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Applied Sciences
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Adaptive Dynamic Programming and Its Control Applications in Intelligent Systems
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Adaptive Dynamic Programming and Its Control Applications in Intelligent Systems

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Robotics and Automation".

Deadline for manuscript submissions: closed (20 December 2022) | Viewed by 3264

Special Issue Editors

Dr. Bo Zhao

E-Mail Website
Guest Editor
School of Systems Science, Beijing Normal University, Beijing 100875, China
Interests: adaptive dynamic programming; robot control; fault diagnosis and tolerant control; optimal control; artificial-intelligence-based control
Dr. Xuejing Lan

E-Mail Website
Guest Editor
School of Mechanical and Electrical Engineering, Guangzhou University, Guangzhou 510006, China
Interests: adaptive dynamic programming; intelligent control; distributed control; trajectory planning
Dr. Zhiwei Hou

E-Mail Website
Guest Editor
School of Systems Science and Engineering, Sun Yat-Sen University, Guangzhou 510275, China
Interests: trajectory planning; reinforcement learning; multi-agent systems; formation control; adaptive control

Special Issue Information

Dear Colleagues,

Adaptive dynamic programming (ADP) is a new interdisciplinary subject in artificial intelligence and control. ADP-based methods have effectively solved the control problems of large-scale complex nonlinear systems in the fields of transportation, logistics, power and process engineering, which has attracted the attention of many researchers. Therefore, this Special Issue intends to present new ideas and experimental results in the field of ADP and its control applications in intelligent systems.

Potential topics include, but are not limited to, the following:

  • Improved design and analysis of ADP framework and theory;
  • Combination of ADP and other control algorithms, such as fault-tolerant control, sliding mode control, adaptive control, fuzzy control, and robust control;
  • Realization of ADP control techniques based on neural networks, fuzzy logic, fuzzy neural networks, etc.;
  • ADP-based control techniques applied for unmanned systems, multi-agent systems, and complex nonlinear systems;
  • Distributed cooperative optimization based on ADP;
  • Data-based intelligent control based on ADP (reinforcement learning);
  • Multiobjective optimal control based on ADP.

Dr. Bo Zhao
Dr. Xuejing Lan
Dr. Zhiwei Hou
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. Applied Sciences 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 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 dynamic programming
  • optimal control
  • intelligent control
  • multi-agent systems
  • unmanned systems
  • complex nonlinear systems

Published Papers (2 papers)

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Research

23 pages, 4433 KiB  
Article
Event-Triggered Single-Network ADP for Zero-Sum Game of Unknown Nonlinear Systems with Constrained Input
by Binbin Peng, Xiaohong Cui, Yang Cui and Wenjie Chen
Appl. Sci. 2023, 13(4), 2140; https://doi.org/10.3390/app13042140 - 7 Feb 2023
Cited by 2 | Viewed by 1338
Abstract
In this paper, an event-triggered adaptive dynamic programming (ADP) method is proposed to deal with the H∞ problem with unknown dynamic and constrained input. Firstly, the H∞-constrained problem is regarded as the two-player zero-sum game with the nonquadratic value function. [...] Read more.
In this paper, an event-triggered adaptive dynamic programming (ADP) method is proposed to deal with the H∞ problem with unknown dynamic and constrained input. Firstly, the H∞-constrained problem is regarded as the two-player zero-sum game with the nonquadratic value function. Secondly, we develop the event-triggered Hamilton–Jacobi–Isaacs(HJI) equation, and an event-triggered ADP method is proposed to solve the HJI equation, which is equivalent to solving the Nash saddle point of the zero-sum game. An event-based single-critic neural network (NN) is applied to obtain the optimal value function, which reduces the communication resource and computational cost of algorithm implementation. For the event-triggered control, a triggering condition with the level of disturbance attenuation is developed to limit the number of sampling states, and the condition avoids Zeno behavior by proving the existence of events with minimum triggering interval. It is proved theoretically that the closed-loop system is asymptotically stable, and the critic NN weight error is uniformly ultimately boundedness (UUB). The learning performance of the proposed algorithm is verified by two examples. Full article
(This article belongs to the Special Issue Adaptive Dynamic Programming and Its Control Applications in Intelligent Systems)
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16 pages, 2133 KiB  
Article
Integrated Adaptive Steering Stability Control for Ground Vehicle with Actuator Saturations
by Jinhua Zhang and Mingyu Wang
Appl. Sci. 2022, 12(17), 8502; https://doi.org/10.3390/app12178502 - 25 Aug 2022
Cited by 3 | Viewed by 1231
Abstract
During a steering manoeuvre in a ground vehicle, both yaw motion and roll motion can occur simultaneously, and their dynamics can be coupled, as the roll motion is generalized directly from the tires’ lateral force under steering. Hence, it is of significance to [...] Read more.
During a steering manoeuvre in a ground vehicle, both yaw motion and roll motion can occur simultaneously, and their dynamics can be coupled, as the roll motion is generalized directly from the tires’ lateral force under steering. Hence, it is of significance to analyze them as an integrated plant in the vehicle steering stability control problem. Furthermore, the actuator saturation of yaw control cannot be neglected, as vehicles often steer at a high velocity or on low-friction roads. In this paper, an integrated steering dynamics model is established considering the coupling between the roll motion and lateral motion, then a novel nonlinear adaptive controller is proposed to stabilize the steering motion considering the actuator saturation of yaw motion control. Simulation results indicate that the designed integrated controller is effective in improving the performance of both the yaw rate tracking error and ride comfort taking into account vehicle parameter uncertainties and actuator saturation; the steering stability of ground vehicles can consequently be guaranteed. Full article
(This article belongs to the Special Issue Adaptive Dynamic Programming and Its Control Applications in Intelligent Systems)
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