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Advanced Control Systems and Control Engineering
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Advanced Control Systems and Control Engineering

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Mechanical Engineering".

Deadline for manuscript submissions: 20 August 2025 | Viewed by 2472

Special Issue Editors

Dr. Francisco Rego

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Guest Editor
Department of Electrical and Computer Engineering, Institute for Systems and Robotics (ISR), Instituto Superior Técnico (IST), University of Lisbon, Lisbon, Portugal
Interests: control theory; advanced control theory; network; stability analysis; systems dynamics; stability; nonlinear dynamics; MATLAB simulation; modeling and simulation; Kalman filtering
Special Issues, Collections and Topics in MDPI journals
Dr. Ricardo Simões Santos

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Guest Editor
GOVCOPP, Campus Universitário de Santiago, University of Aveiro, 3810-193 Aveiro, Portugal
Interests: energy systems; sustainability; industrial engineering and management; soft computing
Special Issues, Collections and Topics in MDPI journals
Dr. Sylvain Bertrand

E-Mail Website
Guest Editor
Information Processing and Systems Department, ONERA – Paris-Saclay University, 91123 Palaiseau, France
Interests: unmanned aerial vehicles; autonomous and multi-agent systems; control systems; probabilistic risk assessment; applications to robotic and aerospace systems
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

As our world is becoming increasingly automated and interconnected, the need for robust, efficient, and intelligent control systems has never been more critical. This Special Issue is dedicated to exploring the forefront of this vital field, highlighting groundbreaking research and innovations that address contemporary challenges. Our focus includes the following topics. Advances and applications in reinforcement learning: introducing adaptive algorithms that enhance decision-making processes, allowing systems to learn and improve over time. Theoretical physics-informed learning: bridging the gap between machine learning and traditional physics, providing robust models that respect and leverage known physical laws. Path planning in complex environments: this is pivotal for the efficient and safe navigation of autonomous vehicles and robots. Multi-agent systems: enabling coordinated actions among multiple autonomous entities, unlocking new possibilities in complex, dynamic environments. Advances in fault-tolerant control systems: these are essential for maintaining functionality in the face of component failures, ensuring reliability and safety in critical applications.

This Issue aims to inspire and inform researchers, practitioners, and enthusiasts by showcasing the latest advancements in this field and fostering a deeper understanding of these transformative technologies. Join us in exploring the exciting developments that are shaping the future of control engineering.

Dr. Francisco Rego
Dr. Ricardo Simões Santos
Dr. Sylvain Bertrand
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

  • advanced control systems
  • control engineering
  • reinforcement learning
  • physics-informed machine learning
  • path planning
  • autonomous vehicles
  • multi-agent systems
  • fault-tolerant control
  • intelligent control
  • robotics

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Published Papers (3 papers)

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Research

23 pages, 2596 KiB  
Article
Adaptive Longitudinal Speed Control for Heavy-Duty Vehicles Considering Actuator Constraints and Disturbances Using Simulation Validation
by Junyoung Lee, Taeyoung Oh and Jinwoo Yoo
Appl. Sci. 2025, 15(13), 7327; https://doi.org/10.3390/app15137327 - 29 Jun 2025
Viewed by 342
Abstract
Heavy-duty vehicles (HDVs), such as buses and commercial trucks, display unique dynamic characteristics due to their high mass and specific actuator properties. These factors make HDVs particularly sensitive to changes in vehicle load and road gradient, which significantly affect their longitudinal control performance. [...] Read more.
Heavy-duty vehicles (HDVs), such as buses and commercial trucks, display unique dynamic characteristics due to their high mass and specific actuator properties. These factors make HDVs particularly sensitive to changes in vehicle load and road gradient, which significantly affect their longitudinal control performance. In other words, such variations present considerable challenges in maintaining stable and efficient longitudinal control of HDVs. To address these challenges, this study proposes a model reference adaptive control (MRAC) framework explicitly designed for HDVs. The control system utilizes a state predictor to mitigate actuator load problems caused by high-frequency components in the adaptive control input. In addition, when input constraints are present, the reference model is modified using the μ-modification technique. The system satisfies Lyapunov stability conditions and ensures stable longitudinal control performance across a range of driving conditions. The proposed closed-loop longitudinal control system was evaluated by implementing the controller using the vehicle dynamics simulation software IPG TruckMaker 12.0.1 and integrated with MATLAB/Simulink R2022b. The test scenarios included repetitive speed change maneuvers, which accounted for uncertainties such as road gradients, headwinds, and vehicle load conditions. The simulation results show that the control system not only effectively suppresses disturbances but also enables stable longitudinal speed tracking by considering actuator load and constraints, outperforming conventional MRAC. These results suggest that the proposed closed-loop longitudinal control system can be effectively applied to HDVs. The findings suggest that the proposed closed-loop longitudinal control system can be effectively applied to HDVs, ensuring improved stability and performance under real-world driving conditions. Full article
(This article belongs to the Special Issue Advanced Control Systems and Control Engineering)
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17 pages, 661 KiB  
Article
The Robust Control of a Nonsmooth or Switched Control-Affine Uncertain Nonlinear System Using an Auxiliary Robust Integral of the Sign of the Error (ARISE) Controller
by Sujata Basyal, Jonathan Ting, Kislaya Mishra and Brendon Connor Allen
Appl. Sci. 2025, 15(8), 4482; https://doi.org/10.3390/app15084482 - 18 Apr 2025
Viewed by 376
Abstract
To deal with uncertainties in a dynamic system, many nonlinear control approaches have been considered. Unique challenges arise from uncertainties that are bounded by constants, which has led to the development of both continuous and discontinuous control methods. However, these methods either are [...] Read more.
To deal with uncertainties in a dynamic system, many nonlinear control approaches have been considered. Unique challenges arise from uncertainties that are bounded by constants, which has led to the development of both continuous and discontinuous control methods. However, these methods either are limited to classes of smooth nonlinear models or have a tendency to result in chattering during practical applications. In this work, a novel auxiliary robust integral of the sign of the error (ARISE) controller is proposed to prevent chattering and deal with uncertainties (even those bounded by constants) for general, switched, and nonsmooth control-affine nonlinear systems. The ARISE control system includes a unique auxiliary error that is designed to inject a sliding mode (SM) term directly into the error system without including an SM term in the controller itself. In fact, the ARISE control law includes an integral SM term that is continuous. Consequently, the ARISE control law minimizes the chattering effect that results from discontinuous SM terms. The proposed ARISE control system is augmented with an adaptive update law to deal with the unknown control effectiveness matrix in the dynamic model. To prove the effectiveness of the ARISE controller, a nonlinear stability analysis was conducted and resulted in semi-global exponential tracking towards an ultimate bound. Furthermore, the performance of the proposed controller was evaluated and compared against a traditional SM controller through simulations using a switched Van der Pol oscillator model. It was concluded that the proposed ARISE controller performs better for a switched system than an SM controller. The improved performance of the ARISE controller was consistent across different dynamic parameters and disturbances. Full article
(This article belongs to the Special Issue Advanced Control Systems and Control Engineering)
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24 pages, 4942 KiB  
Article
Levitating Control System of Maglev Ruler Based on Active Disturbance Rejection Controller
by Jiyuan Sun, Gengyun Tian, Pin Li, Chunlin Tian and Zhenxiong Zhou
Appl. Sci. 2024, 14(17), 8069; https://doi.org/10.3390/app14178069 - 9 Sep 2024
Cited by 1 | Viewed by 1038
Abstract
The autonomous displacement and displacement measurement functions of the maglev ruler are performed by the mover core. The magnetic levitation ruler can serve as a viable alternative to the linear measurement system of a coordinate measuring machine. The stability of the four magnetic [...] Read more.
The autonomous displacement and displacement measurement functions of the maglev ruler are performed by the mover core. The magnetic levitation ruler can serve as a viable alternative to the linear measurement system of a coordinate measuring machine. The stability of the four magnetic fields in air gaps and the levitation position of the maglev ruler is one of the key factors for the stability of the thrust force on the power core, and it is also one of the key factors for ensuring the precision of the maglev ruler. There is cross-coupling between the two ends of the mover core of the maglev ruler, resulting in a strongly coupled, nonlinear, multi-input and multi-output system for the levitating system of the maglev ruler. This paper establishes a mathematical model for the levitating system of the maglev ruler and designs a levitating control system for the maglev ruler based on an active disturbance rejection control algorithm to achieve decoupling and disturbance suppression. Through simulation analysis and experimental testing of the levitating system with starting and disturbance, it is proved that the levitating control system of the maglev ruler has good dynamic characteristics, static characteristics, and robustness. Full article
(This article belongs to the Special Issue Advanced Control Systems and Control Engineering)
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