This paper presents an improved generalized super-twisting control (IGSTC) scheme for neutral-point-clamped (NPC) converters subject to the line-inductance parameter uncertainties. By optimizing the algorithm structure, the proposed method accelerates transient response. An online fixed-time inductance estimation algorithm is integrated into the current-tracking loop, significantly enhancing the system’s robustness against inductance variations. Through Lyapunov-based analysis, the practical finite-time stability of the IGSTC and the practical fixed-time convergence of the identification algorithm are rigorously established. Finally, comprehensive simulations under both nominal and varying inductance scenarios validate that the superior performance of the proposed strategy.

In this paper, a generalized proportional integral observer (GPIO)-based finite-time sliding mode control scheme is proposed to enhance the convergence rate and disturbance rejection capacity of the grid-connected three-level neutral-point-clamped (NPC) converter. Firstly, a generalized super-twisting algorithm (GSTA) is designed in the voltage regulation loop and the instantaneous power loop of the NPC converter. Compared with the conventional super-twisting algorithm (STA), this method provides a faster convergence speed while the system trajectories are far from the origin, which is applied to the NPC converter to improve its dynamic performance and robustness. Additionally, by introducing a generalized proportional integral observer (GPIO) combined with the GSTA in the voltage regulation loop, the unknown time-varying disturbances can be rejected effectively. The stability of the proposed control scheme is proved. Finally, a set of comparative experiments between the proposed controller and the classic STA-based method have been carried out based on a three-level NPC converter prototype, and the results confirmed the efficacy of the proposed control strategy.

This article proposes an event-triggered generalized super-twisting sliding mode disturbance rejection control strategy for permanent magnet synchronous motors (PMSMs), aiming to ensure precise position tracking while efficiently conserving communication resources. A unified event-triggering mechanism facilitates the simultaneous transmission of measurement and actuator signals, effectively implementing feedback-control bidirectional triggering. Furthermore, the entire control strategy is updated based on triggered state information. It incorporates a generalized super-twisting controller characterized by a simple structure and smooth dynamic performance, in addition to a neural network observer and a high-gain observer designed to estimate lumped disturbances and enhance system robustness. The practical stability of the closed-loop system, the boundedness of the signals, and the Zeno-free execution of triggering sequences are rigorously verified. Finally, experimental results on a PMSM validate the superiority of the proposed control approach in terms of transient-state position tracking, steady-state smoothness, communication efficiency, and robustness.

This article explores a novel variable-gain super-twisting observer (VGSTO)-based fixed-time sliding mode control (FTSMC) method for the dc-link voltage control of three-level neutral-point-clamped (NPC) active front-end (AFE) converters. Among the literature review, the super-twisting observer is an attractive solution for disturbance estimation. However, its convergence velocity is limited when the trajectories are far away from the origin. To overcome this drawback, a novel VGSTO is proposed in this work, whose innovation lies in adopting dynamically adapted exponent coefficients in the conventional super-twisting observer; thus, it turns into a linear observer outside a ball around the origin, which increases the convergence rate of conventional super-twisting observer, and the disturbance rejection ability is enhanced significantly. In addition, an FTSMC is designed for the NPC converter and its settling time is independent of the initial states, which breaks through the limitation of the traditional finite-time sliding mode controllers and assures the dynamic performance of the NPC converter. The proposed control scheme is assessed and compared with other representative observer-based sliding mode control methods based on a three-level NPC AFE converter test bench, and the experimental results verify its feasibility and effectiveness.

Insulator cleaning robot operates in challenging and unpredictable conditions, whereas the conventional control algorithms are not easy to adapt to the complex disturbances. To deal with this issue, in this paper, a two-degree-of-freedom Lagrangian dynamics model is derived and a radial basis function (RBF) neural network based non-singular fast terminal sliding mode (NFTSM) controller is designed for the insulator cleaning robot. The NFTSM is designed for tracking the robot's reference trajectory, and RBF neural network is introduced to compensate external disturbances and internal unmodelled dynamic, which further improves both the dynamic and steady state performance of the robot. Finally, simulation results demonstrate the advantages of the proposed controller in insulator cleaning robot trajectory tracking control.

This paper introduces a fixed-time sliding mode control (FTSMC) scheme that utilizes a fixed-time disturbance observer (FTDOB) for three-level neutral-point-clamped (3L-NPC) converters. Therein, a FTSMC with adaptive exponential coefficient is developed to regulate the dc-link voltage. Compared with existing methods, the proposed approach features a settling time upper bound that is independent of the initial error, which ensures the dynamic performance of the 3L-NPC converters. Furthermore, a FTDOB is employed to estimate external disturbances and act as feedforward compensation of the 3L-NPC converters to enhance its disturbances rejection ability. Finally, a series of simulation results illustrate the advantages of the proposed scheme by compared with several representative methods used in 3L-NPC converters.

In this article, a novel adaptive fixed-time fuzzy control algorithm is designed for uncertain Euler–Lagrange (EL) systems with actuator control input saturation. In contrast to existing algorithms, this article explores a faster fixed-time backstepping control algorithm. It enables the system to achieve fixed-time convergence with a faster convergence rate and obtain a smaller upper bound of the convergence time. To address the problem of actuator control input saturation, a novel fixed-time auxiliary system is constructed, involving coordinate transformation of the system's error variables to mitigate the effects of saturation. In response to the unknown dynamics (including model uncertainty, external disturbance, etc.) of the EL system, this article designs an adaptive interval type-2 fuzzy neural network for estimation and compensation. Stability analysis confirms that the tracking error can achieve faster fixed-time convergence. Simulation and experimental results demonstrate that the proposed control algorithm can enhance dynamic and steady-state tracking control performance.

In this article, on the basis of an existing dual layer nested (DLN) adaptive sliding-mode control (ASMC) strategy, an observer-based sliding-mode control strategy with an improved DLN adaptive tuning mechanism (IDLN-ASMC) is proposed for a three-level neutral-point-clamped converter. The proposed controller not only ensures good system performance but also mitigates two problems of the existing DLN-ASMC strategy. Meanwhile, three objectives are achieved. First, an adaptive supertwisting algorithm is utilized in the power tracking loop to converge power tracking errors to bounded regions in finite time. Next, a disturbance observer-based IDLN-ASMC strategy is proposed in the dc-link voltage regulation loop to regulate the dc-link voltage to its reference value. Finally, a simple proportional-integral controller is used in the dc-link voltage-balancing loop to reduce the voltage difference between the two dc-link capacitors. The results of simulation and experiment demonstrate the effectiveness and superiority of the proposed strategy.

In this paper, a fixed-time active disturbance rejection-based sliding mode control scheme is proposed for the three-phase three-level neutral-point-clamped (NPC) active front-end (AFE) converter to regulate the dc-link voltage. In order to further improve the disturbance rejection ability of the active disturbance rejection control (ADRC) when applied in NPC converter, a fixed-time disturbance observer is used to estimate the disturbances instead of the traditional extended state observer in ADRC. In addition, a sliding mode controller with constant plus proportional rate reaching law (CPPRL) is designed to regulate the dc-link voltage, and the dynamic performance and control accuracy of NPC converter is improved without increasing the chattering. Finally, the performance of the proposed control scheme is evaluated by a class of comparative simulations, and the results confirm the effectiveness and feasibility of the proposed approach.

In this paper, the prescribed-instant stability control is proposed and utilized in the leader-follower multiagent system with a directed communication topology. The proposed prescribed-instant stability ensures the settling time is exactly equal to the prescribed time instant. Therefore, the specific time instant at which the system containment is established can be manipulated as per our will. This result is of great significance in some complex multiagent system cooperation tasks. The proof of the main result is demonstrated by the Lyapunov method, Specifically, the settling time is clamped from two sides to the selected time instant. Apart from the theoretical proof, a numerical simulation is also presented to validate the proposed method.

In order to obtain a simple and efficient control strategy for three-phase two-level grid-connected power converters with improved system performance including reduced computation and communication burdens, an event-triggered continuous control set-model predictive control (CCS-MPC) is proposed in this paper. In the DC-link voltage regulation loop, a simple but efficient controller is designed to track the DC-link voltage to its reference value. In the power tracking loop, a simple event-triggered CCS-MPC is utilized to ensure that the active power and reactive power also track their reference values. The control signals to the converter are updated and transmitted only when the triggering condition is satisfied. Compared with periodic sampling control strategies, which require the calculation and transmission of control signals in each sampling period, the proposed controller reduces the utilization of limited computation and communication resources while maintaining good tracking performance. By comparing with the periodic sampling proportional-integral strategy, the effectiveness and superiority of the proposed strategy are shown through simulation results.

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.

Cascaded H-bridge (CHB) and modular multilevel converter (MMC) are effective solutions for medium and high voltage motor drive applications. However, the choice between the two converters is not particularly clear. This paper presents a loss evaluation of cascaded H-bridge and modular multilevel converter as a reference for loss calculation. A brief description of CHB and MMC are provided and the explicit expression of conduction loss and switching loss for MMC and CHB is derived respectively to show the relationship between the loss and the main variables of MMC and CHB directly based on carrier phase-shifting PWM (CPS-PWM). In the derivation of switching loss, a novel switching loss calculation method based on PWM is proposed to simplify the theoretical calculation process. Finally, the total loss comparison of the two converters based on different conditions are shown for a better selection in motor drive application.

In spacecraft, Power Conditioning Unit system is responsible to stable bus voltage whose power comes from the solar panel energy. For testing purposes, high dynamic solar array simulator is required to simulate the solar panel, besides that, high slew rate current load is also applied for load variation measurement. High Slew Rate Current Sink is the key part in building both high dynamic solar array simulator and high slew rate current load. Linear power topology is used for fast dynamic performance and good accuracy. A two-Op-Amp Current Sink is proposed to combine stability and current sense accuracy. Parallel structure is necessary to endure high power dissipation in equipment. The consequent problem of common mode interference is reduced after the full-differential structure is used. An 83A/μs current sink protocol is realized with 10 paralleled modules.

To capture the multi-objective and uncertain nature of flexible job shop scheduling, a mathematical model for the multi-objective flexible job shop scheduling problem with release time uncertainties (mOFJSSP-RTU) is constructed, where three objectives of make-span, tardiness, and robustness are taken into account simultaneously under various constraints. To solve MOFJSSP-RTU appropriately, an improved multi-objective evolutionary algorithm based on decomposition (IMOEA/D) is proposed for robust scheduling. The novelty of our algorithm is that it employs a new subproblem update strategy which utilizes the global information, allows the elitists recorded in an archive to take part in the child generation, and incorporates a repair-based crossover operator and an adaptive differential evolution (DE)-based mutation operator for variation, which helps better balance the exploration and exploitation of the algorithm. Experimental results on 4 problem instances indicate that our IMOEA/D-based robust scheduling method has a much better convergence performance than the state-of-the-art multi-objective optimization evolutionary algorithms (MOEAs), and it is also good at maintaining a uniform distribution of solutions. Different trade-offs among the three objectives are also analyzed.