1,721,334 research outputs found
Investigation of the student-professor interaction and self-learning ability for an aerospace engineering student
No full textBased on the didactic experiences of the authors as professors of Aerospace Engineering, this article proposes a mathematical model of the learning of the students in Aerospace Engineering. Starting from the definition of a taxonomy of the student's cognitive levels, a continuous-time model of the student's learning dynamics is developed. To this end, various factors linked to the nature of the student are introduced, such as inertia in learning, forgetting of concepts, readiness to educational stimuli and self-learning skills. Based on the analysis of stability and the position of the equilibrium points of the newly developed model, the characterization of the different types of the student is obtained by outlining different skills in assimilating the educational stimuli or in exploiting self-learning skills. Finally, teaching strategies are proposed based on such analysis
[Special issue on] Safety, Fault Diagnosis and Fault Tolerant Control in Aerospace Systems
No full textThis paper gives an overview of recent progress in theory and methods to analyze and design fault diagnosis and fault tolerant control techniques for aerospace systems. Passive and active approaches are presented and analyzed. Strongpoint and shortcomings of each approach are pointed out. Open problems related to the topic are also highlighted. The paper is written in a tutorial fashion to summarize some of the recent results in the subject area without going into details. A bibliographical review summarizing a decade of references is provided to allow interested readers to obtain more detailed information about the recent contributions in the field. Since the general areas of Fault Tolerant Control (FTC) and Fault Detection and Isolation (FDI) draws from a number of different technical areas in engineering and applied mathematics, no survey paper could hope to capture all existing contributions in the field
A Mathematical Model in Automatic Control Aerospace Engineering Education
No full textThe aerospace engineering educational system aims to create future professionals able to solve problems of high complexity, with time constraints and which solutions matches prescribed level of performance. In our past work, we introduced the innovative concept of the Professional Readiness Level (PRL) as a unique parameter to quantify how close the students are to the aerospace industry. In this paper we propose a dynamic model, of the PRL, capable to capture, in simple but effective way, the student behaviour we, as professors, observed in our educative experience
An experience of project based learning in aerospace engineering
No full textBased on the authors teaching experiences this paper proposes the developing of a ProJect-Based Learning (PJBL) environment for Automatic Control Education in Aerospace Engineering (ACEAE), which have been developed in several projects that involved the same authors. The PJBL approach have been based on the following major aspects: a Hardware/Software platform (quadricopter and related ground station, etc) as an environment to design and implement automatic control laws, and a proper choice of such tools in order to facilitate the communication of the knowledge between student of different classes and academic years, thus also improving communication skills and teamwork experience. A new didactic formulation is thus proposed, summarized by a Professional Readiness Level (PRL) table, useful to organize the learning of automatic controls for the Aerospace Engineering faculties. The actual status of this concept is applied at the University of Bologna in the courses of Automatic flight Control and Applied Control. In this work the choice of educational tools which could make the academic laboratory activities sustainable over time is proposed and the effectiveness of the proposed approach is assessed by means of the direct experience of the authors which summarize the feedback of the students involved in courses
A New Method for Satellite Navigation Signals FDI
No full textIntegrity of signals is an important issue for aerospace navigation systems and, in particular, for satellite navigation positioning. In this paper integrity monitoring techniques are processed with a new FDI technique implemented by a snapshot RAIM algorithm, based on linearized models, and position domain tests. The approach consists of the joint exploitation, in an Errors In Variables (EIV) framework, of all the possible Least Squares (LS) solutions under the hypothesis of a single fault on a pseudorange measurement. The characteristics of the behavior of the different LS position and bias estimates, by varying the fault size and the faulty satellite, are investigated. The non linear dependence of the locus of the solutions from the fault size is considered. The analysis of the loci properties results in a new criterion and algorithm for the detection and isolation of a faulty satellite signal. The effectiveness of the proposed method has been compared with respect to a classic FDI method by means of Montecarlo simulations based on a Galileo constellation simulator
Representing the dynamics of student learning and interactions with a university curriculum
No full textThe aim of the present study is to formulate a model that describes the dynamics of university students on the basis of continuous time differential equations and Petri Nets. Students are modeled by continuous time functions that represent their ability to deal with theoretical concepts and put them into practice. In addition, the curriculum is seen as a set of activities that students can select according to their willingness. The application of the model to public data of aerospace engineering students will be the subject of future work. Copyright (C) 2024 The Authors. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0/
Data-Driven Active and Passive Fault Tolerant Control Applications to a Wind Turbine Model
No full textWind turbines are complex dynamic systems forced by stochastic wind disturbances, gravitational, centrifugal, and gyroscopic loads. Since their aerodynamics can be nonlinear and unsteady, wind turbine modelling is thus challenging. Accurate models should thus contain many degrees of freedom to capture the most important dynamic effects. Moreover, wind turbine systems are remotely-installed structures which are also subject to many possible faults. Early fault detection, isolation and successful controller reconfiguration can considerably increase the performance in faulty conditions and prevent abysmal failures in the system. Therefore, the design of fault tolerant control algorithms for wind turbines must account for both complexity and faults. However, these algorithms must capture the most important turbine dynamics without being too complex and unwieldy. The main purpose of this study is thus to give two examples of viable and straightforward control designs with application to a wind turbine prototype. In particular, the first proposed strategy relies on a fuzzy modelling and identification approach oriented to the design of a passive fault tolerant fuzzy controller. This strategy has been suggested since it is quite simple and easy to implement with respect to different strategies proposed in literature. On the other hand, the second strategy represents an active fault tolerant control scheme relying on adaptive controllers designed by means of the on–line identification of the system model under diagnosis. Extensive simulations on the wind turbine process are the tools for assessing experimentally the reliability, the robustness, and the stability properties of the proposed control schemes in the presence of modelling and measurement errors. These developed control methods are also compared with other different approaches, in order to evaluate advantages and drawbacks of the considered techniques
Data–Driven Design of an Active Wake Steering Control for a Wind Farm Benchmark
No full textWake steering yaws upstream wind turbines to deflect their wakes from downstream turbines, thus increasing the generated power. However, most wake steering methods rely on lookup tables obtained offline, which map a set of conditions, such as wind speed and direction, to yaw angles for each turbine in a farm. These tables assume all turbines are operational and can be significantly non–optimal when one or more turbines do not provide the rated power, because of low wind speed, faults, routine maintenance, or emergency maintenance. This work presents an intelligent wake steering method that adapts to turbine actual working conditions when determining yaw angles. Using a hybrid model–and a learning–based method, i.e. an active control, a neural network is trained online to determine yaw angles from operating conditions including turbine status. Unlike purely model–based approaches which use lookup tables provided by the wind turbine manufacturer or generated offline, the proposed control solution does not need to solve e.g. optimisation problems for each combination of the turbine non-optimal working conditions in a farm; the integration of learning strategy in the control design allows to obtain an active control scheme
Intelligent Fault Diagnosis Techniques Applied to an Offshore Wind Turbine System
Full text linkFault diagnosis of wind turbine systems is a challenging process, especially for offshore plants, and the search for solutions motivates the research discussed in this paper. In fact, these systems must have a high degree of reliability and availability to remain functional in specified operating conditions without needing expensive maintenance works. Especially for offshore plants, a clear conflict exists between ensuring a high degree of availability and reducing costly maintenance. Therefore, this paper presents viable fault detection and isolation techniques applied to a wind turbine system. The design of the so-called fault indicator relies on an estimate of the fault using data-driven methods and effective tools for managing partial knowledge of system dynamics, as well as noise and disturbance effects. In particular, the suggested data-driven strategies exploit fuzzy systems and neural networks that are used to determine nonlinear links between measurements and faults. The selected architectures are based on nonlinear autoregressive with exogenous input prototypes, which approximate dynamic relations with arbitrary accuracy. The designed fault diagnosis schemes were verified and validated using a high-fidelity simulator that describes the normal and faulty behavior of a realistic offshore wind turbine plant. Finally, by accounting for the uncertainty and disturbance in the wind turbine simulator, a hardware-in-the-loop test rig was used to assess the proposed methods for robustness and reliability. These aspects are fundamental when the developed fault diagnosis methods are applied to real offshore wind turbines
Guidance and Nonlinear Active Fault Tolerant Control for General Aviation Aircraft
No full textThis paper addresses the development of a novel Active Fault Tolerant Control Scheme (AFTCS) which, when used with an independently designed guidance system, turns out to give an overall fault tolerant guidance and control system. This AFTCS methodology avoids a logic-based switching controller by exploiting an adaptive fault estimator whose design is based on the Non Linear Geometric Approach (NLGA). The application of the AFTC scheme to a Piper PA-30 aircraft simulator in a flight condition characterized by a tight-coupled longitudinal and lateral dynamics even in presence of wind, shows the enhancement of the flying quality, the asymptotic fault accommodation and the control objective recovery
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