

A new approach to the control of three-phase two-level grid-connected power converters is proposed in this paper. The proposed control is an extended state observer (ESO)based second order sliding mode (SOSM), which comprises two control loops: the outer loop is a voltage regulation loop, as well as inner loop is an instantaneous power tracking loop. The outer loop is accomplished by an H∞controller plus an ESO, which is designed to regulate dc-link capacitor voltage of the converter and asymptotically reject external disturbances and parameter perturbations. The SOSM strategy is employed in the inner loop to drive the active and reactive power convergence to their desired values. Control objectives of nearly unity power factor and dc-link capacitor voltage regulation are simultaneously satisfied. Availability of the ESO-based SOSM is compared with the classic proportional-integral control in simulations, and the comparison implies that the proposed strategy not merely achieves an almost perfect tracking performance, but also provides a complete robustness against resistance load variation.

This paper employs second-order sliding mode control (SOSMC) to carry out the current tracking and voltage regulation tasks of a grid-connected three-phase two-level power converter. For dc-link voltage regulation, a disturbance observer is adopted to improve the whole control performance. In this paper, four different types of disturbance observers are proposed for comparison, which are conventional linear observer (LINO), second-order sliding mode observer (SOSMO), linear extended state observer (LESO) and nonlinear extended state observer (NESO). To ensure fair comparison, the parameters of the observers are tuned to make the power converter achieve almost same current total harmonic distortion (THD) and steady error of dc-link voltage. The performances are compared in the term of transient response of the dc-link voltage. The simulation results show: first, the disturbance observers improve the control performance of SOSMC; second, SOSMO outperforms the other three observers.

In this paper, a novel adaptive sliding mode controller is designed against the actuator saturation for a PEM fuel cell air-feed system. To deal with the saturation nonlinearity, a diagonal matrix with unknown elements is introduced for adaptive design in terms of sliding mode control strategy. An integral-type sliding mode surface is designed with constrained conditions. The designed SMC law can guarantee the finite-time convergence against the actuator saturation of the plant. The effectiveness of the proposed saturated SMC scheme is validated in the application to air-feed PEM fuel cell systems.