Modeling and Simulation of Robot Intelligent Control System
A special issue of Processes (ISSN 2227-9717). This special issue belongs to the section "Automation Control Systems".
Deadline for manuscript submissions: 15 January 2025 | Viewed by 1124
Special Issue Editors
Interests: advanced control engineering; intelligent control systems; industrial robots, mobile robots; autonomous navigation; vision guided robotic systems
Interests: robotics; biomedical engineering; mechanical engineering; control systems; spinal cord injury rehabilitation
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
This Special Issue on the "Modeling and Simulation of Robot Intelligent Control System" focuses on the latest research on the theoretical and practical aspects of modeling, simulating, and controlling intelligent robotic systems. This issue covers a range of topics, including advanced control techniques for robotic systems, the simulation of robotic behaviors, the integration of artificial intelligence in robots, and the development of algorithms for autonomous navigation and task execution. Researchers are invited to submit their latest findings on improving the efficiency, accuracy, and reliability of robot control systems through innovative modeling and simulation approaches. This Special Issue seeks contributions that address these challenges and propose solutions for enhancing robotic systems' adaptability and performance in various environments.
Dr. Raouf Fareh
Dr. Mohammad H. Rahman
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. Processes is an international peer-reviewed open access monthly journal published by MDPI.
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Keywords
- robot control systems
- intelligent robots
- simulation
- intelligent control systems
- artificial intelligence
- modeling of robotic systems
- decision-making algorithms
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Planned Papers
The below list represents only planned manuscripts. Some of these manuscripts have not been received by the Editorial Office yet. Papers submitted to MDPI journals are subject to peer-review.
Title: Robust control design and optimization for underactuated mechanical systems considering fuzzy uncertainties
Authors: Xiaofei Chen; Jie Fang; Jiandong Li; Shengchao Zhen
Affiliation: West Anhui University
Abstract: The control challenge of underactuated systems arises from the insufficient degrees of freedom for control and heightened sensitivity to various uncertainties. These factors lead to difficulties such as poor controllability, unstable internal dynamics, and inadequate robustness performance. This paper addresses these issues, focusing on the control research of underactuated dynamic systems with uncertainties. Firstly, the controller is designed by integrating fuzzy mathematics and Lyapunov stability theory. Fuzzy set theory is used to describe the system's uncertainties, leading to the proposal of a robust control algorithm based on fuzzy dynamic systems. Secondly, the optimization of robust control is explored by minimizing performance indicators based on fuzzy information. Finally, a linear motor-driven single inverted pendulum system was used for simulation and experimental validation. The results demonstrated that the optimal robust controller reduced the cart's position error by 34.89% and the pendulum's angle error by 29.20% compared to its initial state. In comparison to traditional PD control, the steady-state position error of the cart decreased from 0.00318m to 0.00057m, and the pendulum's steady-state angle error decreased from 0.01117 rad to 0.00055 rad, further confirming the effectiveness of the proposed algorithm.
