Special Issue "Latest Theoretical and Technological Advancements in Nonlinear Adaptive Control and Decision-Making"

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Systems & Control Engineering".

Deadline for manuscript submissions: 31 December 2022 | Viewed by 1427

Special Issue Editors

Prof. Dr. Jiangshuai Huang
E-Mail Website1 Website2
Guest Editor
School of Automation, Chongqing University, Chongqing 400044, China
Interests: underactuated mechanical systems; adaptive control; robust control; robotics
Dr. Zongcheng Liu
E-Mail Website
Guest Editor
Aeronautics Engineering College, Air Force Engineering University, Xi’an 710038, China
Interests: adaptive control; nonlinear systems; multi-agent systems
Dr. Rui Gao
E-Mail Website
Guest Editor
School of Automation, Chongqing University, Chongqing 400044, China
Interests: adaptive control; nonlinear systems; cyber-physical systems

Special Issue Information

Dear Colleagues, 

Most practical engineering systems are characterized by complex structures, high nonlinearities and strong dynamic couplings, however, they operating in a severe and dynamic environment, making the control problem of such systems rather complicated. Over the last several decades, adaptive control theory has evolved as a powerful strategy for designing nonlinear feedback controllers for systems with parametric uncertainty. Hence, adaptive control and parameter estimation for complicated uncertain systems are uncertain technical issues that need to be improved. Extensive efforts are being made in academia to improve the technologies for efficient control, better transient performance and the ability to handle the uncertain systems. Recently, addressing the consensus of multi-agent systems (MAS), decision-making methods are always incorporated with adaptive control methods to research these problem, which attracts much researches due to its significant potential applications for a large range of real systems.

The purpose of this Special Issue is to create a platform for scientists, engineers and practitioners to present their latest theoretical and technological advancements in adaptive control, parameter estimation and fault-tolerance techniques for uncertain systems, as well as decision-making methods or cooperative control methods for complicated real systems. The focus will be on the advanced and the non-traditional approaches that incorporate considerable novelties.

Topics of interest include but not limited to:

  • Nonlinear adaptive control for stochastic systems;
  • Adaptive fuzzy/neural control ;
  • Decision-making method;
  • Sliding mode adaptive control;
  • Adaptive fault-tolerant control;
  • Stability and robustness analysis;
  • Adaptive consensus control;
  • Multi-agent systems;
  • Adaptive control under cyber attacks;
  • Parameter estimation

Prof. Dr. Jiangshuai Huang
Dr. Zongcheng Liu
Dr. Rui Gao
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. Electronics is an international peer-reviewed open access semimonthly 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 2000 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.

Published Papers (3 papers)

Order results
Result details
Select all
Export citation of selected articles as:

Research

Article
The Joint Phantom Track Deception and TDOA/FDOA Localization Using UAV Swarm without Prior Knowledge of Radars’ Precise Locations
Electronics 2022, 11(10), 1577; https://doi.org/10.3390/electronics11101577 - 14 May 2022
Viewed by 259
Abstract
This paper develops the model of the joint phantom track deception and the joint techniques of time-difference of arrival (TDOA) and frequency-difference of arrival (FDOA) localization to deceive air defense radar networks under the condition that an unmanned aerial vehicle (UAV) swarm has [...] Read more.
This paper develops the model of the joint phantom track deception and the joint techniques of time-difference of arrival (TDOA) and frequency-difference of arrival (FDOA) localization to deceive air defense radar networks under the condition that an unmanned aerial vehicle (UAV) swarm has no prior knowledge of the radars’ precise locations, and related performance experiment and analysis are presented to demonstrate the effectiveness of the proposed method and to clarify the influence factors of phantom track deception. The main contributions of this paper are as follows. Firstly, the model of phantom track deception against a radar network by UAV swarm without prior knowledge of the radars’ positions are established. Secondly, TDOA/FDOA are adapted to locate networked enemy radars using UAV swarm, where the Fisher information matrix (FIM) is derived to evaluate the estimation accuracy. Thirdly, the uncertainty analysis consisting of radar location error and UAV position error is deduced. With these efforts, the integrated capability of sensing and jamming is realized. Moreover, the same source testing using space resolution cell (SRC) from the perspective of a radar network is executed to provide guidance for phantom track design. Finally, performance experiment and analysis are given to verify the theoretical analysis with simulation results. Full article
Show Figures

Figure 1

Article
Adaptive NN Control of Electro-Hydraulic System with Full State Constraints
Electronics 2022, 11(9), 1483; https://doi.org/10.3390/electronics11091483 - 05 May 2022
Viewed by 273
Abstract
This paper presents an adaptive neural network (NN) control approach for an electro-hydraulic system. The friction and internal leakage are nonlinear uncertainties, and the states in the considered electro-hydraulic system are fully constrained. In the control design, the NNs are utilized to approximate [...] Read more.
This paper presents an adaptive neural network (NN) control approach for an electro-hydraulic system. The friction and internal leakage are nonlinear uncertainties, and the states in the considered electro-hydraulic system are fully constrained. In the control design, the NNs are utilized to approximate the nonlinear uncertainties. Then, by constructing barrier Lyapunov functions and based on the adaptive backstepping control design technique, a novel adaptive NN control scheme is formulated. It has been proven that the developed adaptive NN control scheme can sustain the controlled electro-hydraulic system to be stable and make the system output track the desired reference signal. Furthermore, the system states do not surpass the given bounds. The computer simulation results verify the effectiveness of the proposed controller. Full article
Show Figures

Figure 1

Article
The Application of Improved Harmony Search Algorithm to Multi-UAV Task Assignment
Electronics 2022, 11(8), 1171; https://doi.org/10.3390/electronics11081171 - 07 Apr 2022
Viewed by 355
Abstract
In this work, aiming at the problem of cooperative task assignment for multiple unmanned aerial vehicles (UAVs) in actual combat, battlefield tasks are divided into reconnaissance tasks, strike tasks and evaluation tasks, and a cooperative task-assignment model for multiple UAVs is built. Meanwhile, [...] Read more.
In this work, aiming at the problem of cooperative task assignment for multiple unmanned aerial vehicles (UAVs) in actual combat, battlefield tasks are divided into reconnaissance tasks, strike tasks and evaluation tasks, and a cooperative task-assignment model for multiple UAVs is built. Meanwhile, heterogeneous UAV-load constraints and mission-cost constraints are introduced, the UAVs and their constraints are analyzed and the mathematical model is established. The exploration performance and convergence performance of the harmony search algorithm are analyzed theoretically, and the more general formulas of exploration performance and convergence performance are proved. Based on theoretical analysis, an algorithm called opposition-based learning parameter-adjusting harmony search is proposed. Using the algorithm to test the functions of different properties, the value range of key control parameters of the algorithm is given. Finally, four algorithms are used to simulate and solve the assignment problem, which verifies the effectiveness of the task-assignment model and the excellence of the designed algorithm. Simulation results show that while ensuring proper assignment, the proposed algorithm is very effective for the multi-objective optimization of heterogeneous UAV-cooperation mission planning with multiple constraints. Full article
Show Figures

Figure 1

Back to TopTop