Special Issue "Recent Advances in Complex Dynamical Systems via Intelligent Control Approach"

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

Deadline for manuscript submissions: closed (30 June 2022) | Viewed by 1397

Special Issue Editors

Prof. Dr. Nallappan Gunasekaran
E-Mail Website
Guest Editor
Computational Intelligence Laboratory, Department of Advanced Science and Technology, Toyota Technological Institute, Nagoya 468-8511, Japan
Interests: stability analysis for nonlinear systems; neural networks and their applications; complex dynamical systems and their applications
Dr. R. Vadivel
E-Mail Website
Guest Editor
Faculty of Science and Technology, Phuket Rajabhat University, Phuket 83000, Thailand
Interests: time-varying delay; stability analysis; mathematical modeling; neural networks
Special Issues, Collections and Topics in MDPI journals
Dr. Yongbao Wu
E-Mail Website
Guest Editor
School of Automation, Southeast University, Nanjing 210096, China
Interests: event-triggered control; stochastic complex networks; neural networks; multi-agent systems
Dr. Bing Yan
E-Mail Website
Guest Editor
School of Electrical and Electronic Engineering, The University of Adelaide, South Australia 5005, Australia
Interests: multi-agent systems; flight control systems; neural networks; robust control

Special Issue Information

Dear Colleagues,

Many realistic systems can be modeled using dynamical equations. Increasing system performance requirements need to deal with the increasingly complicated dynamical systems used to simulate reality in control system analysis and design. Nonlinearity, uncertainty, time delay, system singularity, stochastic effects, the presence of linkages, and other factors contribute to the complexity. Technological and control theory advancements have made it possible to analyze complicated dynamical systems. Complex systems research is becoming increasingly essential, providing an additional push for the development of novel approaches and abilities for complex control systems. It has been applied widely in many complex fields, for example in missile guidance systems, active vehicle suspension systems, automobile control systems, etc. Due to their theoretical and practical significance, complex dynamical systems have long been and will continue to be one of the most active research areas. Although there have been many interesting publications on complex dynamical systems in recent years, there remain many challenging open issues. This provides the motivation for this Special Issue.

One of the main goals of this Special Issue is to bring together the latest innovative knowledge, analysis, and modeling techniques of control problems in dynamical networks. We accept both original research and review articles, and papers must contain unique theory or design material. The Special Issue focuses on recent achievements and applications in the field of complex system control and analysis, with particular emphasis on how to solve various control and observer design problems for nonlinear and interconnected systems. The systems under consideration typically have at least two functions: nonlinearity, faults, time delays, disturbance/uncertainty, interconnections between subsystems, stochastic processes, system singularities, and comparisons between simulations and experiments. The Special Issue focuses on the results of theoretical research and practical applications, with a focus on new methodologies for analysis, design, synthesis, and/or applications. Interconnected/networked systems, variable structure control, singular system control, time delay systems, fuzzy control and impulsive control, robust observer design and parameter identification, fault detection and fault-tolerant control, analysis and control of stochastic systems, and applications of advanced control systems are among the topics covered in this Special Issue.

Prof. Dr. Nallappan Gunasekaran
Prof. Dr. R. Vadivel
Dr. Yongbao Wu
Dr. Bing Yan
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.

Keywords

  • T-S fuzzy systems
  • multi-agent systems
  • neural networks
  • stochastic neural networks
  • chaos theory, hybrid systems
  • robust control

Published Papers (2 papers)

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

Research

Article
New Development in Quadratic L2 Performance of Switched Uncertain Stochastic Systems
Electronics 2022, 11(13), 1963; https://doi.org/10.3390/electronics11131963 - 23 Jun 2022
Viewed by 203
Abstract
Global quadratic stability and L2 performance in probability (quadratic stability and L2 gain γ in probability: abbreviated as GQL2(γ)-P) is studied for switched systems consisting of linear stochastic subsystems with norm-bounded uncertainties. Under the assumption [...] Read more.
Global quadratic stability and L2 performance in probability (quadratic stability and L2 gain γ in probability: abbreviated as GQL2(γ)-P) is studied for switched systems consisting of linear stochastic subsystems with norm-bounded uncertainties. Under the assumption that there is no single subsystem achieving GQL2(γ)-P, it is shown that if there exists a convex combination of subsystems achieving GQL2(γ)-P, then a state-dependent switching law, based on the convex combination of subsystems, is proposed under which the switched system achieves GQL2(γ)-P. Then, the discussion is extended to the case involving state feedback controller gain. A numerical example and the application to DC–DC boost converters are provided to demonstrate the proposed design condition and the algorithm. Full article
Show Figures

Figure 1

Article
Numerical Solutions of a Differential System Considering a Pure Hybrid Fuzzy Neutral Delay Theory
Electronics 2022, 11(9), 1478; https://doi.org/10.3390/electronics11091478 - 05 May 2022
Viewed by 355
Abstract
In this paper, we propose and derive a new system called pure hybrid fuzzy neutral delay differential equations. We apply the classical fourth-order Runge–Kutta method (RK-4) to solve the proposed system of ordinary differential equations. First, we define the RK-4 method for hybrid [...] Read more.
In this paper, we propose and derive a new system called pure hybrid fuzzy neutral delay differential equations. We apply the classical fourth-order Runge–Kutta method (RK-4) to solve the proposed system of ordinary differential equations. First, we define the RK-4 method for hybrid fuzzy neutral delay differential equations and then establish the efficiency of this method by utilizing it to solve a particular type of fuzzy neutral delay differential equation. We provide a numerical example to verify the theoretical results. In addition, we compare the RK-4 and Euler solutions with the exact solutions. An error analysis is conducted to assess how much deviation from exactness is found in the two numerical methods. We arrive at the same conclusion for our hybrid fuzzy neutral delay differential system since the RK-4 method outperforms the classical Euler method. Full article
Show Figures

Figure 1

Back to TopTop