CERES :: Browsing by Author "Ignatyev, Dmitry"

Browsing by Author "Ignatyev, Dmitry"

Now showing 1 - 20 of 23

Open Access
The accuracy and computational efficiency of the Loewner framework for the system identification of mechanical systems
(MDPI, 2023-06-20) Dessena, Gabriele; Civera, Marco; Ignatyev, Dmitry; Whidborne, James F.; Zanotti Fragonara, Luca; Chiaia, Bernardino
The Loewner framework has recently been proposed for the system identification of mechanical systems, mitigating the limitations of current frequency domain fitting processes for the extraction of modal parameters. In this work, the Loewner framework computational performance, in terms of the elapsed time till identification, is assessed. This is investigated on a hybrid, numerical and experimental dataset against two well-established system identification methods (least-squares complex exponential, LSCE, and subspace state space system identification, N4SID). Good results are achieved, in terms of better accuracy than LSCE and better computational performance than N4SID.
Open Access
Advancing fault diagnosis in aircraft landing gear: an innovative two-tier machine learning approach with intelligent sensor data management
(AIAA, 2024-01-04) Kadripathi, K. N.; Ignatyev, Dmitry; Tsourdos, Antonios; Perrusquía, Adolfo
Revolutionizing aircraft safety, this study unveils a pioneering two-tier machine learning model specifically designed for advanced fault diagnosis in aircraft landing gear systems. Addressing the critical gap in traditional diagnostic methods, our approach deftly navigates the challenges of sensor data anomalies, ensuring robust and accurate real-time health assessments. This innovation not only promises to enhance the reliability and safety of aviation but also sets a new benchmark in the application of intelligent machine-learning solutions in high-stakes environments. Our method is adept at identifying and compensating for data anomalies caused by faulty or uncalibrated sensors, ensuring uninterrupted health assessment. The model employs a simulation-based dataset reflecting complex hydraulic failures to train robust machine learning classifiers for fault detection. The primary tier focuses on fault classification, whereas the secondary tier corrects sensor data irregularities, leveraging redundant sensor inputs to bolster diagnostic precision. Such integration markedly improves classification accuracy, with empirical evidence showing an increase from 95.88% to 98.76% post-imputation. Our findings also underscore the importance of specific sensors—particularly temperature and pump speed—in evaluating the health of landing gear, advocating for their prioritized usage in monitoring systems. This approach promises to revolutionize maintenance protocols, reduce operational costs, and significantly enhance the safety measures within the aviation industry, promoting a more resilient and data-informed safety infrastructure.
Open Access
A comprehensive survey of unmanned ground vehicle terrain traversability for unstructured environments and sensor technology insights
(Elsevier, 2023-09-29) Beyçimen, Semih; Ignatyev, Dmitry; Zolotas, Argyrios
This article provides a detailed analysis of the assessment of unmanned ground vehicle terrain traversability. The analysis is categorized into terrain classification, terrain mapping, and cost-based traversability, with subcategories of appearance-based, geometry-based, and mixed-based methods. The article also explores the use of machine learning (ML), deep learning (DL) and reinforcement learning (RL) and other based end-to-end methods as crucial components for advanced terrain traversability analysis. The investigation indicates that a mixed approach, incorporating both exteroceptive and proprioceptive sensors, is more effective, optimized, and reliable for traversability analysis. Additionally, the article discusses the vehicle platforms and sensor technologies used in traversability analysis, making it a valuable resource for researchers in the field. Overall, this paper contributes significantly to the current understanding of traversability analysis in unstructured environments and provides insights for future sensor-based research on advanced traversability analysis.
Open Access
Conceptual design study based on defined parameters for next-generation Martian rotorcrafts
(IEEE, 2024-05-13) Youhanna, Vishal; Felicetti, Leonard; Ignatyev, Dmitry
The remarkable achievement of NASA’s Ingenuity Helicopter has opened exciting possibilities for the future exploration of Mars, suggesting that aerobots will play a crucial role alongside rovers and landers. However, Ingenuity’s capabilities are limited by its small and relatively basic design. This limitation is primarily evident in its restricted long-range endurance and limited capacity for scientific payloads. To address these shortcomings and advance the field of Martian drone technology, this paper introduces a practical approach to optimising the Martian rotorcraft concepts within the set parameters. The primary objective of these concepts is to enhance performance, endurance, and payload capacity to meet more demanding requirements for future Martian aerobot missions. The paper addresses an essential phase in the design process—an initial sizing of rotary electric vertical takeoff and landing (eVTOL) configurations. This phase is informed by a comprehensive parametric analysis, which considers various factors affecting the performance of drones during hover (stationary flight), vertical climb (ascending flight), and forward flight. The analysis is based on the principles of simplified rotorcraft momentum theory, a foundational concept in rotorcraft engineering. These Martian drone concepts are tailored to address the more challenging mission requirements that future Martian exploration missions are likely to demand. These requirements may include extended flight durations, increased payload capacity to accommodate scientific instruments, and the ability to cover larger areas on the Martian surface. Importantly, the designs are constrained by the maximum size of the spacecraft aeroshell, ensuring that they can be safely transported to Mars within the confines of the protective aeroshell. Among the various configurations considered in this study, a tandem rotorcraft configuration emerged as the most efficient option. This configuration is expected to attain a balance between performance, endurance, and payload capacity, making it a promising choice for future Martian aerobot missions. In contrast, the analysis revealed that a conventional single main rotor configuration within the defined parameters performed poorly in meeting the requirements of the mission.
Open Access
Estimation of non-symmetric and unbounded region of attraction using shifted shape function and R-composition
(Elsevier, 2022-09-21) Li, Dongyang; Ignatyev, Dmitry; Tsourdos, Antonios; Wang, Zhongyuan
Sum-of-squares programming is widely used for region of attraction (ROA) estimations of asymptotically stable equilibrium points of nonlinear polynomial systems. However, existing methods yield conservative results, especially for non-symmetric and unbounded regions. In this study, a cost-effective approach for ROA estimation is proposed based on the Lyapunov theory and shape functions. In contrast to existing methods, the proposed method iteratively places the center of a shifted shape function (SSF) close to the boundary of the acquired invariant subset. The set of obtained SSFs yields robust ROA subsets, and R-composition is employed to express these independent sets as a single but richer-shaped level set. Several benchmark examples show that the proposed method significantly improves ROA estimations, especially for non-symmetric or unbounded ROA without a significant computational burden.
Open Access
Fault detection in aircraft flight control actuators using support vector machines
(MDPI, 2023-02-02) Grehan, Julianne; Ignatyev, Dmitry; Zolotas, Argyrios
Future generations of flight control systems, such as those for unmanned autonomous vehicles (UAVs), are likely to be more adaptive and intelligent to cope with the extra safety and reliability requirements due to pilotless operations. An efficient fault detection and isolation (FDI) system is paramount and should be capable of monitoring the health status of an aircraft. Historically, hardware redundancy techniques have been used to detect faults. However, duplicating the actuators in an UAV is not ideal due to the high cost and large mass of additional components. Fortunately, aircraft actuator faults can also be detected using analytical redundancy techniques. In this study, a data-driven algorithm using Support Vector Machine (SVM) is designed. The aircraft actuator fault investigated is the loss-of-effectiveness (LOE) fault. The aim of the fault detection algorithm is to classify the feature vector data into a nominal or faulty class based on the health of the actuator. The results show that the SVM algorithm detects the LOE fault almost instantly, with an average accuracy of 99%.
Open Access
Flettner-rotor-powered VTOL’s theoretical performances
(AIAA, 2023-06-08) Shimamune, Satoki; Ignatyev, Dmitry
The demand for VTOLs is growing rapidly. From inspection to logistics, thanks to the evolution of autonomous technology. However, most of the fields remain just possibilities rather than actual usage cases due to the limited flight range, wall interaction, noise and instability of the aircraft. Alleviating an instability is especially an important key to achieve a reliable aerial system. One reason of instability is due to the limited four degrees of freedom. (i.e. VTOLs have to tilt to move horizontally) In this paper, a Flettner-force-powered VTOL that has sixdegrees of freedom, called Horizonist, is proposed and the stability of Horizonist is discussed in comparison to the conventional. (Horizonist is filed as a patent in Japan (issued as JP6938005) and PCT) The performances are evaluated in terms of settling time and power consumption against various inputs and a wind.
Open Access
Futuristic Martian aerobot design
(2022-08-26) Youhanna, Vishal; Ignatyev, Dmitry; Felicetti, Leonard
NASA’s Ingenuity Helicopter has proved that flight is possible on Mars with its ingenious yet elementary design, but it lacks long-range endurance and the capacity to carry any dedicated scientific instruments. In this paper, we propose a preliminary study for an innovative development in the series of Martian drones. The Futuristic Mars Aerobot Design (FuMAD) proposes a foldable winged drone based on Ingenuity’s rotors design for enhancing long-range endurance and payload capacity.
Open Access
Incremental nonlinear dynamic inversion with sparse online Gaussian processes adaptation for partially unknown systems
(IEEE, 2022-08-01) Ignatyev, Dmitry; Tsourdos, Antonios
Sensor-based Incremental control is a recently developed family of techniques with a reduced dependency on a plant model. This approach uses measurements or estimates of current state derivatives and actuator states to linearize the dynamics with respect to the previous time moment. However, in such a formulation, the control system is sensitive to the quality of measurements or estimations. The presence of uncertainties caused by unforeseen malfunctions in measurement and/or actuation systems could provoke drastic performance degradation. The paper proposes a sensor-based Incremental Nonlinear Dynamic Inversion (INDI) control algorithm augmented with Budgeted Sparse Online Gaussian Processes Adaptation for the compensation of unknown system behaviour. INDI performs quite efficiently under design conditions. Meanwhile, GP-based direct adaptation provides not only long-term dependency learning but also noise signal filtering. The efficiency of the proposed approach is demonstrated with a longitudinal motion of a missile.
Open Access
Integrated compact electrically powered and signaled actuation systems
(AIAA, 2022-06-20) Wang, I-Tsun; Ignatyev, Dmitry; Inalhan, Gokhan; Collins, Andrew; Cheng, Szuyu; Stephen, Shirley
One of the key challenges in enabling More Electric Aircraft is the development of electrically powered servos that meet or exceed the performance, packaging, weight, and cost of a hydraulic fly-by-wire servo. This paper introduces an innovative Electro-Hydrostatic Actuator that outperforms the existing solutions in terms of mass, size and energy efficiency. The innovative design features hydraulic regeneration when the commanded movement is aligned with the direction of external force. This new feature helps to decrease energy consumption. The high efficiency of the actuator prototype is confirmed by simulation with a verified MATLAB/Simulink model. Simulations also manifest that the proposed actuator has improved phase and gain margins as compared to existing solutions.
Open Access
A Loewner-based system identification and structural health monitoring approach for mechanical systems
(Wiley, 2023-04-18) Dessena, Gabriele; Civera, Marco; Zanotti Fragonara, Luca; Ignatyev, Dmitry; Whidborne, James F.
Data-driven structural health monitoring (SHM) requires precise estimates of the target system behaviour. In this sense, SHM by means of modal parameters is strictly linked to system identifcation (SI). However, existing frequency-domain SI techniques have several theoretical and practical drawbacks. This paper proposes using an input-output system identifcation technique based on rational interpolation, known as the Loewner framework (LF), to estimate the modal properties of mechanical systems. Pioneeringly, the Loewner framework mode shapes and natural frequencies estimated by LF are then applied as damage-sensitive features for damage detection. To assess its capability, the Loewner framework is validated on both numerical and experimental datasets and compared to established system identification techniques. Promising results are achieved in terms of accuracy and reliability.
Open Access
Low-cost multi-object positioning system with optical sensor fusion
(AIAA, 2023-01-19) Pashchapur, Ravi Ashok; Chen, Yuxi; Ignatyev, Dmitry
Indoor position estimation of any moving objects with the aid of integration of multiple sensors such as optical, radio, and ultrasonic is an ongoing field of research. Although, commercial companies like VICON and OptiTrack provides the higher precision indoor positioning by using custom design optical sensors, but not every teaching or research institute can afford them because of the cost metric. To overcome this problem, an affordable low-cost solution for object tracking using multiple low-cost cameras is provided in this paper. The object tracking system introduced in this paper uses cameras to track active markers such as LEDs and estimate the coordinates of these LEDs with less than 0.15 meters of error in all the axes. The VICON camera system setup is used to opt ground truth measurements which later utilized for error estimation of the low-cost object tracking system.
Open Access
Non-linear control of a quadrotor with actuator delay
(AIAA, 2024-01-04) Kartal, Muhammed R.; Ignatyev, Dmitry; Zolotas, Argyrios
During the last decade, Unmanned Aerial Vehicles (UAVs) gained significant interest for use in various application domains such as monitoring/surveillance, freight/cargo shipping, and agriculture spraying. Developing such vehicle platforms requires the utilization of robust control approaches to maintain stable and appropriate maneuvering capabilities, as well as to address system uncertainty such as payload variation or dynamic variations (e.g., spraying drones are affected by such uncertainty). Moreover, due to the rotor-based structure, rotorcraft UAVs are quite vulnerable to UAV systems control input signal delay. In terms of maintaining a robust approach for a rotorcraft UAV, it is essential to provide stability against UAV systems control input signal delay. This paper makes an analysis throughout to improve control efficiency against UAV systems control input signal delay. Through investigation and improved fault rejection, three controlling algorithms were designed and applied. The analysis focused on three different scenarios. Insights are discussed within the remit of command tracking performance with UAV systems control input signal delay.
Open Access
Parametric analysis of battery-electric rotorcraft configurations to fly on Mars
(Council of European Aerospace Societies (CEAS), 2023-07-13) Youhanna, Vishal; Felicetti, Leonard; Ignatyev, Dmitry
The success of NASA’s Ingenuity Helicopter promises that the future exploration of Mars will include aerobots in line with rovers and landers. However, Ingenuity lacks long-range endurance and scientific payload capacity because of its small and elementary design. In the series of optimised Martian drone concepts development, we introduced in this paper - an initial sizing of rotary eVTOL design configurations based on the performed parametric analysis for hover and vertical climb using simplified rotorcraft momentum theory, for a set of more challenging requirements for a Martian aerobot mission and sized to fit into the maximum spacecraft aeroshell limit. A tandem rotor configuration was found to be the most efficient configuration, whereas a conventional single main rotor configuration with small diameters manifested the poorest performance.
Open Access
Parametric analysis of rotary VTOL aerobot design configurations to fly on Titan
(International Astronautical Federation (IAF), 2024-10-18) Youhanna, Vishal; Felicetti, Leonard; Ignatyev, Dmitry
The exploration of Titan, Saturn’s largest moon, presents significant aerodynamic challenges due to its dense atmosphere and low gravity, necessitating specialised rotorcraft designs. This study conducts a parametric analysis of multiple rotary Vertical Takeoff and Landing (VTOL) aerobot configurations, including conventional helicopters, coaxial systems, tandem rotorcraft, quadcopters, and hexacopters, with a focus on performance in Titan's environment. Using simplified momentum theory, the power consumption and operational efficiency of these rotorcraft are evaluated across key flight phases such as vertical climb, hover, and forward flight. The analysis highlights that hexacopter configurations are the most power-efficient during vertical ascent and hover for smaller rotor diameters, whereas conventional helicopter designs excel in forward flight for larger rotor sizes. The study also utilises Battery Mass Fraction (BMF) calculations to assess the energy requirements for various flight segments, offering valuable insights into the energy-efficient design of rotorcraft for Titan exploration. This research establishes a foundational framework for optimising rotorcraft design in extraterrestrial environments, providing critical data for future missions aimed at exploring Titan’s surface and atmosphere.
Open Access
Predicting autonomous vehicle navigation parameters via image and image-and-point cloud fusion-based end-to-end methods
(IEEE, 2022-10-13) Beycimen, Semih; Ignatyev, Dmitry; Zolotas, Argyrios
This paper presents a study of end-to-end methods for predicting autonomous vehicle navigation parameters. Image-based and Image & Lidar points-based end-to-end models have been trained under Nvidia learning architectures as well as Densenet-169, Resnet-152 and Inception-v4. Various learning parameters for autonomous vehicle navigation, input models and pre-processing data algorithms i.e. image cropping, noise removing, semantic segmentation for image data have been investigated and tested. The best ones, from the rigorous investigation, are selected for the main framework of the study. Results reveal that the Nvidia architecture trained Image & Lidar points-based method offers the better results accuracy rate-wise for steering angle and speed.
Open Access
Preliminary design exploration of prospective multirotor aerobots
(ICAS, 2024-09-30) Youhanna, Vishal; Felicetti, Leonard; Ignatyev, Dmitry
The groundbreaking success of NASA's Ingenuity Helicopter has spurred immense potential for Martian exploration, emphasizing the pivotal role of aerobots alongside rovers and landers. However, the helicopter's limitations, stemming from its compact and simplistic design, are apparent in its restricted long-range endurance and payload capacity. This paper suggests a feasible optimisation approach for Martian rotorcraft concepts while addressing constraints and progressing Martian drone technology. The key focus lies in improving performance to meet the evolving demands of forthcoming Martian aerobot missions. Based on a comprehensive parametric analysis rooted in simplified rotorcraft momentum theory, this study focuses on power requirements of rotorcrafts with single, coaxial, tandem, quad and hexa rotors for hover, vertical climb, and forward flight segments. Modified to meet more demanding mission criteria, these designs are limited by the spacecraft aeroshell's maximum size for safe transport to Mars. Among the considered configurations, the hexacopter emerged as the most efficient choice, offering a balance between performance, endurance, and payload capacity, while a conventional single main rotor configuration fell short within the specified parameters.
Open Access
Project-based learning course design for multi-agent autonomy using quadrotors
(Elsevier BV, 2024-09-05) Lee, Hae-In; Ignatyev, Dmitry; Shin, Hyo-Sang; Tsourdos, Antonios
This paper proposes a project-based learning course utilising multiple quadrotors, aiming to solidify and amplify technical knowledge and develop critical thinking capabilities. An engineering problem is provided as a surveillance mission with multiple quadrotors autonomously searching, detecting, and tracking ground vehicles. The course covers all stages of multi-agent autonomy development, from identifying system requirements, designing software and hardware, to conducting demonstrations in a drone flying arena. During the course, students improve their ability to critically formulate, solve and evaluate engineering problems as well as gain and apply technical knowledge in all aspects of autonomy such as flight dynamics, control, navigation, guidance, task allocation, situational awareness and communication. The paper details the problem design, course timeline, outcomes, and key lessons learnt from the course.
Open Access
Return: group design project for pin-point landing demonstrator using drone technologies
(Elsevier, 2024) Felicetti, Leonard; Ignatyev, Dmitry; Grustan, Enric; Tsourdos, Antonios
In a rapidly changing world, engineers must identify societal needs, solve problems with ingenuity, and create new knowledge. While conventional taught-based courses provide a solid foundation of knowledge, they often fall short in stimulating creative thinking, translating theoretical knowledge into real-world solutions, and fostering leadership and teamwork. This paper proposes a project-based learning course designed to solidify and amplify the technical knowledge gained in preceding taught-based modules while developing essential soft skills. The course covers various stages of designing a reusable launcher-like demonstrator, aiming to simulate take-of and pinpoint landing operations using drone technology. This involves identifying system requirements and designing both software and hardware components. Throughout the course, students enhance their ability to critically formulate, solve, and evaluate engineering problems. They gain and apply technical knowledge in all aspects of drone technology, including fight dynamics, control, navigation, guidance, situational awareness, and communication. Additionally, students explore key aspects of systems engineering practices, risk management, and time management. This paper details the problem design, course timeline, outcomes and key lessons learned from the course.
Open Access
Safe online learning for nonlinear dynamical systems using control contraction metrics
(Cranfield University, 2023-03) Osborne, Matthew; Shin, Hyo-Sang; Ignatyev, Dmitry; Tsourdos, Antonios
This thesis aims to develop an online learning framework for a military fixed-wing aircraft that can adapt a control policy to unforeseen changes in the airframe’s flight dynamics. This is an active area of research and a significant challenge for high dimensional non linear systems due to the inherent safety risks and computational challenges of solving exponential time algorithms. The research achieves this aim by providing an extensive survey of safe online learn ing approaches for nonlinear systems by assessing each technique with the aid of key performance metrics. Two critical performance metrics are the reliability and time com plexity of the approach taken. To support the survey a benchmarking study of salient techniques provides further evidence to support the findings of the literature survey to identify promising avenues of research. A generic safe learning process is defined and a convex optimisation learning pipeline is developed to handle nonlinear system identification and online controller synthesis via control contraction metrics. The developed pipeline is applied to a longitudinal simulation of an F-16 aircraft using high-fidelity wind tunnel data. The gap in knowledge around the application of control contraction metrics to aircraft designed to meet flying qualities requirements based on linear time invariant theory is bridged. A novel cascaded two loop algorithm is developed to explicitly place the eigenvalues of the inner and outer loop of a differential feedback controller. Further a parameterisa tion of a robust controller is shown to better optimise the performance relative to flying qualities specifications. Conditions for a hybrid linear sum of controllers is shown to provide a stability guarantee for a mixed controller that enables a performance trade-off of each approach. The performance of the developed controllers is demonstrated on six damaged aircraft profiles to assess the robustness and transient characteristics for each method based on a forty second flight trajectory. The variation in nonlinear damage profiles illustrates the limitations of a linear ap proximating function for three nonlinear deviations. We show that the robust quadratic regulator controller generates a smoother transient response compared to the exponential contraction controllers. The two-loop contraction metric controller improves the rise-time performance compared to a single loop but is less robust to damage variations. The out come of the research is a greater understanding of the application of contraction-based controllers and the effect of tuning parameters for a robust controller with potential for a reinforcement learning algorithm. Further a method to hybridise control policies is proposed and a loop shaping method using contraction based linear matrix inequalities developed with potential application to cascaded systems.