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Electronics
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Feature Papers in Systems & Control Engineering
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Feature Papers in Systems & Control Engineering

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

Deadline for manuscript submissions: closed (31 July 2023) | Viewed by 12180

Special Issue Editors

Prof. Dr. Olivier Sename

E-Mail Website
Guest Editor
GIPSA-Lab, Grenoble Institute of Technology, Universite Grenoble Alpes, Saint Martin d'Heres, 38400 Grenoble, France
Interests: modeling and control of linear parameter varying systems; control of automotive vehicle dynamics and of autonomous vehicles
Dr. Soheib Fergani

E-Mail Website
Guest Editor
LAAS - CNRS, Université de Toulouse, CNRS, UPS, Toulouse, France
Interests: robust control; LPV control; nonlinear control; setmembership estimation; interval analysis; FTC control and diagnosis; automotive control; UAV control and navigation

Special Issue Information

Dear Colleagues,

We are pleased to announce that the section Systems & Control Engineering is now compiling a collection of papers submitted by the Editorial Board Members (EBMs) of our section and outstanding scholars in this research field. We welcome contributions as well as recommendations from the EBMs.

The purpose of this Special Issue is to publish a set of papers that characterise the best insightful and influential original articles or reviews, with our section’s EBMs discussing key topics in the field. We expect these papers to be widely read and highly influential within the field.

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

  • Robotics and artificial intelligence;
  • Intelligent and autonomous systems;
  • Automated vehicles and intelligent transport systems;
  • Smart mechatronic systems;
  • Renewable energy systems and smart grids;
  • Data-driven modeling and control;
  • Cyber-physical systems and network security;
  • Distributed networked control systems;
  • Complex systems (non-linear, hybrid, switched, uncertain, etc.);
  • Monitoring and diagnosis;
  • Fault-tolerant control (reconfiguration);
  • Human-in-the-loop control;
  • Interaction Human & Cyber-Physical System;
  • Industrial electronics;
  • Advanced manufacturing systems.

Prof. Dr. Olivier Sename
Dr. Soheib Fergani
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 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

  • cyber-physical systems
  • advanced manufacturing systems
  • complex systems
  • distributed networked control systems
  • intelligent transport systems
  • data-driven modelling and control
  • smart mechatronic systems

Published Papers (7 papers)

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Research

Jump to: Review

21 pages, 7910 KiB  
Article
ROS Implementation of Planning and Robust Control Strategies for Autonomous Vehicles
by Mohamad Hachem, Ariel M. Borrell, Olivier Sename, Hussam Atoui and Marcelo Morato
Electronics 2023, 12(17), 3680; https://doi.org/10.3390/electronics12173680 - 31 Aug 2023
Viewed by 1406
Abstract
Autonomous vehicles are rapidly emerging as a crucial sector within the automotive industry. Several companies are investing in the development and enhancement of technologies, which presents challenging problems in the context of robotics and control. In particular, this work primarily focuses on the [...] Read more.
Autonomous vehicles are rapidly emerging as a crucial sector within the automotive industry. Several companies are investing in the development and enhancement of technologies, which presents challenging problems in the context of robotics and control. In particular, this work primarily focuses on the creation of an autonomous vehicle architecture utilizing the robotic operating system (ROS2) framework, accompanied by advanced control algorithms. In order to facilitate the development and implementation of lateral vehicle dynamics controllers, a reduced-size automated car available in GIPSA-Lab is used as an experimental platform. The objective is to design robust controllers capable of achieving optimal tracking and stability. Accordingly, this problem is tackled under different robust control syntheses, considering the H∞ approach: using linear time-invariant (LTI) and linear parameter-varying (LPV) model representations. Several simulation and experimental results are included to demonstrate the efficiency of the controllers. Full article
(This article belongs to the Special Issue Feature Papers in Systems & Control Engineering)
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21 pages, 6779 KiB  
Article
A Robust Lateral Control Architecture for Off-Road Vehicle Guidance on Deformable Soils
by David Vieira, Antoine Vie, Rodolfo Orjuela, Matthias Spisser and Michel Basset
Electronics 2023, 12(11), 2395; https://doi.org/10.3390/electronics12112395 - 25 May 2023
Viewed by 917
Abstract
This paper introduces a novel lateral guidance strategy for autonomous ground vehicles operating in deformable environments. The strategy combines a geometric algorithm with a dynamic controller to leverage the advantages of both methods. The geometric algorithm is based on a modified Pure Pursuit [...] Read more.
This paper introduces a novel lateral guidance strategy for autonomous ground vehicles operating in deformable environments. The strategy combines a geometric algorithm with a dynamic controller to leverage the advantages of both methods. The geometric algorithm is based on a modified Pure Pursuit method, which calculates the lateral error by considering a dynamic parameter associated with the look-ahead distance. The controller takes model uncertainties and time-variant parameters into account in a grid-based LPV (Linear Parameter Varying) synthesis. To validate the proposed control architecture, a dedicated off-road vehicle simulator that accounted for deformable soils was used. The effectiveness and robustness of the proposed lateral guidance strategy were demonstrated by integrating and validating the control architecture on a vehicle prototype. The results indicate that the proposed approach effectively handled complex and uncertain deformable environments. Overall, this study presents a new lateral guidance strategy that enhances the performance and reliability of autonomous ground vehicles in challenging environments. Full article
(This article belongs to the Special Issue Feature Papers in Systems & Control Engineering)
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18 pages, 4213 KiB  
Article
Linear Active Disturbance Rejection Control for a Laser Powder Bed Fusion Additive Manufacturing Process
by S. Zahid Hussain, Zareena Kausar, Zafar Ullah Koreshi, Muhammad Faizan Shah, Ahmd Abdullah and Muhammad Umer Farooq
Electronics 2023, 12(2), 471; https://doi.org/10.3390/electronics12020471 - 16 Jan 2023
Cited by 1 | Viewed by 1567
Abstract
Functional metal parts with complicated geometry and internal features for the aerospace and automotive industries can be created using the laser powder bed fusion additive manufacturing (AM) technique. However, the lack of uniform quality of the produced parts in terms of strength limits [...] Read more.
Functional metal parts with complicated geometry and internal features for the aerospace and automotive industries can be created using the laser powder bed fusion additive manufacturing (AM) technique. However, the lack of uniform quality of the produced parts in terms of strength limits its enormous potential for general adoption in industries. Most of the defects in selective laser melting (SLM) parts are associated with a nonuniform melt pool size. The melt pool area may fluctuate in spite of constant SLM processing parameters, like laser power, laser speed, hatching distance, and layer thickness. This is due to heat accumulation in the current track from previously scanned tracks in the current layer. The feedback control strategy is a promising tool for maintaining the melt pool dimensions. In this study, a dynamic model of the melt pool cross-sectional area is considered. The model is based on the energy balance of lumped melt pool parameters. Energy coming from previously scanned tracks is considered a source of disturbance for the current melt pool cross-section area in the control algorithm. To track the reference melt pool area and manage the disturbances and uncertainties, a linear active disturbance rejection control (LADRC) strategy is considered. The LADRC control technique is more successful in terms of rapid reference tracking and disturbance rejection when compared to the conventional PID controller. The simulation study shows that an LADRC control strategy presents a 65% faster time response than the PID, a 97% reduction in the steady state error, and a 98% reduction in overshoot. The integral time absolute error (ITAE) performance index shows 95% improvement for reference tracking of the melt pool area in SLM. In terms of reference tracking and robustness, LADRC outperforms the PID controller and ensures that the melt pool size remains constant. Full article
(This article belongs to the Special Issue Feature Papers in Systems & Control Engineering)
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14 pages, 1835 KiB  
Article
Stochastic Fixed-Time Tracking Control for the Chaotic Multi-Agent-Based Supply Chain Networks with Nonlinear Communication
by Lili Shi, Wanli Guo, Lu Wang, Stelios Bekiros, Hajid Alsubaie, Ahmed Alotaibi and Hadi Jahanshahi
Electronics 2023, 12(1), 83; https://doi.org/10.3390/electronics12010083 - 25 Dec 2022
Cited by 2 | Viewed by 1240
Abstract
The multi-agent-based supply chain network is a dynamic system consisting of multiple subchains connected by information flows, material flows and capital flow, etc. The consensus of multi-agent systems is often applied to the cooperation between subchains and inventory management in supply chain networks. [...] Read more.
The multi-agent-based supply chain network is a dynamic system consisting of multiple subchains connected by information flows, material flows and capital flow, etc. The consensus of multi-agent systems is often applied to the cooperation between subchains and inventory management in supply chain networks. Considering the ubiquitous external disturbances, this paper mainly considers the fixed-time consensus of a stochastic three-echelon multi-agent-based supply chain system. A nonlinear feedback fixed-time control protocol is constructed for ensuring the consensus of the considered supply chain network. Using the stability theory of stochastic differential equations, sufficient conditions for the fixed-time consensus and the upper bound estimation of the settling time are obtained. Finally, the validity of the control protocol and the correctness of the theoretical analysis are revealed by numerical simulation. Full article
(This article belongs to the Special Issue Feature Papers in Systems & Control Engineering)
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33 pages, 4127 KiB  
Article
Speed-Gradient Adaptive Control for Parametrically Uncertain UAVs in Formation
by Alexander M. Popov, Daniil G. Kostrygin, Anatoly A. Shevchik and Boris Andrievsky
Electronics 2022, 11(24), 4187; https://doi.org/10.3390/electronics11244187 - 14 Dec 2022
Cited by 5 | Viewed by 1527
Abstract
The paper is devoted to the problem of the decentralized control of unmanned aerial vehicle (UAV) formation in the case of parametric uncertainty. A new version of the feedback linearization approach is proposed and used for a point mass UAV model transformation. As [...] Read more.
The paper is devoted to the problem of the decentralized control of unmanned aerial vehicle (UAV) formation in the case of parametric uncertainty. A new version of the feedback linearization approach is proposed and used for a point mass UAV model transformation. As result, a linear model is obtained containing an unknown value of the UAV mass. Employing the speed-gradient design method and the implicit reference model concept, a combined adaptive control law is proposed for a single UAV, including the UAV’s mass estimation and adaptive tuning of the controller parameters. The obtained new algorithms are then used to address the problem of consensus-based decentralized control of the UAV formation. Rigorous stability conditions for control and identification are derived, and simulation results are presented to demonstrate the quality of the closed-loop control system for various conditions. Full article
(This article belongs to the Special Issue Feature Papers in Systems & Control Engineering)
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22 pages, 7122 KiB  
Article
A Modified Active-Disturbance-Rejection Control with Sliding Modes for an Uncertain System by Using a Novel Reaching Law
by Dong Zhang, Tao Wu, Shangyao Shi and Zhen Dong
Electronics 2022, 11(15), 2392; https://doi.org/10.3390/electronics11152392 - 31 Jul 2022
Cited by 7 | Viewed by 1505
Abstract
This article presents a modified active-disturbance-rejection control (ADRC) combined with a sliding mode control (SMC) regarding the tracking control problems for plants with unmatched uncertainty. The proposed modified active-disturbance-rejection control with sliding mode (ADRC-SM) employs a reduced-order extended state observer (ESO) for estimating [...] Read more.
This article presents a modified active-disturbance-rejection control (ADRC) combined with a sliding mode control (SMC) regarding the tracking control problems for plants with unmatched uncertainty. The proposed modified active-disturbance-rejection control with sliding mode (ADRC-SM) employs a reduced-order extended state observer (ESO) for estimating various uncertainties of system in time, including unmatched and matched uncertainties. Meanwhile, a novel reaching law of SMC was designed by using the cycloid function as the main controller of ADRC, which ensures the robustness of the uncertain system. Due to the reduced-order ESO tracking and compensating for various uncertainties in the system as a total disturbance, the upper bound of the disturbance in the SMC is relaxed. The gain coefficient of the reaching law only needs to be designed to be larger than the limit of the lumped disturbance; thus, the chattering problem is greatly reduced. The designed new reaching law of the cycloid function shortens the time for the system state’s convergence to the sliding mode’s surface. The cycloid function replaces the switching function in the traditional reaching law, making the actual control input continuous and shortening the approach time. Compared with traditional ADRC-SM, the use of multiple ESOs or intelligent algorithms to approximate plant parameters can be avoided, the design is simplified, its robustness is enhanced, computational costs are reduced, and the convergence time is reduced. The controlled object with unmatched uncertainty is transformed into a system with matched uncertainty using state-space transformation, which reduces the complexity of the controller’s design. In addition, the stability analysis of the closed-loop system is carried out based on the Lyapunov method. Simulations and experiments verify that the modified ADRC-SM has the merits of fast response, small overshoot, small steady-state error, strong anti-interference competence, and high control accuracy. Full article
(This article belongs to the Special Issue Feature Papers in Systems & Control Engineering)
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Review

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24 pages, 995 KiB  
Review
Review on Haptic Assistive Driving Systems Based on Drivers’ Steering-Wheel Operating Behaviour
by Simplice Igor Noubissie Tientcheu, Shengzhi Du and Karim Djouani
Electronics 2022, 11(13), 2102; https://doi.org/10.3390/electronics11132102 - 05 Jul 2022
Cited by 4 | Viewed by 2885
Abstract
With the availability of modern assistive techniques, ambient intelligence, and the Internet of Things (IoT), various innovative assistive environments have been developed, such as driving assistance systems (DAS), where the human driver can be provided with physical and emotional assistance. In this human–machine [...] Read more.
With the availability of modern assistive techniques, ambient intelligence, and the Internet of Things (IoT), various innovative assistive environments have been developed, such as driving assistance systems (DAS), where the human driver can be provided with physical and emotional assistance. In this human–machine collaboration system, haptic interaction interfaces are commonly employed because they provide drivers with a more manageable way to interact with other components. From the view of control system theory, this is a typical closed-loop feedback control system with a human in the loop. To make such a system work effectively, both the driving behaviour factors, and the electrical–mechanical components should be considered. However, the main challenge is how to deal with the high degree of uncertainties in human behaviour. This paper aims to provide an insightful overview of the relevant work. The impact of various types of haptic assistive driving systems (haptic guidance and warning systems) on driving behaviour performance is discussed and evaluated. In addition, various driving behaviour modelling systems are extensively investigated. Furthermore, the state-of-the-art driving behaviour controllers are analysed and discussed in driver–vehicle–road systems, with potential improvements and drawbacks addressed. Finally, a prospective approach is recommended to design a robust model-free controller that accounts for uncertainties and individual differences in driving styles in a haptic assistive driving system. The outcome indicated that the haptic feedback system applied to the drivers enhanced their driving performance, lowered their response time, and reduced their mental workload compared to a system with auditory or visual signals or without any haptic system, despite some annoyances and system conflicts. The driving behaviour modelling techniques and the driving behaviour control with a haptic feedback system have shown good matching and improved the steering wheel’s base operation performance. However, mathematical principles, a statistical approach, and the lack of consideration of the individual differences in the driver–vehicle–road system make the modelling and the controller less robust and inefficient for different driving styles. Full article
(This article belongs to the Special Issue Feature Papers in Systems & Control Engineering)
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