1,721,005 research outputs found
Unmanned aerial vehicles as an efficient platform to enable agriculture's digital future
No full textIgnatyev, Dmitry I. - Associate SupervisorThe potential for Unmanned Aerial Vehicles to revolutionise agriculture,
particularly small-scale farms, is enormous. Today, most agriculture UAVs are
bulky, expensive, and primarily designed for heavy-lift applications, making them
unaffordable for most small-scale farmers. Despite the availability of smaller
UAVs, they were not designed for agricultural purposes, and have limited
endurance. This project presents an innovative solution that involves integration
of cylindrical Li-ion cells into the multirotor’s airframe structure, thereby cost-
effectively enhancing endurance. Through the proposed engineering design
approach, a prototype UAV is built and tested, demonstrating a significant
endurance improvement over similarly sized vehicles powered by LiPo batteries.
This design presents a budget friendly solution that could enable small-scale
farmers to take advantage of affordable UAV technology.MSc by Research in Aerospac
Sparse online Gaussian process adaptation for incremental backstepping flight control
Full text linkPresence of uncertainties caused by unforeseen malfunctions in actuation or measurement systems or changes in aircraft behaviour could lead to aircraft loss-of-control during flight. This paper considers sparse online Gaussian Processes (GP) adaptive augmentation for Incremental Backstepping (IBKS) flight control. IBKS uses angular accelerations and control deflections to reduce the dependency on the aircraft model. However, it requires knowledge of the relationship between inner and outer loops and control effectiveness. Proposed indirect adaptation significantly reduces model dependency. Global uniform ultimate boundness is proved for the resultant GP adaptive IBKS. Conducted research shows that if the input-affine property is violated, e.g., in severe conditions with a combination of multiple failures, the IBKS can lose stability. Meanwhile, the proposed sparse GP-based estimator provides fast online identification and the resultant controller demonstrates improved stability and tracking performance.Aerospace Science and Technolog
Two-layer adaptive augmentation for incremental backstepping flight control of transport aircraft in uncertain conditions
Full text linkPresence of uncertainties caused by unforeseen malfunctions in actuation system or changes in aircraft behaviour could lead to aircraft loss-of-control during flight. The paper presents Two-Layer Adaptive augmentation for Incremental Backstepping (TLA-IBKS) control algorithm designed for a large transport aircraft. IBKS uses angular accelerations and current control deflections to reduce the dependency on the aircraft model. However, it requires knowledge of control effectiveness. The proposed technique is capable to detect possible failures for an overactuated system. At the first layer, the system performs monitoring of a combined effectiveness and detects possible failures via an innovation process. If a problem is detected the algorithm initiates the second-layer algorithm for adaptation of effectiveness of individual control effectors. Filippov generalization for nonlinear differential equations with discontinuous right-hand sides is utilized to develop Lyapunov based tuning function adaptive law for the second layer adaptation and to prove uniform asymptotic stability of the resultant closed-loop system. Conducted simulation manifests that if the input-affine property of the IBKS is violated, e.g., in severe conditions with a combination of multiple failures, the IBKS can lose stability. Meanwhile, the proposed TLA-IBKS algorithm demonstrates improved stability and tracking performance
A Loewner-based system identification and structural health monitoring approach for mechanical systems
Full text linkData-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.Engineering and Physical Sciences Research Council (EPSRC): 2277626Structural Control and Health Monitorin
The Accuracy and Computational Efficiency of the Loewner Framework for the System Identification of Mechanical Systems
Full text linkThe 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
Damping identification sensitivity in flutter speed estimation
Full text linkData supporting this study (− method MATLAB implementation) are openly available from the Zenodo Repository at https://doi.org/10.5281/zenodo.15176140. Furthermore, this study used existing authors’ data made available under licence at https://doi.org/10.5281/zenodo.11635814 and derived from the following resource available in the public domain: [11].Predicting flutter remains a key challenge in aeroelastic research, with certain models relying on modal parameters, such as natural frequencies and damping ratios. These models are particularly useful in early design stages or for the development of small Unmanned Aerial Vehicles (maximum take-off mass below 7 kg). This study evaluates two frequency-domain system identification methods, Fast Relaxed Vector Fitting (FRVF) and the Loewner Framework (LF), for predicting the flutter onset speed of a flexible wing model. Both methods are applied to extract modal parameters from Ground Vibration Testing data, which are subsequently used to develop a reduced-order model with two degrees of freedom. The results indicate that FRVF- and LF-informed models provide reliable flutter speed, with predictions deviating by no more than 3% (FRVF) and 5% (LF) from the N4SID-informed benchmark. The findings highlight the sensitivity of flutter speed predictions to damping ratio identification accuracy and demonstrate the potential of these methods as computationally efficient alternatives for preliminary aeroelastic assessments.Engineering and Physical Sciences Research Council (EPSRC)The authors from Cranfield University disclosed receipt of the following financial support for the research, authorship, and/or publication of this article. This work was supported by the Engineering and Physical Sciences Research Council (EPSRC) [grant number 2277626]. The third author is supported by the Centro Nazionale per la Mobilità Sostenibile (MOST–Sustainable Mobility Center), Spoke 7 (Cooperative Connected and Automated Mobility and Smart Infrastructures), Work Package 4 (Resilience of Networks, Structural Health Monitoring and Asset Management).Vibratio
Conceptual Design of Martian Aerial Robots
No full textThis thesis addresses the design and optimisation of rotary Vertical Take-Off and
Landing (VTOL) aerobots for Mars exploration. Current surface exploration
robots, such as rovers and landers, are constrained by their limited mobility in
accessing Mars’ diverse and rugged terrain. To overcome these challenges, this
research investigates the feasibility and performance of aerobots as a
complementary solution, building on NASA's Ingenuity Helicopter technology
demonstrator.
The research focuses on overcoming the engineering challenges posed by Mars'
thin atmosphere, low gravity, and extreme environmental conditions. A structured
framework is developed to systematically integrate environmental constraints and
mission-specific requirements into the aerobot design process. Central to the
study is the adaptation of helicopter momentum theory for Martian conditions,
providing a theoretical basis for estimating power consumption and rotorcraft
performance during key flight phases, including hover, vertical climb, and forward
flight. Following the theoretical groundwork, a parametric analysis evaluates
several rotorcraft configurations such as single-rotor, dual, quadcopter, and
hexacopter, focusing on power efficiency, lift capacity, and operational feasibility.
Among the configurations analysed, hexacopters demonstrate superior stability,
redundancy, and power efficiency, making them the most promising design for
Martian missions.
The research also develops practical design variants for the proposed aerobots,
addressing deployment challenges such as packaging within spacecraft
aeroshells through the implementation of foldable rotor systems. These
innovations ensure that the aerobots meet the spatial constraints of Mars
exploration missions while maximising performance. The findings from this
research provide a foundation for future Mars aerobot development, with
recommendations for further computational modelling and experimental
validation to enhance reliability in mission-critical applications.PhD in Aerospac
Safe online learning for nonlinear dynamical systems using control contraction metrics
No full textThis 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.Engineering and Physical Sciences Research Council (EPSRC)PhD in Manufacturin
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
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