Microgrids have been identified as a viable solution to the integration of renewable distributed generations (DGs) into power systems, while the coordination of DGs is frequently hindered by nonideal communication networks. To eliminate the negative consequences of these communication constraints, this article proposes a distributed predictive-proportional-integral control strategy for dc microgrids subject to communication delays and packet dropouts. The proposed control method can achieve voltage regulation and proportional power sharing simultaneously in a distributed manner. To address the issues of time delay and packet loss, an active prediction method is recommended, in combination with the PID scheme, which makes use of the model information and historical data for predictive compensation as well as retain the benefits of PID controllers effectively. The closed-loop system of the dc microgrid under the proposed control scheme is presented for stability and consensus analysis. Finally, experimental results from a wind turbine-based dc microgrid system are provided to demonstrate the superiority and effectiveness of the proposed method.

This article focuses on the consensus and tracking problem of multiagent systems under communication delays, and proposes an observer-based distributed predictive control scheme to actively compensate for communication delays. First, an auxiliary variable and its corresponding estimator are innovatively designed to provide an observation of a globally consensus value that converges faster than the actual system output. Then, a cost function is formulated for this observer, and the gain of the correction term is optimized in a data-driven way to enhance the accuracy of the estimation. Based on the auxiliary variables, a distributed predictive controller is presented. Unlike existing control schemes, the proposed controller compensates for the delayed data in an active way, and the rolling prediction process is carried out in a distributed manner, facilitated by the designed auxiliary variables. Case studies conducted in both numerical and industrial scenarios demonstrate the effectiveness of the proposed method.

Efficient energy optimization and scheduling in industrial factories depend on accurate, reasonable, and real-time monitoring of equipment power consumption. However, the power prediction of industrial equipment requires a large number of process data, which could be inevitably contaminated by some imperfect data, due to the harsh environments. Monitoring or predicting equipment power consumption is usually not feasible using data-driven black-box models with imperfect data. This paper proposes a prediction-based approach for power consumption monitoring using an interpretable data-driven model. First, a data preprocessing method is used to remove outliers and fill in missing values. Then, a Volterra polynomial basis function (VPBF) model is built to predict equipment power consumption. This model decomposes power values into a series of basis functions consisting of input parameters. Moreover, to compensate for data dropouts during the power consumption monitoring process, a networked predictive monitoring system is also proposed. Finally, this paper presents two case studies based on actual production equipment in an industrial manufacturing factory. The results demonstrate that the proposed approach can achieve satisfactory monitoring accuracy and adaptation ability.Note to Practitioners—This paper is motivated by the problem of power consumption monitoring of industrial equipment in harsh production environments. A conventional solution is to predict the power consumption using data-driven black-box models, with limited feasibility and interpretability. This paper proposes a new power consumption monitoring approach, utilizing an interpretable data-driven model and a networked predictive method. This approach accurately reveals the transparent relationships between the output and input parameters. The power prediction result is consequently interpretable and more reasonable. Meanwhile, this approach actively compensates for data dropouts in the network, which can help operators real-time grasp the power consumption of equipment. Furthermore, this approach can be integrated into energy optimization systems as a basis of optimization and decision-making. Practical applications in an aluminum manufacturing company located in Guangdong Province demonstrate that this approach is feasible and applicable. Future research is to expand this approach further for energy optimization and scheduling.

The use of nonideal communication networks makes communication constraints become a topical issue in the research of dc microgrids. How to design a distributed secondary control scheme for voltage recovery and accurate current sharing in islanded dc microgrids subject to communication constraints is of interest in this article. In order to restore the bus voltage to the rated value, a nonlinear element is first introduced into the primary control layer. Then, the closed-loop system of primary control is modeled as a data-driven time-varying linear system. Based on the established model, considering communication constraints, a distributed secondary predictive control strategy is developed to achieve accurate current sharing. While actively compensating for network delays and packet losses, the proposed method renders mathematical physical models unnecessary for the traditional predictive control, and simultaneously completes the multitask in dc microgrids. Finally, several case studies are conducted on a hardware microgrid experimental platform, which not only verifies the effectiveness of the designed data-driven predictive control strategy but also tests microgrid properties such as the plug-and-play ability.

This article introduces an Internet of Things (IoT)-based solution to a multiagent system (MAS) experimentation with high space utilization and high flexibility. The solution has been applied in the Networked Control System Laboratory (NCSLab), which provides hundreds of educational equipment instances, offering abundant choices for MAS experiments. Based on the networked control theory and integrated circuit technology, a novel compact architecture for online laboratories is proposed first. Combined with multiple features of NCSLab, such as online algorithm design, parameter tuning, and live video monitor, researchers can conduct interactive verification. To achieve good dynamic performance and coordinated performance in a communication-constrained network, a predictive state feedback controller for MAS is proposed. Three web-based leader–follower MAS experiments are carried out to demonstrate the effectiveness of the proposed controller and powerful configurable ability for the MAS in NCSLab. The proposed IoT-based compact laboratory provides a cost-effective and space-efficient solution for other remote laboratories.

With the development of mobile technologies, mobile applications are increasingly designed and developed. In the field of science, technology, engineering, and mathematics education, the idea of using mobile devices for teaching and learning has gradually gained popularity and gained in-depth research. Owing to the advantages of convenience, portability, and excellent interactive abilities, mobile devices are a good choice for accessing remote laboratories. In propose of promoting the massive online experimentation of control education, a mobile application with framework based on react-native is implemented in this article. The overall remote laboratory architecture adopts front-end and back-end separation scheme, which benefits the mobile application focusing on the construction of front-end interface and user experience. Various functional modules and technologies are applied in the mobile application, allowing users to access various experiment test rigs in the remote laboratory with intuitive experimental immersion. Moreover, a complete laboratory management system to manage the massive users from different universities has also been integrated into the mobile application. At the end, a remote networked control experiment has been conducted to prove the practicability of the mobile application.

The technology of multiagent system (MAS) has been developed rapidly to fulfill the information interconnection nowadays. Meanwhile, implementing MAS-based projects is facing great challenges in workload and technologies while most work is still focused on simulation, implying the gap between the simulation and implementation. Aiming at this problem, this article proposes an all-in-one framework for the design, simulation, and implementation of MASs via network, based on a triple-layer data structure that includes overall topology, entity, and physical device. Through the proposed framework, MASs could be designed together with graphic, then corresponding simulation and multitask codes generation could be attained based on the designed model. A simultaneous multiapplication launching for distributed entities could be completed with instant automatic deployment eventually. The entire process provides a unified scheme for construction, verification, and practice of various MAS projects. Using such scheme, users could prototype and deploy MASs quickly with convenient operation, which allows more time and focus to be dedicated to the design and exploration of the control system itself. The practicability of the proposed framework has been verified by typical cases, based on which a more general solution could be improved and applied in the future.

Modular dc–dc converters are popular in dc power systems, such as demagnetization systems due to their advantages of high efficiency, high reliability, and low current stress on components. However, the dynamic consensus of output currents of the multiple converter degaussing systems (MCDSs) has not been well solved yet, especially when communication delay is considered. In this article, a novel coordinated control method based on multistep state predictions with active compensation of delay is proposed to address the poor dynamic consensus performance of currents in MCDSs. The implementation of the scheme consists of the following two main phases: the design of a multistep state predictor for MCDSs and the optimization of the coordinating cost of currents. The multistep state predictor can estimate immeasurable future states of converters over a large horizon length, which presents a novel approach to the current regulator design. The optimal control protocol is derived by minimizing a distributed coordinating performance index function (PIF) for the output currents. This optimization of the PIF minimizes the consensus error between output currents for converters and compensates for communication constraints. Furthermore, the conditions for simultaneous stability and consensus of the closed-loop degaussing system with the distributed multistep state prediction controller are given. Finally, the performance of the proposed scheme is verified by numerous case studies in an experimental testbed.

This paper presents a novel flexible capacitive power transfer (CPT) system, which has stable output capability when the coupler is deformed. To obtain the flexible coupler structure, the copper foil with the features of light, thin, and cost-efficiency is employed to form the flexible capacitive coupling. To achieve stable output capability, the frequency band selection method and the frequency splitting characteristic are deduced, which indicates that if the system works on optimized natural resonant frequency, moderate deformation of the copper foil coupler could have negligible effects on output power and efficiency. Furthermore, the finite-element analysis (FEA) is employed to simulate the variation of electric field distribution in the flexible coupler. Finally, a prototype is constructed in the laboratory. The copper foil coupler with 60$\mu \text{m}$thickness and the dimension of$30\times 16$cm is adopted, which can achieve more than 147 W power transfer for a 100 mm air gap with the efficiency over 86%. When the bending displacement is within 40 mm, the fluctuations of received power and efficiency are less than 3.6% and 3.1%, respectively. The measured results validate the feasibility of the proposed CPT system for being applied in flexible scenarios.

This paper proposes an LCCC and CCL compensated wireless servo motor control circuitry utilizing the merits of fundamental and third harmonic. With this circuitry, the motor side needs no additional power supply and controller, which significantly reduces the difficulty of maintenance. Besides, benefiting from the proposing of CCL compensating topology and utilizing of the self-driven circuitry, the secondary operates in fully resonant state and the motor direction control H-bridge is self-driven by the LC frequency selecting circuitry (FSC). Moreover, compared with the conventional motor control circuitry, because of the use of fundamental and third harmonic, the power equalization becomes significantly easier, and zero voltage switch (ZVS) can be realized at the same time; Besides, motion direction control of the motor is simpler with only a single pole double throw (SPDT) at the transmitter side. In addition, system resource consumption is reduced compared with conventional motor drive topologies. In this paper, an 180W prototype is built for experimental verification, and the result shows a good power equalization capability and a transfer efficiency reaching up to 90% at the distance of 10cm.

As a crucial part of cyber-physical systems, a digital twin can process data, visualize processes, and send commands to the control system, which can be used for the research on thermal power plants that are vital for providing energy for manufacturing and industry, and also daily consumptions. This article introduces the methodologies and techniques toward a web-based digital twin thermal power plant. To implement a web-based digital twin thermal power plant, the architecture, modeling, control algorithm, rule model, and physical-digital twin control are explored. The potential functionalities of the web-based digital twin including real-time monitoring, visualization and interactions, and provided services for physical thermal plants and universities are also presented. A case study has been provided to illustrate the web-based digital twin power plant. The research in this article can provide potential solutions for web-based digital twin research and education.

Online experimentation systems that support remote and/or virtual experiments in an Internet-based environment play an important role in skill-enhanced online learning, especially in the field of engineering. This article explores a human-centered online system with a unified architecture that covers the entire process of control engineering experimentation. The control and security-oriented design are presented and the human-centered design including the HTML5-based web application and the configurable graphical user interface is also introduced. Interactive features such as tuning parameters and 3-D animations and interactions are integrated into the system. Enhanced 3-D effects such as anaglyph 3-D and parallax 3-D are also provided. Thus, users can experience different types of 3-D effects on experiment equipment or in a 3-D virtual world while conducting experiments. Details of an application example with a dual tank system are also explored to verify the performance of the proposed system.

The intermittent and stochastic character of the renewable energy resource may lead to instability or even collapse of the distribution network. Against the backdrop, the distributed energy storage unit (DESU) will be a key component to alleviate power fluctuations and frequency instability in the islanded distribution network. However, previous studies mainly account to qualitative analysis of single or multi-machine networks which contain energy storage unit. Motivated by this, we investigate how the DESU affects the frequency stability of the large-scale distribution network. This paper develops a frequency-based control scheme for DESU to change the charging state with frequency. Employing the Kuramoto oscillator model, the dynamic equation of distributed generation (DG) nodes can be obtained to establish an islanded large-scale distribution network model which contains DESU nodes and DG nodes. Through testing the network frequency fluctuation amplitude and the network synchronization time, we explicitly analyze how the DESU enhance the frequency stability of the distribution network. For demonstration purpose, we build a 201-nodes islanded distribution network model which contains DESU nodes and DG nodes to verify the validity of the analysis.

This paper introduces the schemes of remote wiring interactions in an online control laboratory using an HTML5-based virtual 3-D interface. Although virtual laboratories have drawn increasing research attention in the last decade, wiring practice, which is a crucial part of experimentation, is normally neglected. In this paper, a practice including 3-D modeling, HTML5-based rendering, and control algorithm design is implemented for the interactive virtual wiring based on the Networked Control System Laboratory (NCSLab) framework. The wiring practice is combined with control algorithm design, which is already realized in NCSLab, where users are allowed to customize algorithms using MATLAB/Simulink real-time workshop. Apart from remotely implementing the control algorithm, the 3-D virtual wiring process must be completed correctly before the online experiments can proceed properly. The proposed wiring laboratory is evaluated in practical teaching, with both students' performance and perception considered. The conclusions derived from the report show that the 3-D virtual wiring interactions make virtual experimentation complete for simulating a real case, as well as providing an opportunity for a clearer comprehension of control systems.

This paper is concerned with the design of networked control systems (NCSs) with random network delay in the feedback channel and gives stability criteria of closed-loop networked predictive control systems. The principle of predictive control is adopted to overcome the effects of network time delay. The necessary and sufficient conditions on the stability of the closed-loop NCS are derived, which provides useful analytical stability criteria. The closed-loop networked predictive control system with bounded random network delay is stable if the corresponding switched system is stable. Simulation and real-time results give an illustration of the proposed control strategies