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The paper presents the first classical internal model control (IMC) design in the context of railway carbody roll control. We propose a simple control approach for a recent hydraulically actuated vehicle body roll concept that offers limited carbody roll. The IMC approach addresses both preview- and nulling-type tilt setups, highlighting related benefits and limitations. The design provides a model simplification process that facilitates PI and PID-type control structures without the need for complex optimization. A simple, yet practical, tool for the industrial rail rolling stock engineer in vehicle control design is offered. Vehicle roll performance is rigorously studied on the deterministic (curving acceleration response) and stochastic (ride quality) trade off. Simulations are performed on an in-house multibody dynamics software package employing a realistic nonlinear railway vehicle model and allow to appropriately assess the performance of preview and nulling type tilt performance. The results obtained confirm that preview tilt control offers the better tilt performance as it utilizes a tilt command reference, and highlighted that nulling-type tilt performance remains at a relatively comparable level with the former.

Group Design Project (GDP) is a common education strategy in engineering. However, due to the COVID-19 pandemic, GDP cannot be fulfilled in a typical lab condition. The paper describes an example of delivering intensive hands-on, group project-based engineering course Autonomous Vehicle Dynamics and Control at Cranfield University. The project was designed to be implemented using modern simulation tools. As a result, students have not only obtained a better understanding of the engineering areas but also learned the usage of essential engineering and IT tools. The students obtained skillsets useful in modern engineering applications, where a simulation environment could improve the quality of the system before deployment and reduce a development cost.

This paper presents a novel security approach called Anomalous Resource Consumption Detection (ARCD), which acts as an additional layer of protection to detect cyberattacks in embedded systems (ESs). The ARCD approach is based on the differentiation between the predefined standard resource consumption pattern and the anomalous consumption pattern of system resource utilization. The effectiveness of the proposed approach is tested in a rigorous manner by simulating four types of cyberattacks: a denial-of-service attack, a brute-force attack, a remote code execution attack, and a man-in-the-middle attack, which are executed on a Smart PiCar (used as the testbed). A septenary tuple model consisting of seven parameters, representing the embedded system’s architecture, has been created as the core of the detection mechanism. The approach’s efficiency and effectiveness has been validated in terms of range and pattern by analyzing the collected data statistically in terms of mean, median, mode, standard deviation, range, minimum, and maximum values. The results demonstrated the potential for defining a standard pattern of resource utilization and performance of the embedded system due to a significant similarity of the parameters’ values at normal states. In contrast, the attacked cases showed a definite, observable, and detectable impact on resource consumption and performance of the embedded system, causing an anomalous pattern. Thus, by merging these two findings, the ARCD approach has been developed. ARCD facilitates building secure operating systems in line with the ES’s capabilities. Furthermore, the ARCD approach can work along with existing countermeasures to augment the security of the operating system layer.

This paper presents a unique security approach for detecting cyber-attacks against embedded systems (ESs). The proposed approach has been shaped within an architectural framework called anomalous resource consumption detection (ARCD). The approach’s detection mechanism detects cyber-attacks by distinguishing anomalous performance and resource consumption patterns from a pre-determinable reference model. The defense mechanism of this approach acts as an additional layer of protection for ESs. This technique’s effectiveness was previously evaluated statistically, and in this paper, we tested this approach’s efficiency computationally by using the support-vector machine algorithm. The datasets were generated and collected based on a testbed model, where it was run repeatedly under different operation conditions (normal cases (Rs) versus attacked cases). The executed attack scenarios are 1) denial-of-service (DoS); 2) brute force (BF); and 3) remote code execution (RCE), and man-in-the-middle (MITM). A septenary tuple model, which consists of seven determinants that are analyzed based on seven statistical criteria, is the core of the detection mechanism. The prediction accuracy in terms of classifying anomalous patterns compared to normal patterns based on the confusion matrix revealed promising results, proving this approach’s effectiveness, where the final results confirmed very high prediction accuracies in terms of distinguishing anomalous patterns from the typical patterns. Integrating the ARCD concept into an operating system’s functionality could help software developers augment the existing security countermeasures of ESs. Adopting the ARCD approach will pave the way for software engineers to build more secure operating systems in line with the embedded system’s capabilities, without depleting its resources.

Diagnosis and prognosis of failures for aircrafts’ integrity are some of the most important regular functionalities in complex and safety-critical aircraft structures. Further, development of failure diagnostic tools such as Non-Destructive Testing (NDT) techniques, in particular, for aircraft composite materials, has been seen as a subject of intensive research over the last decades. The need for diagnostic and prognostic tools for composite materials in aircraft applications rises and draws increasing attention. Yet, there is still an ongoing need for developing new failure diagnostic tools to respond to the rapid industrial development and complex machine design. Such tools will ease the early detection and isolation of developing defects and the prediction of damages propagation; thus allowing for early implementation of preventive maintenance and serve as a countermeasure to the potential of catastrophic failure. This paper provides a brief literature review of recent research on failure diagnosis of composite materials with an emphasis on the use of active thermography techniques in the aerospace industry. Furthermore, as the use of unmanned aerial vehicles (UAVs) for the remote inspection of large and/or difficult access areas has significantly grown in the last few years thanks to their flexibility of flight and to the possibility to carry one or several measuring sensors, the aim to use a UAV active thermography system for the inspection of large composite aeronautical structures in a continuous dynamic mode is proposed., Thermosense: Thermal Infrared Applications XLIII, April 12-16, 2021, Online Only, United States, Series: Proceedings of SPIE

Unmanned Aerial Vehicles (UAVs) that can fly around an aircraft carrying several sensors, e.g., thermal and optical cameras, to inspect the parts of interest without removing them can have significant impact in reducing inspection time and cost. One of the main challenges in the UAV based active InfraRed Thermography (IRT) inspection is the UAV’s unexpected motions. Since active thermography is mainly concerned with the analysis of thermal sequences, unexpected motions can disturb the thermal profiling and cause data misinterpretation especially for providing an automated process pipeline of such inspections. Additionally, in the scenarios where post-analysis is intended to be applied by an inspector, the UAV’s unexpected motions can increase the risk of human error, data misinterpretation, and incorrect characterization of possible defects. Therefore, post-processing is required to minimize/eliminate such undesired motions using digital video stabilization techniques. There are number of video stabilization algorithms that are readily available, however, selecting the best suited one is also challenging. Therefore, this paper evaluates video stabilization algorithms to minimize/mitigate undesired UAV motion and proposes a simple method to find the best suited stabilization algorithm as a fundamental first step towards a fully operational UAV-IRT inspection system.

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&ndash, 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.

The industrial norm of tilting high speed trains, nowadays, is that of Precedence tilt (also known as Preview tilt). Precedence tilt, although succesfull as a concept, tends to be complex (mainly due to the signal interconnections between vehicles and the advanced signal processing required for monitoring). Research studies of early prior to that of precedence tilt schemes, i.e. the so-called Nulling-type schemes, utilized local-per-vehicle signals to provide tilt action (this was essentially a typical disturbance rejection-scheme) but suffered from inherent delays in the control). Nulling tilt may still be seen as an important research aim due to the simple nature and most importantly due to the more straightforward fault detection compared to precedence schemes. The work in this paper presents a substantial extension conventional to robust H∞ mixed sensitivity nulling tilt control in literature. A particular aspect is the use of optimization is used in the design of the robust controller accompanied by rigorous investigation of the conflicting deterministic/stochastic local tilt trade-off.

The research and development of autonomous vehicle has entered the era of commercialization. While the vehicle self-driving technology has been growing rapidly, the validation for autonomous vehicle in terms of driving model, human factor model and traffic model is still maturing. Most of previous infrastructures are mainly focused on validation of those three models separately resorting either on real driving test at physical infrastructure or software simulation in virtualized infrastructure. However, neither the real driving test can cover all possible scenarios of autonomous driving and human factors, nor the virtualized software simulation can generate a feasible model for practical on/off-road driving. Furthermore, future autonomous transport in smart cities requires comprehensive validation. In order for autonomous vehicles to meet the autonomous transport in such complex traffic environment, an integrated testing and simulation infrastructure has been built targeting the systematic validation for autonomous vehicles: the Multi-User Environment for Autonomous Vehicle Innovation (MUEAVI). A preliminary investigation of a new autonomous vehicle validation infrastructure that can serve a multitude of research projects for smart city is presented.

The paper presents a two-degree-of-freedom control method that exploits the spring dynamics of a magnetic coupling for electromechanical torque transfer. Initially, through analysis of a dynamic model and linearisation, it is shown that control parameters designed by previous reported methods can be too aggressive, and that a broader performance envelope can be obtained by linearising at around 75% of the pull-out torque. Secondly, the paper presents a method of identifying the spring dynamics without measuring the load-side position of the coupling. Finally, input shaping and the identified parameters are employed to provide a new controller design methodology. The internal model principle is used along with the proposed linearisation scheme to construct a feed-forward/feedback control scheme whose parameters are calculated to provide desired tracking and disturbance rejection characteristics. Experimental results show excellent reference tracking and load torque disturbance rejection performance, whilst reducing the possibility of pole-slipping resulting from aggressive control action.

We present robust dynamic resource allocation mechanisms to allocate application resources meeting Service Level Objectives (SLOs) agreed between cloud providers and customers. In fact, two filter-based robust controllers, i.e. H-infinity filter and Maximum Correntropy Criterion Kalman filter (MCC-KF), are proposed. The controllers are self-adaptive, with process noise variances and covariances calculated using previous measurements within a time window. In the allocation process, a bounded client mean response time (mRT) is maintained. Both controllers are deployed and evaluated on an experimental testbed hosting the RUBiS (Rice University Bidding System) auction benchmark web site. The proposed controllers offer improved performance under abrupt workload changes, shown via rigorous comparison with current state-of-the-art. On our experimental setup, the Single-Input-Single-Output (SISO) controllers can operate on the same server where the resource allocation is performed; while Multi-Input-Multi-Output (MIMO) controllers are on a separate server where all the data are collected for decision making. SISO controllers take decisions not dependent to other system states (servers), albeit MIMO controllers are characterized by increased communication overhead and potential delays. While SISO controllers offer improved performance over MIMO ones, the latter enable a more informed decision making framework for resource allocation problem of multi-tier applications., 16 pages

The paper introduces a novel indicator of urban built form termed Form Signature. Generic models of four urban built forms are developed including pavilion, terrace, court and a newly introduced tunnel-court which are used to compare and contrast their land-use performance and density characteristics. Selecting plot ratio and site coverage as the most popular and appropriate density indicators, the simultaneous relationship to each of the considered urban built forms is shown graphically with the number of storeys, plan depth and cut-off angle as the main variables of interest. For existing urban areas, the resulting graphs provide a robust tool for statistical analysis of contexts such as climate, economy, energy and crime potential and establish their relationship to form and density. To show the value of the contribution, analysing 32 case studies from 19 cities in different global locations showed an insignificant relationship between climate and form/density of urban areas, while practically depicting that urban areas built in court form acquire higher cut-off angle compared to terrace form urban developments. For the planning of future urban areas, the resulting relationships provide an application-oriented urban planning tool to facilitate the most effective land-use method in order to achieve sustainable cities. Examples showing the potential of the tool for future statistical energy and social analysis of urban areas are provided. Finally, a relative comparison shows that the newly-introduced tunnel-court form achieves the greatest density while pavilion achieves the lowest.

A novel design of amphibious UAV with a swimming-ring shaped floater that can inflate before landing and deflate after taking off is presented. An air pump system is developed to control the floater and is integrated in the whole flight control system. The mechanism of such system is discussed, while simulations in MATLAB and Simulink carried out for a UAV with simple missions and trajectories are shown. Results illustrate the feasibility of using the proposed design within the remit of water landing UAVs.

Nulling-type tilt control in tilting railway vehicles, i.e. Single-Input–Single-Output (SISO) control using non-precedent sensor information for lateral acceleration and tilt angle, suffers from performance limitations due to the system's non-minimum phase characteristics [Zolotas, A. C., & Goodall, R. M. (2000). Advanced control strategies for tilting railway vehicles. UKACC international conference on control, University of Cambridge, Cambridge, UK. 6p., ISBN: 0-85296-240-1.]. From an engineering point of view, this is due to the suspension's dynamic interactions and the sensor information used for feedback control. This paper revisits SISO PID-based nulling-type tilt control design (hereby referred to as ‘economical tilt control’) and rigorously studies its design via optimization to improve system performance. The strong coupling between the roll and lateral dynamic modes of the vehicle body is shown and the performance limitations using conventional control highlighted. PID controllers are designed to illustrate different levels of tilt performance regarding the deterministic (curving acceleration response) and stochastic (ride quality) with the latter being a bounded constraint. With novel contribution to use of PID control in the tilt control application with rational transfer functions, particular emphasis is placed on the practical aspects of the tilt dynamics within the design framework via detailed simulation results.

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.

The paper considers the impact of Demand Side Response events on supply power profile and energy efficiency of widely distributed aggregated loads applied across commercial refrigeration systems. Responses to secondary grid frequency static DSR events are investigated. Experimental trials are conducted on a system of refrigerators representing a small retail store, and subsequently on the refrigerators of an operational superstore in the UK. Energy consumption and energy savings during 3 hours of operation, pre and post-secondary DSR, are discussed. In addition, a simultaneous secondary DSR event is realised across three operational retail stores located in different geographical regions of the UK. A Simulink model for a 3Φ power network is used to investigate the impact of a synchronised return to normal operation of the aggregated refrigeration systems post DSR on the local power network. Results show ~1% drop in line voltage due to the synchronised return to operation. An analysis of energy consumption shows that DSR events can facilitate energy savings of between 3.8% and 9.3% compared to normal operation. This is a result of the refrigerators operating more efficiently during and shortly after the DSR. The use of aggregated refrigeration loads can contribute to the necessary load-shed by 97.3% at the beginning of DSR and 27% during 30 minutes DSR, based on a simultaneous DSR event carried out on three retail stores.

Active suspensions for railway vehicles have been a topic of research for a number of decades and while their applications in service operation are limited it seems clear that they will in due course see widespread adoption. Railway suspension design is a problem of compromise on the non-trivial trade-off of ride quality vs track following (guidance), and the skyhook damping control approach has been paramount in illustrating the potential benefits. Since skyhook damping control, various advanced control studies appeared contributing to redefine the boundaries of the aforementioned trade-off. Yet there is no study on the impact of fractional order methods in the context of skyhook railway active suspensions, and in particular related to skyhook damping control. This is the area to which this paper strongly contributes. We present findings from a current project on fractional order controllers for railway vehicles active suspensions, in particular work on the effect of fractional order methods in basic skyhook damping control schemes, i.e. pure and intuitively-based skyhook. Firstly we present a brief review of conventional skyhook damping control and then proceed to a rigorous investigation of the impact of fractional order on the ride quality / track following trade-off. The relevant benefits from fractional order methods are appraised and new insights highlighted.

We present PLC-based fractional-order controller design for an industrial -oriented water tank volume control application. The system comprises input delay which is a typified characteristic in such industrial process control applications. The particular contribution of this work is on discrete fractional-order PID implementation via PLC and its application to the aforementioned realistic water tank test bed. Stability and robustness properties of fractional-order discrete PID feedback-loops for different approximation methods and orders are also shown. Fractional-order controllers are obtained for a variety of stability margin choices, and benefits of the non-integer-order controllers compared to the integer-order PID control are illustrated via simulation and experimental runs on a realistic test-bed.

The output voltage regulation problem of a PWM-based dc-dc buck converter under various sources of uncertainties and disturbances is investigated in this paper via an optimized active disturbance rejection control (ADRC) approach. Aiming to practical implementation, a new reduced-order generalized proportional integral (GPI) observer is first designed to estimate the lumped (possibly time-varying) disturbances within the dc-dc circuit. By integrating the disturbance estimation information raised by the reduced-order GPI observer into the output prediction, an optimized ADRC method is developed to achieve optimized tracking performance even in the presence of disturbances and uncertainties. It is shown that the proposed controller will guarantee the rigorous stability of the closed-loop system, for any bounded uncertainties of the circuit, by appropriately choosing the observer gains and the bandwidth factor. Experimental results illustrate that the proposed control solution is characterized by improved robustness performance against various disturbances and uncertainties compared with traditional ADRC and integral model predictive control (MPC) approaches.