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Actuators
Special Issues
Intelligent Sensing, Control and Actuation in Networked Systems
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Intelligent Sensing, Control and Actuation in Networked Systems

A special issue of Actuators (ISSN 2076-0825). This special issue belongs to the section "Control Systems".

Deadline for manuscript submissions: 28 February 2025 | Viewed by 2522

Special Issue Editors

Dr. Guangtao Ran

E-Mail Website
Guest Editor
Department of Control Science and Engineering, Harbin Institute of Technology, Harbin, China
Interests: networked systems; fault diagnosis; event-based control; nonlinear control
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Yanning Guo

E-Mail Website
Guest Editor
Department of Control Science and Engineering, Harbin Institute of Technology, Harbin, China
Interests: space exploration; satellite attitude control; nonlinear control
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Chuan-jiang Li

E-Mail Website
Guest Editor
Department of Control Science and Engineering, Harbin Institute of Technology, Harbin, China
Interests: optimal control; nonlinear control and its applications; formation flying; multi-agent system

Special Issue Information

Dear Colleagues,

Networked systems integrate distributed sensing, control, and actuation components operating within complex, interconnected networks, which are ubiquitous in various engineering domains, from aerospace and robotics to power systems and chemical processes. These systems pose unique challenges due to factors such as communication constraints, system nonlinearities, and the need for decentralized decision-making. Addressing the challenges is crucial for improving the performance, reliability, and safety of modern technological systems. This Special Issue aims to showcase the latest advancements in sensing, control, and actuation technologies that are transforming the way we approach networked system challenges. By integrating cutting-edge techniques from fields such as machine learning, adaptive control, event-triggered control, and multi-agent coordination, researchers are developing innovative solutions to enhance the operational capabilities of networked systems. The scope of this Special Issue includes, but is not limited to, the following topics:

  1. Distributed actuator layout optimization;
  2. Advanced sensing and learning-based control algorithm;
  3. Machine learning-based techniques, such as neural networks and data-driven models, for anomaly detection and fault diagnosis;
  4. Actuator fault-tolerant control;
  5. Planning and control strategies for networked systems involving actuators;
  6. Actuator applications in networked systems.

Dr. Guangtao Ran
Prof. Dr. Yanning Guo
Prof. Dr. Chuan-jiang Li
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Actuators is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • networked systems
  • intelligent sensing and control
  • actuator applications
  • data-driven control
  • fault-tolerant control

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Further information on MDPI's Special Issue polices can be found here.

Published Papers (3 papers)

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Research

15 pages, 629 KiB  
Article
Fixed-Time Congestion Control for a Class of Uncertain Multi-Bottleneck TCP/AWM Networks
by Yanxin Li, Jiqing Chen, Shangkun Liu, Weimin Zheng and Runan Guo
Actuators 2024, 13(10), 388; https://doi.org/10.3390/act13100388 - 1 Oct 2024
Viewed by 494
Abstract
As network technology continues to advance, network congestion has become an inevitable aspect of network communication. Considering the external interference, unmodeled uncertainty and the interaction between nodes, a multi-bottleneck TCP/AWM network model is established in this paper. A new fixed-time congestion controller was [...] Read more.
As network technology continues to advance, network congestion has become an inevitable aspect of network communication. Considering the external interference, unmodeled uncertainty and the interaction between nodes, a multi-bottleneck TCP/AWM network model is established in this paper. A new fixed-time congestion controller was designed by combining a neural network and the backstepping technique. The neural network approximation property is used to eliminate the interference of unmodeled uncertainty and UDP flow in the system. The controller designed in this paper can ensure the stability of the TCP/AWM closed-loop system in a fixed time. Finally, the simulation results demonstrate the effectiveness of the proposed TCP/AWM controller. Full article
(This article belongs to the Special Issue Intelligent Sensing, Control and Actuation in Networked Systems)
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17 pages, 838 KiB  
Article
Distributed Event-Triggered Optimal Algorithm Designs for Economic Dispatching of DC Microgrid with Conventional and Renewable Generators: Actuator-Based Control and Optimization
by Wenming Shi, Xianglian Lv and Yang He
Actuators 2024, 13(8), 290; https://doi.org/10.3390/act13080290 - 1 Aug 2024
Cited by 1 | Viewed by 843
Abstract
Actuators play a crucial role in modern distributed electric grids and renewable energy network architectures, implementing control actions based on sensor data to ensure optimal system performance and stability. This paper addresses the economic dispatch (ED) problem of distributed DC microgrids with renewable [...] Read more.
Actuators play a crucial role in modern distributed electric grids and renewable energy network architectures, implementing control actions based on sensor data to ensure optimal system performance and stability. This paper addresses the economic dispatch (ED) problem of distributed DC microgrids with renewable energy. In these systems, numerous sensors and actuators are integral for monitoring and controlling various parameters to ensure optimal performance. A new event-triggered distributed optimization algorithm in the discrete time domain is employed to ensure the minimum production cost of the power grid. This algorithm leverages data from sensors to make real-time adjustments through actuators, ensuring the maximum energy utilization rate of renewable generators (RGs) and the minimum cost of conventional generators (CGs). It realizes the optimal synergy between conventional energy and renewable energy. Compared to the continuous sampling optimization algorithm, the event-triggered control (ETC) optimization algorithm reduces the frequency of communication and current sampling, thus improving communication efficiency and extending the system’s lifetime. The use of actuators in this context is crucial for implementing these adjustments effectively. Additionally, the convergence and stability of the DC microgrid are proven by the designed Lyapunov function. Finally, the effectiveness of the proposed optimization algorithm is validated through simulations of the DC microgrid. Full article
(This article belongs to the Special Issue Intelligent Sensing, Control and Actuation in Networked Systems)
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21 pages, 2350 KiB  
Article
L1 Adaptive Fault-Tolerant Control for Nonlinear Systems Subject to Input Constraint and Multiple Faults
by Yan Zhou, Huiying Liu and Huijuan Guo
Actuators 2024, 13(7), 258; https://doi.org/10.3390/act13070258 - 9 Jul 2024
Cited by 2 | Viewed by 596
Abstract
This paper investigates an L1 adaptive fault-tolerant control scheme for nonlinear systems with input constraint, external disturbances, and multiple faults, which include actuator faults and sensor faults. Faults and input constraint are important factors that affect the stability and performance of a control [...] Read more.
This paper investigates an L1 adaptive fault-tolerant control scheme for nonlinear systems with input constraint, external disturbances, and multiple faults, which include actuator faults and sensor faults. Faults and input constraint are important factors that affect the stability and performance of a control system. Actuators and sensors are the most vulnerable components, with the former receiving more attention in comparison. In this paper, sensor faults are first transformed into pseudo-actuator faults through the augmented matrix approach, which facilitates their handling together with actuator faults. Saturation constraints on the control signal are not conducive to the design of the controller. The conversion of an input-saturated function to a time-varying linear system is completed based on function approximation and Lagrange’s mean value theorem. Moreover, a nonlinear system with unknown input gain and uncertainties is constructed using these methods. Next, an L1 adaptive fault-tolerant controller is designed to cope with uncertainties, including system uncertainties, external disturbances, faults, and approximation errors. In the L1 adaptive controller, the online estimation of the time-varying parameters allows for updating of the system state, while the combination of the two is transmitted to the control law such that it can compensate for the effects of the uncertainties. The stability and performance boundaries are further derived using the Lyapunov theory and the L1 reference system. Finally, simulations are carried out to demonstrate the effectiveness of the proposed controller. Full article
(This article belongs to the Special Issue Intelligent Sensing, Control and Actuation in Networked Systems)
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