Conflict resolution algorithms for optimal trajectories in presence of uncertainty

Mención Internacional en el título de doctorThe objective of the work presented in this Ph.D. thesis is to develop a novel method to address the aircraft-obstacle avoidance problem in presence of uncertainty, providing optimal trajectories in terms of risk of collision and time of flight. The obstacle avoidance maneuver is the result of a Conflict Detection and Resolution (CD&R) algorithm prepared for a potential conflict between an aircraft and a fixed obstacle which position is uncertain. Due to the growing interest in Unmanned Aerial System (UAS) operations, CD&R topic has been intensively discussed and tackled in literature in the last 10 years. One of the crucial aspects that needs to be addressed for a safe and efficient integration of UAS vehicles in non-segregated airspace is the CD&R activity. The inherent nature of UAS, and the dynamic environment they are intended to work in, put on the table of the challenges the capability of CD&R algorithms to handle with scenarios in presence of uncertainty. Modeling uncertainty sources accurately, and predicting future trajectories taking into account stochastic events, are rocky issues in developing CD&R algorithms for optimal trajectories. Uncertainty about the origin of threats, variable weather hazards, sensing and communication errors, are only some of the possible uncertainty sources that make jeopardize air vehicle operations. In this work, conflict is defined as the violation of the minimum distance between a vehicle and a fixed obstacle, and conflict avoidance maneuvers can be achieved by only varying the aircraft heading angle. The CD&R problem, formulated as Optimal Control Problem (OCP), is solved via indirect optimal control method. Necessary conditions of optimality, namely, the Euler-Lagrange equations, obtained from calculus of variations, are applied to the vehicle dynamics and the obstacle constraint modeled as stochastic variable. The implicit equations of optimality lead to formulate a Multipoint Boundary Value Problem (MPBVP) which solution is in general not trivial. The structure of the optimality trajectory is inferred from the type of path constraint, and the trend of Lagrange multiplier is analyzed along the optimal route. The MPBVP is firstly approximated by Taylor polynomials, and then solved via Differential Algebra (DA) techniques. The solution of the OCP is therefore a set of polynomials approximating the optimal controls in presence of uncertainty, i.e., the optimal heading angles that minimize the time of flight, while taking into account the uncertainty of the obstacle position. Once the obstacle is detected by on-board sensors, this method provide a useful tool that allows the pilot, or remote controller, to choose the best trade-off between optimality and collision risk of the avoidance maneuver. Monte Carlo simulations are run to validate the results and the effectiveness of the method presented. The method is also valid to address CD&R problems in presence of storms, other aircraft, or other types of hazards in the airspace characterized by constant relative velocity with respect to the own aircraft.L’obiettivo del lavoro presentato in questa tesi di dottorato è la ricerca e lo sviluppo di un nuovo metodo di anti collisione velivolo-ostacolo in presenza di incertezza, fornendo traiettorie ottimali in termini di rischio di collisione e tempo di volo. La manovra di anticollisione è il risultato di un algoritmo di detezione e risoluzione dei conflitti, in inglese Conflict Detection and Resolution (CD&R), che risolve un potenziale conflitto tra un velivolo e un ostacolo fisso la cui posizione è incerta. A causa del crescente interesse nelle operazioni che coinvolgono velivoli autonomi, anche definiti Unmanned Aerial System (UAS), negli ultimi 10 anni molte ricerche e sviluppi sono state condotte nel campo degli algoritmi CD&R. Uno degli aspetti cruciali per un’integrazione sicura ed efficiente dei velivoli UAS negli spazi aerei non segregati è l’attività CD&R. La natura intrinseca degli UAS e l’ambiente dinamico in cui sono destinati a lavorare, impongono delle numerose sfide fra cui la capacità degli algoritmi CD&R di gestire scenari in presenza di incertezza. La modellizzazione accurata delle fonti di incertezza e la previsione di traiettorie che tengano conto di eventi stocastici, sono problemi particolarmente difficoltosi nello sviluppo di algoritmi CD&R per traiettorie ottimali. L’incertezza sull’origine delle minacce, zone di condizioni metereologiche avverse al volo, errori nei sensori e nei sistemi di comunicazione per la navigazione aerea, sono solo alcune delle possibili fonti di incertezza che mettono a repentaglio le operazioni degli aeromobili. In questo lavoro, il conflitto è definito come la violazione della distanza minima tra un veicolo e un ostacolo fisso, e le manovre per evitare i conflitti possono essere ottenute solo variando l’angolo di rotta dell’aeromobile, ovvero virando. Il problema CD&R, formulato come un problema di controllo ottimo, o Optimal Control Problem (OCP), viene risolto tramite un metodo indiretto. Le condizioni necessarie di ottimalità, vale a dire le equazioni di Eulero-Lagrange derivanti dal calcolo delle variazioni, sono applicate alla dinamica del velivolo e all’ostacolo modellizato come una variabile stocastica. Le equazioni implicite di ottimalità formano un problema di valori al controno multipunto, Multipoint Boundary Value Problem(MPBVP), la cui soluzione in generale è tutt’altro che banale. La struttura della traiettoria ottimale viene dedotta dal tipo di vincolo, e l’andamento del moltiplicatore di Lagrange viene analizzato lungo il percorso ottimale. Il MPBVP viene prima approssimato con un spazio di polinomi di Taylor e successimvamente risolto tramite tecniche di algebra differenziale, in inglese Differential Algebra (DA). La soluzione del OCP è quindi un insieme di polinomi che approssima il controllo ottimo del problema in presenza di incertezza. In altri termini, il controllo ottimo è l’insieme degli angoli di prua del velivolo che minimizzano il tempo di volo e che tenendo conto dell’incertezza sulla posizione dell’ostacolo. Quando l’ostacolo viene rilevato dai sensori di bordo, questo metodo fornisce un utile strumento al pilota, o al controllore remoto, al fine di scegliere il miglior compromesso tra ottimalità e rischio di collisione con l’ostacolo. Simulazioni Monte Carlo sono eseguite per convalidare i risultati e l’efficacia del metodo presentato. Il metodo è valido anche per affrontare problemi CD&R in presenza di tempeste, altri velivoli, o altri tipi di ostacoli caratterizzati da una velocità relativa costante rispetto al proprio velivolo.El objetivo del trabajo presentado en esta tesis doctoral es la búsqueda y el desarrollo de un método novedoso de anticolisión con osbstáculos en espacios aéreos en presencia de incertidumbre, proporcionando trayectorias óptimas en términos de riesgo de colisión y tiempo de vuelo. La maniobra de anticolisión es el resultado de un algoritmo de detección y resolución de conflictos, en inglés Conflict Detection and Resolution (CD&R), preparado para un conflicto potencial entre una aeronave y un obstáculo fijo cuya posición es incierta. Debido al creciente interés en las operaciones de vehículos autónomos, también definidos como Unmanned Aerial System (UAS), en los últimos 10 años muchas investigaciones se han llevado a cabo en el tema CD&R. Uno de los aspectos cruciales que debe abordarse para una integración segura y eficiente de los vehículos UAS en el espacio aéreo no segregado es la actividad CD&R. La naturaleza intrínseca de UAS, y el entorno dinámico en el que están destinados a trabajar, suponen un reto para la capacidad de los algoritmos de CD&R de trabajar con escenarios en presencia de incertidumbre. La precisa modelización de las fuentes de incertidumbre, y la predicción de trayectorias que tengan en cuenta los eventos estocásticos, son problemas muy difíciles en el desarrollo de algoritmos CD&R para trayectorias óptimas. La incertidumbre sobre el origen de las amenazas, condiciones climáticas adversas, errores en sensores y sistemas de comunicación para la navegación aérea, son solo algunas de las posibles fuentes de incertidumbre que ponen en peligro las operaciones de los vehículos aéreos. En este trabajo, el conflicto se define como la violación de la distancia mínima entre un vehículo y un obstáculo fijo, y las maniobras de anticolisión se pueden lograr variando solo el ángulo de rumbo de la aeronave, es decir virando. El problema CD&R, formulado como problema de control óptimo, o Optimal Control Problem (OCP), se resuelve a través del método de control óptimo indirecto. Las condiciones necesarias de optimalidad, es decir, las ecuaciones de Euler-Lagrange que se obtienen a partir del cálculo de variaciones, son aplicadas a la dinámica de la aeronave y al obstáculo modelizado como variable estocástica. Las ecuaciones implícitas de optimalidad forman un problema de valor de frontera multipunto (MPBVP) cuya solución en general no es trivial. La estructura de la trayectoria de optimalidad se deduce del tipo de vínculo, y la tendencia del multiplicador de Lagrange se analiza a lo largo de la ruta óptima. El MPBVP se aproxima en primer lugar a través de un espacio de polinomios de Taylor, y luego se resuelve por medio de técnicas de álgebra diferencial, en inglés Differential Algebra(DA). La solución del OCP es un conjunto de polinomios que aproximan los controles óptimos en presencia de incertidumbre, es decir, los ángulos de rumbo óptimos que minimizan el tiempo de vuelo teniendo en cuenta la incertidumbre asociada a la posición del obstáculo. Una vez que los sensores a bordo detectan el obstáculo, este método proporciona una herramienta muy útil que permite al piloto, o control remoto, elegir el mejor compromiso entre optimalidad y riesgo de colisión con el obstáculo. Se ejecutan simulaciones de Monte Carlo para validar los resultados y la efectividad del método presentado. El método también es válido para abordar los problemas de CD&R en presencia de tormentas, otras aeronaves u otros tipos de obstáculos caracterizados por una velocidad relativa constante con respecto a la propia aeronave.Programa de Doctorado en Mecánica de Fluidos por la Universidad Carlos III de Madrid; la Universidad de Jaén; la Universidad de Zaragoza; la Universidad Nacional de Educación a Distancia; la Universidad Politécnica de Madrid y la Universidad Rovira i VirgiliPresidente: Carlo Novara.- Secretario: Lucia Pallotino.- Vocales: Manuel Sanjurjo Rivo; Yoshinori Matsuno; Alfonso Valenzuela Romer

4D Trajectory Optimization Satisfying Waypoint and No-Fly Zone Constraints

This paper presents a model of an innovative Flight Management System (FMS) which is purposely developed to control a commercial airliner along an optimized 4-Dimensional Trajectory (4DT), respecting time and path constraints, while avoiding No-Fly Zones (NFZ). The optimum, expressed in terms of minimum fuel consumption, is optained by solving an Optimization Control Problem (OCP) by means of the Chebyshev Pseudospectral numerical direct collocation scheme. The OCP trajectory solution is a discrete sequence of optimal aircraft states, which guarantee the minimum-fuel trip between two waypoints. With the aim of controlling the aircraft along lateral, vertical and longitudinal axis, and in order to respect NFZ and waypoints constraints along the optimum 4DT, different guidance navigation and control techniques can be implemented. The effectiveness of the algorithms is evaluated through simulations performed in the Multipurpose Aircraft Simulation Laboratory (MASLab), on a Boeing 747-100 model, equipped with a complete Automatic Flight Control System (AFCS) suite

Prognostic Relevance of Neutrophil to Lymphocyte Ratio (NLR) in Luminal Breast Cancer: A Retrospective Analysis in the Neoadjuvant Setting.

The neutrophil to lymphocyte ratio (NLR) is a promising predictive and prognostic factor in breast cancer. We investigated its ability to predict disease-free survival (DFS) and overall survival (OS) in patients with luminal A- or luminal B-HER2-negative breast cancer who received neoadjuvant chemotherapy (NACT). Pre-treatment complete blood cell counts from 168 consecutive patients with luminal breast cancer were evaluated to assess NLR. The study population was stratified into NLRlow or NLRhigh according to a cut-off value established by receiving operator curve (ROC) analysis. Data on additional pre- and post-treatment clinical-pathological characteristics were also collected. Kaplan-Meier curves, log-rank tests, and Cox proportional hazards models were used for statistical analyses. Patients with pre-treatment NLRlow showed a significantly shorter DFS (HR: 6.97, 95% CI: 1.65-10.55, p = 0.002) and OS (HR: 7.79, 95% CI: 1.25-15.07, p = 0.021) compared to those with NLRhigh. Non-ductal histology, luminal B subtype, and post-treatment Ki67 ≥ 14% were also associated with worse DFS (p = 0.016, p = 0.002, and p = 0.001, respectively). In a multivariate analysis, luminal B subtype, post-treatment Ki67 ≥ 14%, and NLRlow remained independent prognostic factors for DFS, while only post-treatment Ki67 ≥ 14% and NLRlow affected OS. The present study provides evidence that pre-treatment NLRlow helps identify women at higher risk of recurrence and death among patients affected by luminal breast cancer treated with NACT

The impact of the Hippo pathway and cell metabolism on pathological complete response in locally advanced Her2+ breast cancer: the TRISKELE multicenter prospective study

The Hippo pathway and its two key effectors, Yes-associated protein (YAP) and transcriptional coactivator with PDZ-binding motif (TAZ), are consistently altered in breast cancer. Pivotal regulators of cell metabolism such as the AMP-activated protein kinase (AMPK), Stearoyl-CoA-desaturase 1 (SCD1), and HMG-CoA reductase (HMGCR) are relevant modulators of TAZ/YAP activity. In this prospective study, we measured the tumor expression of TAZ, YAP, AMPK, SCD1, and HMGCR by immunohistochemistry in 65 Her2+ breast cancer patients who underwent trastuzumab-based neoadjuvant treatment. The aim of the study was to assess the impact of the immunohistochemical expression of the Hippo pathway transducers and cell metabolism regulators on pathological complete response. Low expression of cytoplasmic TAZ, both alone and in the context of a composite signature identified by machine learning including also low nuclear levels of YAP and HMGCR and high cytoplasmic levels of SCD1, was a predictor of residual disease in the univariate logistic regression. This finding was not confirmed in the multivariate model including estrogen receptor > 70% and body mass index > 20. However, our findings were concordant with overall survival data from the TCGA cohort. Our results, possibly affected by the relatively small sample size of this study population, deserve further investigation in adequately sized, ad hoc prospective studies

Current drive at plasma densities required for thermonuclear reactors

Progress in thermonuclear fusion energy research based on deuterium plasmas magnetically confined in toroidal tokamak devices requires the development of efficient current drive methods. Previous experiments have shown that plasma current can be driven effectively by externally launched radio frequency power coupled to lower hybrid plasma waves. However, at the high plasma densities required for fusion power plants, the coupled radio frequency power does not penetrate into the plasma core, possibly because of strong wave interactions with the plasma edge. Here we show experiments performed on FTU (Frascati Tokamak Upgrade) based on theoretical predictions that nonlinear interactions diminish when the peripheral plasma electron temperature is high, allowing significant wave penetration at high density. The results show that the coupled radio frequency power can penetrate into high-density plasmas due to weaker plasma edge effects, thus extending the effective range of lower hybrid current drive towards the domain relevant for fusion reactors

Corrigendum: Current drive at plasma densities required for thermonuclear reactors

Nature Communications 1: Article number: 55 (2010); Published: 10 August 2010; Updated:19 September 2013. In Fig. 3 of this Article, the colours of the blue and green curves were accidentally interchanged while the manuscript was being revised. In addition, the x axis labels on Fig. 4 should have read 'Frequency (MHz)'

How future surgery will benefit from SARS-COV-2-related measures: a SPIGC survey conveying the perspective of Italian surgeons

COVID-19 negatively affected surgical activity, but the potential benefits resulting from adopted measures remain unclear. The aim of this study was to evaluate the change in surgical activity and potential benefit from COVID-19 measures in perspective of Italian surgeons on behalf of SPIGC. A nationwide online survey on surgical practice before, during, and after COVID-19 pandemic was conducted in March-April 2022 (NCT:05323851). Effects of COVID-19 hospital-related measures on surgical patients' management and personal professional development across surgical specialties were explored. Data on demographics, pre-operative/peri-operative/post-operative management, and professional development were collected. Outcomes were matched with the corresponding volume. Four hundred and seventy-three respondents were included in final analysis across 14 surgical specialties. Since SARS-CoV-2 pandemic, application of telematic consultations (4.1% vs. 21.6%; p < 0.0001) and diagnostic evaluations (16.4% vs. 42.2%; p < 0.0001) increased. Elective surgical activities significantly reduced and surgeons opted more frequently for conservative management with a possible indication for elective (26.3% vs. 35.7%; p < 0.0001) or urgent (20.4% vs. 38.5%; p < 0.0001) surgery. All new COVID-related measures are perceived to be maintained in the future. Surgeons' personal education online increased from 12.6% (pre-COVID) to 86.6% (post-COVID; p < 0.0001). Online educational activities are considered a beneficial effect from COVID pandemic (56.4%). COVID-19 had a great impact on surgical specialties, with significant reduction of operation volume. However, some forced changes turned out to be benefits. Isolation measures pushed the use of telemedicine and telemetric devices for outpatient practice and favored communication for educational purposes and surgeon-patient/family communication. From the Italian surgeons' perspective, COVID-related measures will continue to influence future surgical clinical practice

Guidance Navigation and Control Techniques for 4D Trajectory Optimization Satisfying Waypoint and No-Fly Zone Constraints

The main purpose of this research is to develop a new FMS (Flight Management System) to control a commercial airliner along an optimized 4-Dimensional Trajectory (4DT), respecting time and path constraints, and avoiding a No-Fly Zone (NFZ). The optimum, expressed in terms of minimum fuel consumption, is addressed by solving an Optimization Control Problem (OCP) by means of a numerical direct collocation scheme, namely the Chebyshev Pseudospectral method. The OCP trajectory solution is a discrete sequence of optimal aircraft states which guarantee the minimum-fuel trip between two waypoints. With the aim of controlling the aircraft along lateral, vertical and longitudinal axis , and in order to respect NFZ and waypoints constraints along the optimum 4DT, different guidance navigation and control techniques were implemented. In order to validate the effectiveness of this algorithms on the Boeing 747-100 Automatic Flight Control System (AFCS), when it has to follow a 4D cruise route, several simulations were performed by generating three FMSs in the Multipurpose Aircraft Simulation Laboratory (MASLab), a software implementing the flight dynamic model of the Boeing 747-100

4D Trajectory Optimization Satisfying Waypoint and No-Fly Zone Constraints

International audienceThis paper presents a model of an innovative Flight Management System (FMS) which is purposely developed to control a commercial airliner along an optimized 4-Dimensional Trajectory (4DT), respecting time and path constraints, while avoiding No-Fly Zones (NFZ). The optimum, expressed in terms of minimum fuel consumption, is optained by solving an Optimization Control Problem (OCP) by means of the Chebyshev Pseu-dospectral numerical direct collocation scheme. The OCP trajectory solution is a discrete sequence of optimal aircraft states, which guarantee the minimum-fuel trip between two waypoints. With the aim of controlling the aircraft along lateral, vertical and longitudinal axis, and in order to respect NFZ and waypoints constraints along the optimum 4DT, different guidance navigation and control techniques can be implemented. The effectiveness of the algorithms is evaluated through simulations performed in the Multipurpose Aircraft Simulation Laboratory (MASLab), on a Boeing 747-100 model, equipped with a complete Automatic Flight Control System (AFCS) suite