Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
4.7
2.9
Journals
Electronics
Special Issues
Advances in Autonomous Control Systems and Their Applications
share announcement

Advances in Autonomous Control Systems and Their Applications

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

Deadline for manuscript submissions: closed (31 January 2023) | Viewed by 16544

Special Issue Editors

Dr. Elías Revestido Herrero

E-Mail Website
Guest Editor
Dept. of Electronic Technology, Systems Engineering and Automatic Control, University of Cantabria, E.T.S. de Náutica, C/ Gamazo 1, 39004 Santander, Spain
Interests: system identification; guidance navigation and control of marine vehicles; dynamic positioning of marine structures; marine remote laboratory
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Victor M. Becerra

E-Mail Website
Guest Editor
School of Engineering, University of Portsmouth, Anglesea Building, Anglesea Road, Portsmouth, PO1 3DJ, UK
Interests: computational optimal control; nonlinear control; fault diagnosis; fault-tolerant control; autonomous control systems; state estimation; smart grids; solar energy; control of power systems; control of energy storage
Special Issues, Collections and Topics in MDPI journals
Dr. Francisco Jesus Velasco

E-Mail Website
Guest Editor
Department of Electronics Technology, Systems and Automation Engineering, Universidad de Cantabria, 39004 Santander, Spain
Interests: guidance navigation and control of marine vehicles; maritime unmanned systems; engineering education; control systems engineering
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Autonomous control refers to the ability of a system to function well in the face of high environmental uncertainty, and the ability to correct for system faults without the need for external intervention. This is distinct from automation, which is commonly characterized as an operation carried out with little or no human intervention.

While it is common to think of different levels of autonomy, it is acknowledged that the availability of inexpensive sensors, the ability to handle massive volumes of data, and the processing capacity and methodologies to execute the essential decision-making algorithms in real-time are key factors in making real autonomous control systems possible.

In the last few decades, significant advances have been made in control systems for different types of autonomous and semi-autonomous vehicles in both military and civilian domains. In most of these applications, the control system plays a role of paramount importance in the achievement of the required performance, safety, and autonomy specifications. This Special Issue focusses on emerging control, sensing, dynamic modelling, and system identification methodologies and applications related to autonomous and semi-autonomous maritime, aerial and terrestrial vehicles both in military and civilian domains.

We aim is to seek high-quality submissions reporting research and real applications covering topics including, but not limited to:

  • Advanced control methodologies for autonomous vehicles;
  • Sensing for autonomous vehicles;
  • Modelling and system identification for the autonomous control of vehicles;
  • Applications to autonomous and semi-autonomous under-water vessels, surface vessels, aerial vehicles, and ground vehicles.

Dr. Elías Herrero
Prof. Dr. Victor Becerra
Dr. Francisco Jesus Velasco
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

  • Autonomous control
  • Autonomous vehicles
  • Sensing for autonomy
  • Modelling and system identification for autonomous control
  • Fault-tolerant control for autonomous vehicles

Related Special Issue

Published Papers (7 papers)

Download All Papers
Order results
Result details
Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:

Research

34 pages, 11091 KiB  
Article
Development and Experimental Validation of Control Algorithm for Person-Following Autonomous Robots
by J. Enrique Sierra-García, Víctor Fernández-Rodríguez, Matilde Santos and Eduardo Quevedo
Electronics 2023, 12(9), 2077; https://doi.org/10.3390/electronics12092077 - 30 Apr 2023
Cited by 4 | Viewed by 1853
Abstract
Automatic guided vehicles, in particular, and industrial autonomous mobile robots, in general, are commonly used to automate intralogistics processes. However, there are certain logistic tasks, such as picking objects of variable sizes, shapes, and physical characteristics, that are very difficult to handle fully [...] Read more.
Automatic guided vehicles, in particular, and industrial autonomous mobile robots, in general, are commonly used to automate intralogistics processes. However, there are certain logistic tasks, such as picking objects of variable sizes, shapes, and physical characteristics, that are very difficult to handle fully automatically. In these cases, the collaboration between humans and autonomous robots has been proven key for the efficiency of industrial processes and other applications. To this aim, it is necessary to develop person-following robot solutions. In this work, we propose a fully autonomously controlling autonomous robotic interaction for environments with unknown objects based on real experiments. To do so, we have developed an active tracking system and a control algorithm to implement the person-following strategy on a real industrial automatic-guided vehicle. The algorithm analyzes the cloud of points measured by light detection and ranging (LIDAR) sensor to detect and track the target. From this scan, it estimates the speed of the target to obtain the speed reference value and calculates the direction of the reference by a pure-pursuit algorithm. In addition, to enhance the robustness of the solution, spatial and temporal filters have been implemented to discard obstacles and detect crossings between humans and the automatic industrial vehicle. Static and dynamic test campaigns have been carried out to experimentally validate this approach with the real industrial autonomous-guided vehicle and a safety LIDAR. Full article
(This article belongs to the Special Issue Advances in Autonomous Control Systems and Their Applications)
►▼ Show Figures

Graphical abstract

14 pages, 2072 KiB  
Article
Null-Space-Based Multi-Player Pursuit-Evasion Games Using Minimum and Maximum Approximation Functions
by Xinxin Guo, An Guo and Suping Zhao
Electronics 2022, 11(22), 3729; https://doi.org/10.3390/electronics11223729 - 14 Nov 2022
Cited by 2 | Viewed by 1127
Abstract
In this article, pursuit and evasion policies are developed for multi-player pursuit–evasion games, while obstacle avoidance and velocity constraints are considered simultaneously. As minimum and maximum approximation functions are both differentiable, pursuit and evasion objectives can be transformed into solving the corresponding differential [...] Read more.
In this article, pursuit and evasion policies are developed for multi-player pursuit–evasion games, while obstacle avoidance and velocity constraints are considered simultaneously. As minimum and maximum approximation functions are both differentiable, pursuit and evasion objectives can be transformed into solving the corresponding differential expressions. For obstacle avoidance, a modified null-space-based approach is designed, which can ensure that all pursuers and evaders of pursuit–evasions are safe to minimize pursuit objective and maximize evasion objective, respectively. Rigorous theoretical analyses are provided to design constrained pursuit and evasion policies with obstacle avoidance. Finally, the performance of proposed policies is demonstrated by simulation results in 3-dimensional space. Full article
(This article belongs to the Special Issue Advances in Autonomous Control Systems and Their Applications)
►▼ Show Figures

Figure 1

17 pages, 3377 KiB  
Article
Evaluating the Efficiency of Connected and Automated Buses Platooning in Mixed Traffic Environment
by Suyong Park, Sanghyeon Nam, Gokul S. Sankar and Kyoungseok Han
Electronics 2022, 11(19), 3231; https://doi.org/10.3390/electronics11193231 - 08 Oct 2022
Cited by 3 | Viewed by 1464
Abstract
Due to the battery capacity limitation of battery electric vehicles (BEVs), the importance of minimizing energy consumption has been increasing in recent years. In the mean time, for improving vehicle energy efficiency, platooning has attracted attention of several automakers. Using the connected and [...] Read more.
Due to the battery capacity limitation of battery electric vehicles (BEVs), the importance of minimizing energy consumption has been increasing in recent years. In the mean time, for improving vehicle energy efficiency, platooning has attracted attention of several automakers. Using the connected and automated vehicles (CAVs) technology, platooning can achieve a longer driving range while preserving a closer distance from the preceding vehicle, resulting in the minimization of the aerodynamic force. However, undesired behaviors of human-driven vehicles (HVs) in the platooning group can prohibit the maximization of the energy efficiency. In this paper, we developed a speed planner based on the model predictive control (MPC) to minimize the total platooning energy consumption, and HVs were programmed to maintain a long enough distance from the preceding vehicle to avoid collision. The simulations were performed to determine how HV influences the efficiencies of the platooning group, which is composed of CAVs and HVs together, in several scenarios including the different positions and numbers of the HVs. Test results show that the CAVs planned by our approach reduces energy consumption by about 4% or more than 4% compared to that of the HVs. Full article
(This article belongs to the Special Issue Advances in Autonomous Control Systems and Their Applications)
►▼ Show Figures

Figure 1

22 pages, 25137 KiB  
Article
Fuzzy Based Backstepping Control Design for Stabilizing an Underactuated Quadrotor Craft under Unmodelled Dynamic Factors
by Ghulam E. Mustafa Abro, Saiful Azrin B. M. Zulkifli, Zain Anwar Ali, Vijanth Sagayan Asirvadam and Bhawani Shankar Chowdhry
Electronics 2022, 11(7), 999; https://doi.org/10.3390/electronics11070999 - 23 Mar 2022
Cited by 5 | Viewed by 2288
Abstract
Since the quadrotor unmanned aerial vehicle (UAV) is one of the systems that has four (4) control inputs and six (6) degree of freedom (DOF) which makes it as an underactuated system. Such underactuated mechatronic systems are very difficult to stabilize but at [...] Read more.
Since the quadrotor unmanned aerial vehicle (UAV) is one of the systems that has four (4) control inputs and six (6) degree of freedom (DOF) which makes it as an underactuated system. Such underactuated mechatronic systems are very difficult to stabilize but at the same time these systems are power efficient and cost-effective because of a lower number of actuators. Later, if someone tries to stabilize this underactuated quadrotor UAV under the impact of unmodelled dynamic factors, it will lead to huge instability, low convergence rate, chattering effect, trajectory deviation and may also encounter some of the serious transient and steady state issues as well. This paper presents one of the adaptive-robust control algorithms, called the fuzzy based backstepping control (FBSC) design, to address the quadrotor’s helical trajectory tracking issue under an influence of unmodelled dynamic factors and external disturbances. This manuscript proposes the synthesis of the proposed FBSC design using MATLAB and Simulink software whereas these results are correlated with the conventional backstepping control (BSC) algorithm to show the effectiveness of the proposed algorithm by computing the integral absolute error values with and without disturbances. Full article
(This article belongs to the Special Issue Advances in Autonomous Control Systems and Their Applications)
►▼ Show Figures

Figure 1

16 pages, 13045 KiB  
Article
Iterative Self-Tuning Minimum Variance Control of a Nonlinear Autonomous Underwater Vehicle Maneuvering Model
by Maria Tomas-Rodríguez, Elías Revestido Herrero and Francisco J. Velasco
Electronics 2021, 10(21), 2686; https://doi.org/10.3390/electronics10212686 - 03 Nov 2021
Viewed by 1669
Abstract
This paper addresses the problem of control design for a nonlinear maneuvering model of an autonomous underwater vehicle. The control algorithm is based on an iteration technique that approximates the original nonlinear model by a sequence of linear time-varying equations equivalent to the [...] Read more.
This paper addresses the problem of control design for a nonlinear maneuvering model of an autonomous underwater vehicle. The control algorithm is based on an iteration technique that approximates the original nonlinear model by a sequence of linear time-varying equations equivalent to the original nonlinear problem and a self-tuning control method so that the controller is designed at each time point on the interval for trajectory tracking and heading angle control. This work makes use of self-tuning minimum variance principles. The benefit of this approach is that the nonlinearities and couplings of the system are preserved, unlike in the cases of control design based on linearized systems, reducing in this manner the uncertainty in the model and increasing the robustness of the controller. The simulations here presented use a torpedo-shaped underwater vehicle model and show the good performance of the controller and accurate tracking for certain maneuvering cases. Full article
(This article belongs to the Special Issue Advances in Autonomous Control Systems and Their Applications)
►▼ Show Figures

Figure 1

15 pages, 5692 KiB  
Article
Model Predictive Control for Autonomous Driving Vehicles
by Trieu Minh Vu, Reza Moezzi, Jindrich Cyrus and Jaroslav Hlava
Electronics 2021, 10(21), 2593; https://doi.org/10.3390/electronics10212593 - 24 Oct 2021
Cited by 15 | Viewed by 4604
Abstract
The field of autonomous driving vehicles is growing and expanding rapidly. However, the control systems for autonomous driving vehicles still pose challenges, since vehicle speed and steering angle are always subject to strict constraints in vehicle dynamics. The optimal control action for vehicle [...] Read more.
The field of autonomous driving vehicles is growing and expanding rapidly. However, the control systems for autonomous driving vehicles still pose challenges, since vehicle speed and steering angle are always subject to strict constraints in vehicle dynamics. The optimal control action for vehicle speed and steering angular velocity can be obtained from the online objective function, subject to the dynamic constraints of the vehicle’s physical limitations, the environmental conditions, and the surrounding obstacles. This paper presents the design of a nonlinear model predictive controller subject to hard and softened constraints. Nonlinear model predictive control subject to softened constraints provides a higher probability of the controller finding the optimal control actions and maintaining system stability. Different parameters of the nonlinear model predictive controller are simulated and analyzed. Results show that nonlinear model predictive control with softened constraints can considerably improve the ability of autonomous driving vehicles to track exactly on different trajectories. Full article
(This article belongs to the Special Issue Advances in Autonomous Control Systems and Their Applications)
►▼ Show Figures

Figure 1

17 pages, 5213 KiB  
Article
LED Module Calibration Strategy to Improve Measurement Accuracy of TRO Concentration
by Gwang-Ho Lee, Do-Hyun Kim, Min-Soo Kim, Hee-Je Kim and Sung-Shin Kim
Electronics 2021, 10(19), 2410; https://doi.org/10.3390/electronics10192410 - 02 Oct 2021
Viewed by 1956
Abstract
In order to limit various alien species by ballast water, electrolysis of ballast water is used to sterilize microorganisms. In this process, total residual oxidizer (TRO) is produced, and it is necessary to measure the precise TRO concentration to prevent excessive disinfection by-products [...] Read more.
In order to limit various alien species by ballast water, electrolysis of ballast water is used to sterilize microorganisms. In this process, total residual oxidizer (TRO) is produced, and it is necessary to measure the precise TRO concentration to prevent excessive disinfection by-products and limit emissions. In this TRO concentration measurement system, a white LED module and RGB sensor are used to measure the absorbance through the DPD colorimetric method. The intensity of LED light has a little error for each LED module. In addition, the effect of LED aging in which the intensity of the light source decreases with the elapsed time. For this reason, the TRO concentration measurement error increases. To solve this problem, we propose an LED module calibration algorithm by current PI control and an optimal LED operation time derivation to reduce the effect of LED aging. A large number of LED modules were applied to various seawater environments. In the conventional method, the measurement accuracy and precision of the average TRO concentration were 6.56% and 9.54%, respectively, and measurement accuracy and precision through the proposed algorithm and LED aging optimization were greatly reduced to 0.10% and 0.85%, respectively. In addition, we derived that LED aging was minimized when the measurement time of LED light was 1 s and the turn-off time of the LED light was 10 s. Through these experimental results, we confirmed that the non-uniform LED light is improved by the proposed algorithm. Furthermore, the standard values for TRO concentration measurement (accuracy: less than 5%, precision: less than 2%) were satisfied. Full article
(This article belongs to the Special Issue Advances in Autonomous Control Systems and Their Applications)
►▼ Show Figures

Figure 1

Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
 
Displaying articles 1-7
Back to TopTop