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Abstract Both electric vehicles and Tokamak power supply use multiple parallel converters to realize high current operation in four quadrants. A finite‐time current sharing control algorithm based on disturbance compensation is proposed to improve the converter system's dynamic and steady‐state performance so that the system can achieve the required load current and branch‐current sharing in a finite time. In the proposed algorithm, this paper adopts a finite‐time observer for unknown disturbances in the converter system and load circuit due to disturbances, such as unknown inductance and resistance in the converter system. The results show that the load current control overshoot is minimal, and the dynamic performance of each branch current is higher than the traditional control algorithm. A finite‐time current sharing control algorithm based on disturbance compensation is proposed so that the converter system can achieve the required load current and branch current sharing in a finite time.

In order to further promote the application and development of unmanned aviation in the manned field, and reduce the difficulty that airlines cannot avoid due to unexpected factors such as bad weather, aircraft failure, and so on, the problem of restoring aircraft routes has been studied. To reduce the economic losses caused by flight interruption, this paper divides the repair problem of aircraft operation plans into two sub problems, namely, the generation of flight routes and the reallocation of aircraft. Firstly, the existing fixed-point iteration method proposed by Dang is used to solve the feasible route generation model based on integer programming. To calculate quickly and efficiently, a segmentation method that divides the solution space into mutually independent segments is proposed as the premise of distributed computing. The feasible route is then allocated to the available aircraft to repair the flight plan. The experimental results of two examples of aircraft fault grounding and airport closure show that the method proposed in this paper is effective for aircraft route restoration.

Automatic systems (ASs) can automatically control the work of controlled objects without unattended participation. They have been extensively used in industry, agriculture, automobiles, robots and other fields in recent years. However, the performance of the controller cannot meet the work requirements under complex environmental conditions. Therefore, improving the control performance is one of the difficult problems that automated systems should solve. Sliding-mode variable structure control has the advantages of fast response, insensitivity to uncertainty and interference and easy implementation; thus, it has been extensively used in the field of complex control systems. This article analyses and explains the research status of motors, microgrids, switched systems, aviation guidance, robots, mechanical systems, automobiles and unmanned aerial vehicles (UAVs) and prospects for the application of sliding-mode variable structure control in complex ASs.

In this study, we explore the precise trajectory tracking control problem of autonomous underwater vehicle (AUV) under the disturbance of the underwater environment. First, a model-free adaptive control (MFAC) is designed based on data-driven ideology and a full-form dynamic linearization (FFDL) method is utilized to online estimate time-varying parameter pseudo gradient (PG) to establish an equivalent data model of AUV motion. Second, the iterative extended state observer (IESO) scheme is designed to combine with FFDL-MFAC. Because the proposed novel controller is able to learn from repeated iterations, the proposed novel controller can estimate and compensate the model approximation error produced by external environmental unknown disturbance. Third, three-dimensional motion is decoupled into horizontal and vertical and a multi closed-loop control structure is designed that exhibits faster convergence rate and reduces sensitivity to parameter jumps than single closed-loop system. Finally, two simulation scenarios are designed featuring non external disturbance and Gaussian noise of signal-to-noise ratio of 90 dB. The simulation results reveal the superiority of FFDL. Furthermore, we adpot the technical parameters data of T-SEA I AUV to conduct numerical simulation, aunderwater trajectory as the tracking scenario and set waves to 0.5 m and current to 0.2 m/s to simulate Lv.2 ocean conditions of "International Ocean State Standard". The simulation results demonstrate the effectiveness and robustness of the proposed tracking control algorithm.

As an effective way of improving traffic efficiency, vehicle platoon control has attracted extensive interest recently. Communication between vehicles tends to be affected by communication noises. Aimed at improving communication efficiency, an event-triggered vehicle platoon control under random communication noises is studied in this paper. First, for vehicle platoons with linear third-order dynamics, a time-varying consensus gain $c(t)$ is introduced to reduce the effects of the communication noises. Second, with the introduction of the algebraic graph theory and matrix analysis theory, conditions for internal stability and $l_{p}$ -string stability under random additive communication noises are derived. Third, by utilizing the Lyapunov approach and $It\hat {o}$ stochastic differential equations, the consensus of vehicle platoon under random additive communication noises is proved. Last, to reduce the frequent communication between vehicles, an event-triggered mechanism is introduced, and the design for the triggering parameter is derived. The effectiveness of the proposed method is verified with some numerical simulations.

An experiment using water-assisted millisecond laser trepanning on superalloy GH4220 was carried out, and the effects of pulse energy on the hole entrance morphology, diameter, roundness, cross-section morphology, taper angle, sidewall roughness, and recast layer in air and with water-based assistance were compared and analyzed. The results show that, compared with the air condition, the water-based assistance improved the material removal rate and hole quality, increased the diameter of the hole entrance and exit, increased the hole roundness, decreased the hole taper angle, decreased the hole sidewall roughness, and reduced the recast layer thickness. In addition, under the combined action of water and steam inside the hole, the sidewall surface morphology quality was improved. Compared with the air condition, the spatter around the hole entrance was reduced, but the oxidation phenomenon formed by the thermal effect surrounding the hole entrance with water-based assistance was more obvious. The research provided technical support for the industrial application of millisecond laser drilling.

Heuristic calculation is an essential method to solve optimisation problems. However, its vast computing requirements limit its real-time and online applications, especially in embedded systems with limited computing resources, such as mobile robots. This paper presents a robot path planning algorithm called DA-APF based on deterministic annealing. It is derived from the artificial potential field and can effectively solve the local minimum problem of the model established by the potential field method. The calculation performance of DA-APF is considerably improved by introducing temperature parameters to enhance the potential field function and by using annealing and tempering methods. Moreover, an optimal or near-optimal robot path planning scheme is given. A comprehensive case study is performed using heuristic methods, such as genetic algorithm and simulated annealing. Simulation results show that DA-APF performs well in various static path planning environments.

Cellular mechanical properties are closely related to cell physiological functions and status, and their analysis and measurement help understand cell mechanism. In this study, a microfluidic platform was built to measure the mechanical properties of cells by using dielectrophoretic (DEP) force. The electrodes generally used to stretch cells are made of indium tin oxide, Au, and Pt, which have inherent disadvantages. In this paper, galinstan alloy liquid metal was first introduced as microelectrode to form non-uniform electric filed for red blood cell stretching manipulation. The liquid metal microelectrode is easy to manufacture, low in price, stable at high voltage, and reusable. An effective microfluidic chip integrated with liquid metal electrode was designed and simulated, and a series of experiments to capture and stretch red blood cells was performed. The length of the red blood cells increased from 6 μm to 8 μm under the DEP force from 0 pN to 103 pN. This work also revealed the potential use of liquid metal as microelectrode to manipulate the microparticles and cells in a microfluidic chip.

In this paper, we propose a novel deep convolutional neural network (DCNN) for removing snowflakes from light field (LF) images. We observe that snowflakes in LF images always interrupt slopes in background scenes in epipolar plane images (EPIs), which means that snowflakes may be easily detected in EPIs. Our method takes 3D EPI volumes (i.e., stacked subaperture views along the same row or column of an LF image) as input. In this way, our snowflake detector based on a 3D residual network with a convolutional long short-term memory (ResNet-ConvLSTM) can utilize both contextual information and 3D scene structural information to effectively detect snowflakes of different sizes in LF images. Then, an encoder-decoder-based LF image restoration network is proposed to restore the background image. Finally, extensive experiments for comparison with the state-of-the-art methods demonstrate the effectiveness of our method for challenging scenes.

As industrialization accelerates, the industrial sensor network environment becomes more complex. Hierarchical multi-cluster wireless sensing network topology is generally used due to large-scale industrial environments, harsh environments, and data overload impact. In industrial wireless sensor networks, the overload of some nodes may lead to the failure of the whole network, which is called cascading failure. This phenomenon has incalculable impact on industrial production. However, cascading failure models have mainly been studied for planar structures, and there is no cascading failure model for hierarchical topologies in industrial environments. Therefore, this paper built a cascading failure model for hierarchical industrial wireless sensor networks (IWSNs) for realistic industrial network topologies. By establishing an evaluation mechanism considering the efficiency of the network and the viability of nodes, the network communication efficiency that is not considered in the traditional evaluation mechanism is solved. In addition, aiming at the problem of network topology changes caused by node failure, dynamic load distribution methods (ADD, SLD) are used to improve network invulnerability. Theoretical analysis and experimental results show that the traditional allocation method (SMLD) does not apply in hierarchical topologies; when the general cluster head node capacity is moderate, increasing the capacity of single-hop cluster head nodes can prevent cascading failures more effectively.

As one of the key components of aerospace power grid, the performance of on load tap changer (OLTC) of power transformer is very important. So it is necessary to realize real-time monitoring of its status. At present, there is no feasible monitoring scheme to carry out on-line monitoring and fault diagnosis for detecting faults of OLTC. The current waveform of the switching process will be abnormal due to the contact fault, the transition resistance fault, and most of the mechanical faults. This paper presents a fault diagnosis method for OLTC based on the current detection in the process of switching. Through on-line acquisition of current waveform in the switching process, empirical mode decomposition and Hilbert-Huang transform is used to calculate normalized time-frequency spectrum, and extract fault characteristic quantity, which can realize the comprehensive diagnosis of the running state of the equipment, and identify the early fault characteristics, and promote the process of the OLTC's maintenance, from regular test to condition based maintenance. Experiment results prove that the designed fault diagnosis instrument can effectively monitor the working condition of OLTC during the switching process and make effective fault diagnosis.

This paper is focused on the stabilization of Takagi–Sugeno fuzzy model-based Markovian jump systems with the aid of a delayed state observer. Due to network-induced constraints in the communication channel, a delay partition method combined with an event-triggered mechanism is proposed to design the observer. Then, a novel integral sliding surface is designed, based on which sliding mode dynamics is obtained. Further, according to stochastic stability theory, feasible conditions are provided to ensure the sliding mode dynamics and the error dynamics have an H∞ attenuate level γ. The challenge is to deal with the issue that transition rates may be totally unknown. Moreover, an observer-based sliding mode controller is constructed to ensure the finite-time reachability of the predefined sliding surface. Finally, a numerical example based on a robotic manipulator is given to verify the effectiveness of the proposed method.

This paper proposes a sliding mode control (SMC) strategy to solve the problem of independent control of temperature and humidity in air conditioners; the complexity increases due to the need to make full use of the wind side for cooling. First, dynamics of indoor temperature and humidity are determined based on mathematical models. Second, in order to reduce the chattering effect of SMC and coordinate indoor conditions to satisfy people’s needs, the independent control of temperature and humidity is realized via a novel fuzzy sliding mode control strategy based on reaching laws. Finally, simulation results are provided to verify the effectiveness of the proposed method.

A varied air volume (VAV) air-conditioning system comprises diverse input and/or output disturbances, which are commonly nonlinear, with large lag and uncertainty. Based on the traditional control methods, testing the controlling parameters of a VAV air-conditioning system is challenging. Sliding mode control could improve the robustness of the system due to the adaptive capacity of disturbance rejection. Moreover, the fuzzy algorithm could be employed to determine the stability of a sliding control system by adjusting the parameters in the approach rate, reducing the switching frequency, and weakening chatter. Fuzzy sliding mode control is investigated in this paper to improve the performance of a VAV air-conditioning system. Simulation results verify that the sliding mode control is suitable for a VAV air-conditioning system to achieve good adaptability and robustness considering the influence of multiple external variable disturbances. In addition, the chattering of the system is improved after the introduction of fuzzy control.

Airline disruption is universal phenomenon that block the originally scheduled flights, and the slow recovery scheduling causes a lot of losses to both the airline companies and the passengers. However, it is very difficult to generate a new recovery scheduling in a reasonable time by traditional methods, especially for large dimension airline disruption problem. To deal with this problem rapidly, the airline disruption problem will be reformulated as integer programmings and a distributed network, which is based on the fixed-point iterative method for integer programming, will be developed in this paper. In response to the airport closure, an airplane reschedule is constructed by these feasible flight lines. In the implementation of distributed network, a certain number of independent segments are obtained by dividing the solution space. As a feature of this fixed-point method, the number of partial feasible flight lines, which have to be calculated for finding an optimized airplane reschedule, is much fewer compared with the number needed by CPLEX CP Optimizer. This is the first distributed integer programming method to large airline disruption problems caused by airports closure. In the numerical results, the proposed distributed approach shows promising, especially for solving the large dimension airline disruption problem.

The execution of the airline operation is often deviated from the original schedule due to some unexpected disruptions, such as aircraft breakdowns and severe weather conditions. In this situation, a recovery plan is needed to get the irregular operation back to normal to minimize the losses of the airline. To produce recovery plans and solve the airline disruption problems, a novel modified traveling salesman problem model is proposed to generate sets of the feasible flight routes for each aircraft fleet type. Then, the feasible flight routes are reassigned to the available aircrafts in each fleet to form a recovery plan. Numerical results show that the approach proposed in this paper is efficient and promising.

A non-fragile sliding mode control problem will be investigated in this article. The problem focuses on a kind of uncertain switched singular time-delay systems in which the state is not available. First, according to the designed non-fragile observer, we will construct an integral-type sliding surface, in which the estimated unmeasured state is used. Second, we synthesize a sliding mode controller. The reachability of the specified sliding surface could be proved by this sliding mode controller in a finite time. Moreover, linear matrix inequality conditions will be developed to check the exponential admissibility of the sliding mode dynamics. After that, the gain matrices designed will be given along with it. Finally, some numerical result will be provided, and the result can be used to prove the effectiveness of the method.

Periodical calibration is necessary to ensure the accuracy and reliability of voltage transformers. The traditional calibration method requires the power to be off, and the calibration period for this method is too long, meaning that problems with the transformer cannot be found in time. In this paper, a voltage transformer error online calibration system based on open–closed capacitors is proposed. Two open–closed capacitors and other auxiliary devices are utilized to construct the standard voltage sensor. The outputs of the open–closed capacitors are compared with each other to realize accurate self-checking. The average value of the output is used as the final output, which can improve the system’s accuracy and reliability. An improved algorithm based on a hybrid convolution window is proposed to extract the fundamental and harmonic signals. Test results show that the variation of the ratio error is less than 0.037%, and the variation of the angle error is less than 0.45’.