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Actuators
Special Issues
Adaptive Fault-Tolerant Control of Uncertain Systems with Actuator Nonlinearities
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Adaptive Fault-Tolerant Control of Uncertain Systems with Actuator Nonlinearities

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

Deadline for manuscript submissions: closed (29 February 2024) | Viewed by 2927

Special Issue Editors

Dr. Guanyu Lai

E-Mail Website
Guest Editor
School of Automation, Guangdong University of Technology, Guangzhou 510006, China
Interests: intelligent control; adaptive visual control; high-performance actuators; robotics
Dr. Kairui Chen

E-Mail Website
Guest Editor
School of Mechanical and Electrical Engineering, Guangzhou University, Guangzhou 510006, China
Interests: multi-agent system; adaptive control; stochastic systems; robotics
Dr. Hanzhen Xiao

E-Mail Website
Guest Editor
School of Automation, Guangdong University of Technology, Guangzhou 510006, China
Interests: mobile robot; formation control; model predictive control; consensus control
Dr. Weijun Yang

E-Mail Website
Guest Editor
School of Mechanical and Electrical Engineering, Guangzhou City Polytechnic, Guangzhou 510405, China
Interests: intelligent control; network system control; optimal control

Special Issue Information

Dear Colleagues,

Adaptive fault-tolerant control (AFTC) of uncertain linear or nonlinear systems has received a great deal of attention in recent years due to its theoretical and practical importance, as well as widespread applications in many fields such as aerospace, high-speed trains, surgical robots, power systems, etc. However, when actuators are subject to some nonlinear constraints, e.g., saturation, dead zone, backlash, and hysteresis, a systematic design and analysis framework for the AFTC of uncertain systems has not been established, in particular for nonlinear systems without canonical form as well as multivariable systems; as a result, new challenging problems will arise, all of which concern the fusion of the adaptive actuator failure compensation strategy and inversion methodology, the development of robust adaptive techniques to accommodate actuator failures and nonlinearities simultaneously, and so on. This Special Issue is expected to present a complete AFTC framework for uncertain systems with actuator nonlinearities.

This Special Issue will include, but is not limited to, the following topics relevant to AFTC:

  • AFTC for linear or nonlinear systems;
  • Intelligent AFTC;
  • Optimal AFTC;
  • Robust AFTC;
  • Adaptive inverse control;
  • Reliability analysis;
  • Networked control systems;
  • Multi-agent systems;
  • Power systems;
  • Industrial robots or mobile robots.

Dr. Guanyu Lai
Dr. Kairui Chen
Dr. Hanzhen Xiao
Dr. Weijun Yang
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

  • adaptive fault-tolerant control
  • robust adaptive control
  • actuator failure compensation
  • nonsmooth actuator nonlinearities
  • stability analysis

Published Papers (2 papers)

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Research

27 pages, 3556 KiB  
Article
Adaptive Self-Triggered Control for Multi-Agent Systems with Actuator Failures and Time-Varying State Constraints
by Jianhui Wang, Zikai Hu, Jiarui Liu, Yuanqing Zhang, Yixiang Gu, Weicong Huang, Ruizhi Tang and Fang Wang
Actuators 2023, 12(9), 364; https://doi.org/10.3390/act12090364 - 19 Sep 2023
Cited by 1 | Viewed by 981
Abstract
This work focuses on the consensus problem for multi-agent systems (MASs) with actuator failures and time-varying state constraints, and presents a fixed-time self-triggered consensus control protocol. The use of time-varying asymmetrical barrier Lyapunov functions (BLF) avoids the violation of time-varying state constraints in [...] Read more.
This work focuses on the consensus problem for multi-agent systems (MASs) with actuator failures and time-varying state constraints, and presents a fixed-time self-triggered consensus control protocol. The use of time-varying asymmetrical barrier Lyapunov functions (BLF) avoids the violation of time-varying state constraints in MASs, ensuring stability and safety. Meanwhile, the system’s performance is further enhanced by leveraging the proposed adaptive neural networks (NNs) control method to mitigate the effects of actuator failures and nonlinear disturbances. Moreover, a self-triggered mechanism based on a fixed-time strategy is proposed to reach rapid convergence and conserve bandwidth resources in MASs. The mechanism achieves consensus within a predefined fixed time, irrespective of the system’s initial states, while conserving communication resources. Finally, the proposed method’s effectiveness is confirmed through two simulation examples, encompassing diverse actuator failure scenarios. Full article
(This article belongs to the Special Issue Adaptive Fault-Tolerant Control of Uncertain Systems with Actuator Nonlinearities)
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17 pages, 3277 KiB  
Article
Tracking Control of Uncertain Neural Network Systems with Preisach Hysteresis Inputs: A New Iteration-Based Adaptive Inversion Approach
by Guanyu Lai, Gongqing Deng, Weijun Yang, Xiaodong Wang and Xiaohang Su
Actuators 2023, 12(9), 341; https://doi.org/10.3390/act12090341 - 25 Aug 2023
Viewed by 974
Abstract
To describe the hysteresis nonlinearities in smart actuators, numerous models have been presented in the literature, among which the Preisach operator is the most effective due to its capability to capture multi-loop or sophisticated hysteresis curves. When such an operator is coupled with [...] Read more.
To describe the hysteresis nonlinearities in smart actuators, numerous models have been presented in the literature, among which the Preisach operator is the most effective due to its capability to capture multi-loop or sophisticated hysteresis curves. When such an operator is coupled with uncertain nonlinear dynamics, especially in noncanonical form, it is a challenging problem to develop techniques to cancel out the hysteresis effects and, at the same time, achieve asymptotic tracking performance. To address this problem, in this paper, we investigate the problem of iterative inverse-based adaptive control for uncertain noncanonical nonlinear systems with unknown input Preisach hysteresis, and a new adaptive version of the closest-match algorithm is proposed to compensate for the Preisach hysteresis. With our scheme, the stability and convergence of the closed-loop system can be established. The effectiveness of the proposed control scheme is illustrated through simulation and experimental results. Full article
(This article belongs to the Special Issue Adaptive Fault-Tolerant Control of Uncertain Systems with Actuator Nonlinearities)
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