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
Feasible, Robust and Reliable Automation and Control for Autonomous Systems
share announcement

Feasible, Robust and Reliable Automation and Control for Autonomous Systems

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

Deadline for manuscript submissions: closed (30 April 2022) | Viewed by 33429

Printed Edition Available!
A printed edition of this Special Issue is available here.

Special Issue Editors

Dr. Umar Zakir Abdul Hamid

E-Mail Website
Guest Editor
CEVT (China Euro Vehicle Technology AB), Goteborg, Sweden
Interests: advanced sriver assistance systems (ADAS); guidance, navigation & control for autonomous vehicle (GNC); motion, mission & path planning; risk assessment; collision avoidance; nonlinear optimal control; and model-based simulations
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Argyrios Zolotas

E-Mail Website
Guest Editor
Centre for Autonomous and Cyber-Physical Systems, SATM, Cranfield University, Bedford MK43 0AL, UK
Interests: autonomous systems; mechatronics & advanced controls; vehicle health management
Assist. Prof. Dr. Chuan Hu

E-Mail Website
Guest Editor
Department of Mechanical Engineering, University of Alaska Fairbanks, Fairbanks, AK 99775, USA
Interests: decision-making; motion planning and control of autonomous vehicles; human-vehicle interaction; trust dynamics; shared control; ADAS; dynamics and control; state and parameter estimations; mechatronics

Special Issue Information

Dear Colleagues,

The past few decades have seen a rapid development towards autonomous systems. Increasing computational power ability and advances in new computing devices nowadays allow for feasible real-time implementation of autonomous systems. This has been further supported by large scale research in autonomous systems applications, including (but not limited) ground, aerial, maritime vehicles, mobile robotics. Different to automated systems, an autonomous system employs situational awareness information, via perception modules, used by the (normally) multi-layer control strategy to command the effectors driving the system. Given that the real world consists of dynamic and varied conditions environment, a reliable control strategy for autonomous systems should offer a safe, reliable, robust solution. Thus, in this proposed special issue on ‘Feasible, Robust and Reliable Automation and Control for Autonomous Systems’, the aim is to have wider dissemination of the control strategy topics for multiple types autonomous systems not constrained to a single platform. The special issue aims to highlight current research in the control field for autonomous systems, as well as showcasing the state-of-the-art control strategy approaches for the autonomous platforms. We strongly believe this special issue call will strongly appeal to control systems related researchers in applications typified in the fields of ground, aerial, maritime vehicles and robotics. Thus, this special issue aims to reflect on the most recent progress of control strategy for autonomous platforms, where the potential topics include, but are not limited to:

  • Control System Design for Autonomous Systems (Road Vehicles, Mobile Robots, Autonomous Surface Vehicles, Autonomous VTOL, Autonomous Machinery).
  • Vehicle and Mobile Robotics Automation
  • Robustness Analysis of Control Strategy Performance of Autonomous Systems
  • Kinematics, Dynamics and Model Nonlinearity effects to the controller performance of the Autonomous Systems
  • Path, trajectory and motion tracking performance of control strategy for autonomous systems in varied conditions
  • Real-time comparisons of controller performances for Autonomous Systems
  • Stability analysis of the controller performance for autonomous systems
  • Gain analysis of the control strategy for autonomous systems
  • Performance Assessment methods for control system performance of autonomous systems
  • Real-Time Validation of multi-objective dynamic Control Strategy Performance of an autonomous system
  • State estimation for autonomous system control strategy
  • Disturbances for autonomous platforms control systems
  • Control strategies for autonomous platforms in uncertain environments
  • Optimal and nonlinear control strategy for autonomous systems such as Model Predictive Control, H-infinity, Sliding Mode Control and Linear-quadratic control.
  • High-level and low-level controller design and implementation for autonomous systems.
  • Control Systems for Robotics Automation
Dr. Umar Zakir Abdul Hamid
Prof. Dr. Argyrios Zolotas
Assist. Prof. Dr. Chuan Hu
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

  • Control Strategy for Autonomous Systems
  • Control Systems for Autonomous Robots
  • Control Systems for Autonomous Vehicles
  • Control Systems for Autonomous VTOL
  • Performance Assessment for Control Systems
  • Robustness and Stability for Control Systems
  • Nonlinear systems
  • Multi-objectives control
  • Autonomous control systems for uncertain environments
  • Control strategy design, implementation and validation for autonomous robots’ platforms

Published Papers (11 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:

Editorial

Jump to: Research

3 pages, 169 KiB  
Editorial
Feasible, Robust and Reliable Automation and Control for Autonomous Systems
by Umar Zakir Abdul Hamid, Chuan Hu and Argyrios Zolotas
Electronics 2022, 11(14), 2126; https://0-doi-org.brum.beds.ac.uk/10.3390/electronics11142126 - 7 Jul 2022
Viewed by 1641
Abstract
The global market for autonomous robotics platforms has grown rapidly due to the advent of drones, mobile robots, and driverless cars, while the mass media coverage examining the progress of robotics and autonomous systems field is widespread [...] Full article
(This article belongs to the Special Issue Feasible, Robust and Reliable Automation and Control for Autonomous Systems)

Research

Jump to: Editorial

14 pages, 2578 KiB  
Article
Leader-Based Trajectory Following in Unstructured Environments—From Concept to Real-World Implementation
by Georg Nestlinger, Johannes Rumetshofer and Selim Solmaz
Electronics 2022, 11(12), 1866; https://0-doi-org.brum.beds.ac.uk/10.3390/electronics11121866 - 13 Jun 2022
Cited by 7 | Viewed by 1273
Abstract
In this paper, the problem of vehicle guidance by means of an external leader is described. The objective is to navigate a four-wheeled vehicle through unstructured environments, characterized by the lack of availability of typical guidance infrastructure like lane markings or HD maps. [...] Read more.
In this paper, the problem of vehicle guidance by means of an external leader is described. The objective is to navigate a four-wheeled vehicle through unstructured environments, characterized by the lack of availability of typical guidance infrastructure like lane markings or HD maps. The trajectory-following approach is based on an estimate of the leader’s path. For that, position measurements are stored over time with respect to an inertial frame. A new strategy is proposed to rate the significance of position measurements and ensure that a certain threshold of stored samples is not exceeded. Having an estimate of the leader path is essential to prevent the cutting-corner phenomenon and for exact path following in general. A spline-approximation technique is applied to obtain a smooth reference path for the underlying lateral and longitudinal motion controllers. For longitudinal tracking, a constant time-headway policy was implemented, to follow the leader with a constant time gap along the estimated path. The algorithm was first developed and tested in a simulation framework and then deployed in a demonstrator vehicle for validation under real operating conditions. The presented experimental results were achieved using only on-board sensors of the demonstrator vehicle, while high-accuracy differential GPS-based position measurements serve as the ground truth data for visualization. Full article
(This article belongs to the Special Issue Feasible, Robust and Reliable Automation and Control for Autonomous Systems)
►▼ Show Figures

Figure 1

18 pages, 40743 KiB  
Article
Practical Nonlinear Model Predictive Controller Design for Trajectory Tracking of Unmanned Vehicles
by Hui Pang, Minhao Liu, Chuan Hu and Nan Liu
Electronics 2022, 11(7), 1110; https://0-doi-org.brum.beds.ac.uk/10.3390/electronics11071110 - 31 Mar 2022
Cited by 4 | Viewed by 2574
Abstract
The trajectory tracking issue of unmanned vehicles has attracted much attention recently, with the rapid development and implementation of sensing, communication, and computing technologies. This paper proposes a nonlinear model predictive controller (NMPC) for the trajectory tracking application of an unmanned vehicle (UV). [...] Read more.
The trajectory tracking issue of unmanned vehicles has attracted much attention recently, with the rapid development and implementation of sensing, communication, and computing technologies. This paper proposes a nonlinear model predictive controller (NMPC) for the trajectory tracking application of an unmanned vehicle (UV). First, a two-degree-of-freedom (2-DOF) kinematics model of this UV is used to derive the desirable controller with two control variables as forward velocity and yaw angle. Next, the one-step Euler method is employed to establish the nonlinear prediction model, then a nonlinear optimization objective function is formulated to minimize the tracking errors of forward velocity and yaw angle from a preset time-varying reference road. Finally, the effectiveness of the proposed NMPC scheme is assessed under two different driving scenarios via MATLAB simulations. The simulation results confirm that the proposed NMPC scheme reveals better control accuracy and computational efficiency than the standard MPC controller under two different prescribed roads. Moreover, an outdoor field test is conducted to verify the performance of the proposed NMPC scheme, and the results show that the proposed NMPC can be applied to the real vehicle and can improve the tracking accuracy and the driving stability of trajectory tracking. Full article
(This article belongs to the Special Issue Feasible, Robust and Reliable Automation and Control for Autonomous Systems)
►▼ Show Figures

Figure 1

20 pages, 804 KiB  
Article
Automatically Learning Formal Models from Autonomous Driving Software
by Yuvaraj Selvaraj, Ashfaq Farooqui, Ghazaleh Panahandeh, Wolfgang Ahrendt and Martin Fabian
Electronics 2022, 11(4), 643; https://0-doi-org.brum.beds.ac.uk/10.3390/electronics11040643 - 18 Feb 2022
Cited by 3 | Viewed by 2419
Abstract
The correctness of autonomous driving software is of utmost importance, as incorrect behavior may have catastrophic consequences. Formal model-based engineering techniques can help guarantee correctness and thereby allow the safe deployment of autonomous vehicles. However, challenges exist for widespread industrial adoption of formal [...] Read more.
The correctness of autonomous driving software is of utmost importance, as incorrect behavior may have catastrophic consequences. Formal model-based engineering techniques can help guarantee correctness and thereby allow the safe deployment of autonomous vehicles. However, challenges exist for widespread industrial adoption of formal methods. One of these challenges is the model construction problem. Manual construction of formal models is time-consuming, error-prone, and intractable for large systems. Automating model construction would be a big step towards widespread industrial adoption of formal methods for system development, re-engineering, and reverse engineering. This article applies active learning techniques to obtain formal models of an existing (under development) autonomous driving software module implemented in MATLAB. This demonstrates the feasibility of automated learning for automotive industrial use. Additionally, practical challenges in applying automata learning, and possible directions for integrating automata learning into the automotive software development workflow, are discussed. Full article
(This article belongs to the Special Issue Feasible, Robust and Reliable Automation and Control for Autonomous Systems)
►▼ Show Figures

Figure 1

13 pages, 2131 KiB  
Article
Development and Verification of Infrastructure-Assisted Automated Driving Functions
by Martin Rudigier, Georg Nestlinger, Kailin Tong and Selim Solmaz
Electronics 2021, 10(17), 2161; https://0-doi-org.brum.beds.ac.uk/10.3390/electronics10172161 - 4 Sep 2021
Cited by 7 | Viewed by 2201
Abstract
Automated vehicles we have on public roads today are capable of up to SAE Level-3 conditional autonomy according to the SAE J3016 Standard taxonomy, where the driver is the main responsible for the driving safety. All the decision-making processes of the system depend [...] Read more.
Automated vehicles we have on public roads today are capable of up to SAE Level-3 conditional autonomy according to the SAE J3016 Standard taxonomy, where the driver is the main responsible for the driving safety. All the decision-making processes of the system depend on computations performed on the ego vehicle and utilizing only on-board sensor information, mimicking the perception of a human driver. It can be conjectured that for higher levels of autonomy, on-board sensor information will not be sufficient alone. Infrastructure assistance will, therefore, be necessary to ensure the partial or full responsibility of the driving safety. With higher penetration rates of automated vehicles however, new problems will arise. It is expected that automated driving and particularly automated vehicle platoons will lead to more road damage in the form of rutting. Inspired by this, the EU project ESRIUM investigates infrastructure assisted routing recommendations utilizing C-ITS communications. In this respect, specially designed ADAS functions are being developed with capabilities to adapt their behavior according to specific routing recommendations. Automated vehicles equipped with such ADAS functions will be able to reduce road damage. The current paper presents the specific use cases, as well as the developed C-ITS assisted ADAS functions together with their verification results utilizing a simulation framework. Full article
(This article belongs to the Special Issue Feasible, Robust and Reliable Automation and Control for Autonomous Systems)
►▼ Show Figures

Graphical abstract

25 pages, 2589 KiB  
Article
Integrated Comfort-Adaptive Cruise and Semi-Active Suspension Control for an Autonomous Vehicle: An LPV Approach
by Gia Quoc Bao Tran, Thanh-Phong Pham, Olivier Sename, Eduarda Costa and Peter Gaspar
Electronics 2021, 10(7), 813; https://0-doi-org.brum.beds.ac.uk/10.3390/electronics10070813 - 30 Mar 2021
Cited by 10 | Viewed by 2947
Abstract
This paper presents an integrated linear parameter-varying (LPV) control approach of an autonomous vehicle with an objective to guarantee driving comfort, consisting of cruise and semi-active suspension control. First, the vehicle longitudinal and vertical dynamics (equipped with a semi-active suspension system) are presented [...] Read more.
This paper presents an integrated linear parameter-varying (LPV) control approach of an autonomous vehicle with an objective to guarantee driving comfort, consisting of cruise and semi-active suspension control. First, the vehicle longitudinal and vertical dynamics (equipped with a semi-active suspension system) are presented and written into LPV state-space representations. The reference speed is calculated online from the estimated road type and the desired comfort level (characterized by the frequency weighted vertical acceleration defined in the ISO 2631 norm) using precomputed polynomial functions. Then, concerning cruise control, an LPV H2 controller using a linear matrix inequality (LMI) based polytopic approach combined with the compensation of the estimated disturbance forces is developed to track the comfort-oriented reference speed. To further enhance passengers’ comfort, a decentralized LPV H2 controller for the semi-active suspension system is proposed, minimizing the effect of the road profile variations. The interaction with cruise control is achieved by the vehicle’s actual speed being a scheduling parameter for suspension control. To assess the strategy’s performance, simulations are conducted using a realistic nonlinear vehicle model validated from experimental data. The simulation results demonstrate the proposed approach’s capability to improve driving comfort. Full article
(This article belongs to the Special Issue Feasible, Robust and Reliable Automation and Control for Autonomous Systems)
►▼ Show Figures

Figure 1

26 pages, 957 KiB  
Article
A Generic Interface Enabling Combinations of State-of-the-Art Path Planning and Tracking Algorithms
by Johannes Rumetshofer, Michael Stolz and Daniel Watzenig
Electronics 2021, 10(7), 788; https://0-doi-org.brum.beds.ac.uk/10.3390/electronics10070788 - 26 Mar 2021
Cited by 8 | Viewed by 2158
Abstract
In the development of Level 4 automated driving functions, very specific, but diverse, requirements with respect to the operational design domain have to be considered. In order to accelerate this development, it is advantageous to combine dedicated state-of-the-art software components, as building blocks [...] Read more.
In the development of Level 4 automated driving functions, very specific, but diverse, requirements with respect to the operational design domain have to be considered. In order to accelerate this development, it is advantageous to combine dedicated state-of-the-art software components, as building blocks in modular automated driving function architectures, instead of developing special solutions from scratch. However, e.g., in local motion planning and control, the combination of components is still limited in practice, due to necessary interface alignments, which might yield sub-optimal solutions and additional development overhead. The application of generic interfaces, which manage the data transfer between the software components, has the potential to avoid these drawbacks and hence, to further boost this development approach. This publication contributes such a generic interface concept between the local path planning and path tracking systems. The crucial point is a generalization of the lateral tracking error computation, based on an introduced error classification. It substantiates the integration of an internal reference path representation into the interface, to resolve the component interdependencies. The resulting, proposed interface enables arbitrary combinations of components from a comprehensive set of state-of-the-art path planning and tracking algorithms. Two interface implementations are finally applied in an exemplary automated driving function assembly task. Full article
(This article belongs to the Special Issue Feasible, Robust and Reliable Automation and Control for Autonomous Systems)
►▼ Show Figures

Figure 1

14 pages, 744 KiB  
Article
High Velocity Lane Keeping Control Method Based on the Non-Smooth Finite-Time Control for Electric Vehicle Driven by Four Wheels Independently
by Qinghua Meng, Xin Zhao, Chuan Hu and Zong-Yao Sun
Electronics 2021, 10(6), 760; https://0-doi-org.brum.beds.ac.uk/10.3390/electronics10060760 - 23 Mar 2021
Cited by 5 | Viewed by 2438
Abstract
In order to improve the output response and robustness of the lane keeping controller for the electric vehicle driven by four wheels independently (EV-DFWI), the article proposes a lane keeping controller based on the non-smooth finite-time (NoS-FT) control method. Firstly, a lane keeping [...] Read more.
In order to improve the output response and robustness of the lane keeping controller for the electric vehicle driven by four wheels independently (EV-DFWI), the article proposes a lane keeping controller based on the non-smooth finite-time (NoS-FT) control method. Firstly, a lane keeping control (LKC) model was built for the EV-DFWI. Secondly, a tracking method and error weight superposition method to track error computing for the lane keeping control based on the LKC model are proposed according to the lane line information. Thirdly, a NoS-FT controller was constructed for lane keeping. It is proved that the NoS-FT controller can stabilize the system by the direct Lyapunov method. Finally, the simulations were carried out to verify that the NoS-FT controller can keep the vehicle running in the desired lane with the straight road, constant curvature road, varied curvature road, and S-bend road. The simulation results show that the NoS-FT controller has better effectiveness than the PID controller. The contributions of this article are that two kinds of tracking error computing methods of lane keeping control are proposed to deal with different conditions, and a Non-FT lane keeping controller is designed to keep the EV-DFWI running in the desired lane suffering external disturbances. Full article
(This article belongs to the Special Issue Feasible, Robust and Reliable Automation and Control for Autonomous Systems)
►▼ Show Figures

Figure 1

38 pages, 3260 KiB  
Article
On-Line Learning and Updating Unmanned Tracked Vehicle Dynamics
by Natalia Strawa, Dmitry I. Ignatyev, Argyrios C. Zolotas and Antonios Tsourdos
Electronics 2021, 10(2), 187; https://0-doi-org.brum.beds.ac.uk/10.3390/electronics10020187 - 15 Jan 2021
Cited by 6 | Viewed by 4218
Abstract
Increasing levels of autonomy impose more pronounced performance requirements for unmanned ground vehicles (UGV). Presence of model uncertainties significantly reduces a ground vehicle performance when the vehicle is traversing an unknown terrain or the vehicle inertial parameters vary due to a mission schedule [...] Read more.
Increasing levels of autonomy impose more pronounced performance requirements for unmanned ground vehicles (UGV). Presence of model uncertainties significantly reduces a ground vehicle performance when the vehicle is traversing an unknown terrain or the vehicle inertial parameters vary due to a mission schedule or external disturbances. A comprehensive mathematical model of a skid steering tracked vehicle is presented in this paper and used to design a control law. Analysis of the controller under model uncertainties in inertial parameters and in the vehicle-terrain interaction revealed undesirable behavior, such as controller divergence and offset from the desired trajectory. A compound identification scheme utilizing an exponential forgetting recursive least square, generalized Newton–Raphson (NR), and Unscented Kalman Filter methods is proposed to estimate the model parameters, such as the vehicle mass and inertia, as well as parameters of the vehicle-terrain interaction, such as slip, resistance coefficients, cohesion, and shear deformation modulus on-line. The proposed identification scheme facilitates adaptive capability for the control system, improves tracking performance and contributes to an adaptive path and trajectory planning framework, which is essential for future autonomous ground vehicle missions. Full article
(This article belongs to the Special Issue Feasible, Robust and Reliable Automation and Control for Autonomous Systems)
►▼ Show Figures

Figure 1

18 pages, 1644 KiB  
Article
Facilitating Autonomous Systems with AI-Based Fault Tolerance and Computational Resource Economy
by Kyriakos M. Deliparaschos, Konstantinos Michail and Argyrios C. Zolotas
Electronics 2020, 9(5), 788; https://0-doi-org.brum.beds.ac.uk/10.3390/electronics9050788 - 11 May 2020
Cited by 5 | Viewed by 3486
Abstract
Proposed is the facilitation of fault-tolerant capability in autonomous systems with particular consideration of low computational complexity and system interface devices (sensor/actuator) performance. Traditionally model-based fault-tolerant/detection units for multiple sensor faults in automation require a bank of estimators, normally Kalman-based ones. An AI-based [...] Read more.
Proposed is the facilitation of fault-tolerant capability in autonomous systems with particular consideration of low computational complexity and system interface devices (sensor/actuator) performance. Traditionally model-based fault-tolerant/detection units for multiple sensor faults in automation require a bank of estimators, normally Kalman-based ones. An AI-based control framework enabling low computational power fault tolerance is presented. Contrary to the bank-of-estimators approach, the proposed framework exhibits a single unit for multiple actuator/sensor fault detection. The efficacy of the proposed scheme is shown via rigorous analysis for several sensor fault scenarios for an electro-magnetic suspension testbed. Full article
(This article belongs to the Special Issue Feasible, Robust and Reliable Automation and Control for Autonomous Systems)
►▼ Show Figures

Figure 1

28 pages, 4708 KiB  
Article
Adaptive Single Neuron Anti-Windup PID Controller Based on the Extended Kalman Filter Algorithm
by Jesus Hernandez-Barragan, Jorge D. Rios, Alma Y. Alanis, Carlos Lopez-Franco, Javier Gomez-Avila and Nancy Arana-Daniel
Electronics 2020, 9(4), 636; https://0-doi-org.brum.beds.ac.uk/10.3390/electronics9040636 - 11 Apr 2020
Cited by 13 | Viewed by 5406
Abstract
In this paper, an adaptive single neuron Proportional–Integral–Derivative (PID) controller based on the extended Kalman filter (EKF) training algorithm is proposed. The use of EKF training allows online training with faster learning and convergence speeds than backpropagation training method. Moreover, the propose adaptive [...] Read more.
In this paper, an adaptive single neuron Proportional–Integral–Derivative (PID) controller based on the extended Kalman filter (EKF) training algorithm is proposed. The use of EKF training allows online training with faster learning and convergence speeds than backpropagation training method. Moreover, the propose adaptive PID approach includes a back-calculation anti-windup scheme to deal with windup effects, which is a common problem in PID controllers. The performance of the proposed approach is shown by presenting both simulation and experimental tests, giving results that are comparable to similar and more complex implementations. Tests are performed for a four wheeled omnidirectional mobile robot. Tests show the superiority of the proposed adaptive PID controller over the conventional PID and other adaptive neural PID approaches. Experimental tests are performed on a KUKA® Youbot® omnidirectional platform. Full article
(This article belongs to the Special Issue Feasible, Robust and Reliable Automation and Control for Autonomous Systems)
►▼ Show Figures

Figure 1

Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
 
Displaying articles 1-11
Back to TopTop