Nonlinear optimal control for aircraft ground manoeuvres

Despite recent advances in flight control systems, aircraft ground manoeuvres are still conducted manually. This thesis aims to improve the efficiency and safety of airport operations by developing a real-time optimal controller forground operations, especially high-speed runway turnoff. A reliable and robust controller is able to improve airport traffic capacity and reduce runway events of incursion, excursion, and confusion. A high-fidelity fully-parameterised aircraft model is developed to capture aircraft ground dynamics. The nonlinearities enter the system via sub-models of tyres and aerodynamics. A numerical continuation method is used to compute and track steady-state solutions under the variation of parameters, providing a global picture of the system stability within a typical operation envelop. Dynamic simulations are carried out to analyse transient behaviourswhich are not captured by the bifurcation analysis. Three controllers are employed to investigate the automation of aircraft runway exit manoeuvres. An Expert Pilot Model is developed to represent manoeuvres that are manually operated by pilots. To evaluate the optimality of the proposed Expert Pilot Model (EPM), Generalised Optimal Control (GOC) is employed to numerically investigate the optimal solutions for aircraft runway exit manoeuvres. A formal solution of real-time optimal steering control problem is desired in light of the gap between the Expert Pilot Modeland Generalised Optimal Control. Therefore, Predictive Steering Control is developed based on Linear Quadratic method with lookahead, which is able to deliver near-optimal manoeuvres.</div

An investigation of a high-speed ground manoeuvre under optimal control

This paper studies the behaviour of a nonlinear aircraft model under optimal control for aircraft ground manoeuvres, specifically for high-speed runway exits. The aircraft’s behavior on the ground is captured by a fully parameterized 6-DOF nonlinear model. A pre-defined cost function is minimized using a Generalized Optimal Control (GOC) algorithm, in order to obtain an optimal control sequence for a particular manoeuvre-cost function combination. In this paper, three scenarios are investigated for a 45-degree high-speed runway exit: the first control sequence minimizes the distance between the aircraft’s CG and the runway centreline; the second maximizes the distance travelled by the aircraft during the 20 seconds of simulation time; the third minimizes tire wear. For each scenario, the GOC algorithm provides the best possible control inputs: such results provide a benchmark against which the effectiveness of future real-time controllers may be judged

Numerical investigation of aircraft high-speed runway exit using generalized optimal control

To aim at reducing aircraft turnaround time and improving airport operation efficiency, this paper considers the optimization of aircraft ground manoeuvres such as a high-speed runway exit. The aircraft on the ground is a highly nonlinear dynamical system described by a fully parameterized mathematical model. The full aircraft model used in this paper has been further developed to include combined slip tire model. An iterative simulation-based optimization algorithm known as Generalized Optimal Control is employed to investigate the optimal solution for the control input such as nose-gear steering, main-gear brakes and engine thrust. To achieve different control objectives, the cost function is defined accordingly and then minimized by GOC. The optimization results of GOC will help to explore the safety boundary of ground handling and guide the design of a real-time controller

Adaptive piecewise equivalent circuit model with SOC/SOH estimation based on extended Kalman filter

Battery modelling plays a critical role in battery management tasks. A model that provides accurate estimations of state of charge and state of heath in varying operating conditions could significantly improve the performance of battery management systems. Departing from existing literature, this paper presents a self-adaptive Piecewise Equivalent Circuit Model (PECM) based on Extended Kalman Filter (EKF). While traditional Equivalent Circuit Models (ECM) are typically parameterized and validated for a specific range of working conditions (temperature, current and etc.), PECM is able to adapt itself to any working condition in real time. Established in the form of a combination of linear and nonlinear piecewise functions, the model parameters are continuously adjusted based on the measurement of voltage, current, and temperature. Another advantage of PECM is it does not require any prior tests in the lab, for example the Open Circuit Voltage (OCV) test which is time consuming and needs to be calibrated when aged. PECM is accurate, flexible and efficient. It has been validated for different battery chemistries, duty cycles, and temperatures. Furthermore, PECM comes with the State of Charge (SOC) and State of Health (SOH) estimation, which is shown in the model validation process and the degradation study. The results demonstrate that the piecewise parameter adaptation proposed in this paper can be applied to a range of different battery chemistries and at different aged states

High quality, patient centred andcoordinated care for Alstrom syndrome: amodel of care for an ultra-rare disease

Background: Patients with rare and ultra-rare diseases make heavy demands on the resources of both health and social services, but these resources are often used inefficiently due to delays in diagnosis, poor and fragmented care. We analysed the national service for an ultra-rare disease, Alstrom syndrome, and compared the outcome and cost of the service to the standard care. Methods: Between the 9th and 26th of March 2014 we undertook a cross-sectional study of the UK Alstrom syndrome patients and their carers. We developed a semi-structured questionnaire to assess our rare patient need, quality of care and costs incurred to patients and their careers. In the UK all Alstrom syndrome patients are seen in two centres, based in Birmingham, and we systematically evaluated the national service and compared the quality and cost of care with patients’ previous standard of care. Results: One quarter of genetically confirmed Alstrom syndrome UK patients were enrolled in this study. Patients that have access to a highly specialised clinical service reported that their care is well organised, personalised, holistic, and that they have a say in their care. All patients reported high level of satisfaction in their care. Patient treatment compliance and clinic attendance was better in multidisciplinary clinic than the usual standard of NHS care. Following a variable costing approach based on personnel and consumables’ cost, our valuation of the clinics was just under £700/patient/annum compared to the standard care of £960/patient/annum. Real savings, however, came in terms of patients’ quality of life. Furthermore there was found to have been a significant reduction in frequency of clinic visits and ordering of investigations since the establishment of the national service. Conclusions: Our study has shown that organised, multidisciplinary “one stop” clinics are patient centred and individually tailored to the patient need with a better outcome and comparable cost compared with the current standard of care for rare disease. Our proposed care model can be adapted to several other rare and ultra-rare diseases

SCSONet: spatial-channel synergistic optimization net for skin lesion segmentation

In the field of computer-assisted medical diagnosis, developing medical image segmentation models that are both accurate and capable of real-time operation under limited computational resources is crucial. Particularly for skin disease image segmentation, the construction of such lightweight models must balance computational cost and segmentation efficiency, especially in environments with limited computing power, memory, and storage. This study proposes a new lightweight network designed specifically for skin disease image segmentation, aimed at significantly reducing the number of parameters and floating-point operations while ensuring segmentation performance. The proposed ConvStem module, with full-dimensional attention, learns complementary attention weights across all four dimensions of the convolution kernel, effectively enhancing the recognition of irregularly shaped lesion areas, reducing the model’s parameter count and computational burden, thus promoting model lightweighting and performance improvement. The SCF Block reduces feature redundancy through spatial and channel feature fusion, significantly lowering parameter count while improving segmentation results. This paper validates the effectiveness and robustness of the proposed SCSONet on two public skin lesion segmentation datasets, demonstrating its low computational resource requirements. https://github.com/Haoyu1Chen/SCSONet

A worldwide bibliometric analysis of malignant peripheral nerve sheath tumors from 2000 to 2022

BackgroundCurrently, malignant peripheral nerve sheath tumors (MPNST) are the subject of intense research interest. However, bibliometric studies have not been conducted in this field. The purpose of the study was to identify historical trends and presents a bibliometric analysis of the MPNST literature from 2000 to 2022.MethodsFor the bibliometric analysis, publications were retrieved from the Web of Science database based on the following search terms: [TI = (MPNST) OR TI= (malignant peripheral nerve sheath tumors) AND PY = (2000–2022)]. The following information was collected for each document: the publication trends and geographical distribution, important authors and collaboration, keyword distribution and evaluation, most popular journals, and most influential articles.ResultsWe included 1400 documents for bibliometric analysis, covering five categories: 824 articles, 17 proceedings papers, 68 letters, 402 meeting abstracts, and 89 reviews. Corrections, editorials, book chapters, data papers, publications with expressed concerns, and retractions were excluded from our research.ConclusionSince 2000, the number of publications on MPNST has continuously increased. Among all countries that contributed to the MPNST research, the USA, Japan, and China were the three most productive countries. The journal Modern Pathology has the most publications on MPNST, while those in the Cancer Research journal were the most frequently cited. The University of Texas MD Anderson Cancer Center may be a good partner to collaborate with. Recent research trends in MPNST have focused on tumorigenesis, clinical management, and predictive biomarkers