scholarly journals Model-Based Systems Engineering Approach with SysML for an Automatic Flight Control System

2021 ◽  
Author(s):  
Haluk Altay ◽  
M. Furkan Solmazgül
Keyword(s):  
Control System ◽  
Complex Systems ◽  
Systems Engineering ◽  
Flight Control ◽  
Flight Control System ◽  
Engineering Approach ◽  
Model Based ◽  
Multidisciplinary Study ◽  
Model Based Systems Engineering

Systems engineering is the most important branch of engineering in interdisciplinary study. Successfully performing a multidisciplinary complex system is one of the most challenging tasks of systems engineering. Multidisciplinary study brings problems such as defining complex systems, ensuring communication between stakeholders, and common language among different design teams. In solving such problems, traditional systems engineering approach cannot provide an efficient solution. In this paper, a model-based systems engineering approach is applied with a case study and the approach is found to be more efficient. In the case study, the design of the helicopter automatic flight control system was realized by applying model-based design processes with integration of tools. Requirement management, system architecture management and model-based systems engineering processes are explained and applied of the case study. Finally, model-based systems engineering approach is proven to be effective compared with the traditional systems engineering methods for complex systems in aviation and defence industries.

scholarly journals APPLYING MODEL-BASED SYSTEMS ENGINEERING TO THE DEVELOPMENT OF AUTONOMOUS VESSEL FUNCTIONS

2020 ◽  
Vol 1 ◽  
pp. 2455-2464
Author(s):  
O. Bleisinger ◽  
S. Forte ◽  
C. Apostolov ◽  
M. Schmitt
Keyword(s):  
Complex Systems ◽  
Systems Engineering ◽  
Usage Phase ◽  
Model Based ◽  
Civil Sector ◽  
External Actors ◽  
Model Based Systems Engineering ◽  
Autonomous Vessel ◽  
Operational Aspects

AbstractDeveloping autonomous functions for complex systems leads to high demands on the consideration of dependencies to external actors in the usage phase. In Model-Based Systems Engineering (MBSE), this can be achieved by modelling operational aspects. Operational aspects are model elements and their relationships to each other. In this contribution, modelling of operational aspects with a MBSE-approach will be demonstrated exemplary on a case study related to the development of a yacht with an autonomous docking assistant. Currently modelling operational aspects is not common in the civil sector.

scholarly journals Microgrid System Design Based on Model Based Systems Engineering: the Case Study in the Amazon Region

2021 ◽  
Author(s):  
Miguel Angel Orellana Postigo ◽  
José Reinaldo Silva
Keyword(s):  
Systems Engineering ◽  
Amazon Forest ◽  
Small Communities ◽  
Model Based ◽  
Network Operation ◽  
Engineering Effort ◽  
Definition Of ◽  
And Control ◽  
Model Based Systems Engineering

Microgrid is a technically and economically viable opportunity to meet the demands of populations that, for various reasons, do not have access to electricity. The complexity of Smart Grid (SG) systems requires considerable engineering effort in the design process. Designing this type of complex system requires new approaches, methods, concepts and engineering tools. Where, requirements analysis plays a major role in better characterizing, understanding and specifying the domain of application that SG systems should solve. This work presents a systemic proposal based specifically on System Systems (SoS) which anticipates the formalization of requirements, aiming to understand, analyze and design SG within the scope of Model Based Systems Engineering (MBSE). The definition of a microgrid from the SoS perspective is presented in order to provide a complete view of its life cycle. Requirements would be represented in an Objective Oriented  Requirements Engineering (GORE) approach, specifically using visual diagrams based on the Keep All  Objectives Satisfied (KAOS) method, where network operation and control will be formally represented. A case  study for small communities in the equatorial Amazon forest is used as a case study for the proposed method.

A Model Based Systems Engineering Approach Towards Developing a Rapid Analysis and Trades Environment

2016 ◽  
Author(s):  
Tejas Kulkarni ◽  
Kevin DeBruin ◽  
Adam Nelessen ◽  
Kevin A. Reilley ◽  
Russell Peak ◽  
...  
Keyword(s):  
Systems Engineering ◽  
Rapid Analysis ◽  
Engineering Approach ◽  
Model Based ◽  
Model Based Systems Engineering

scholarly journals Design and Analysis for Early Warning of Rotor UAV Based on Data-Driven DBN

Electronics ◽  
2019 ◽  
Vol 8 (11) ◽  
pp. 1350 ◽  
Author(s):  
Chen ◽  
Wu ◽  
Wu ◽  
Xiong ◽  
Han ◽  
...  
Keyword(s):  
Neural Network ◽  
Control System ◽  
Fault Diagnosis ◽  
Early Warning ◽  
Flight Control ◽  
Data Driven ◽  
Diagnostic Model ◽  
Flight Control System ◽  
Model Based ◽  
On Line

The unmanned aerial vehicle (UAV), which is a typical multi-sensor closed-loop flight control system, has the properties of multivariable, time-varying, strong coupling, and nonlinearity. Therefore, it is very difficult to obtain an accurate mathematical diagnostic model based on the traditional model-based method; this paper proposes a UAV sensor diagnostic method based on data-driven methods, which greatly improves the reliability of the rotor UAV nonlinear flight control system and achieves early warning. In order to realize the rapid on-line fault detection of the rotor UAV flight system and solve the problems of over-fitting, limited generalization, and long training time in the traditional shallow neural network for sensor fault diagnosis, a comprehensive fault diagnosis method based on deep belief network (DBN) is proposed. Using the DBN to replace the shallow neural network, a large amount of off-line historical sample data obtained from the rotor UAV are trained to obtain the optimal DBN network parameters and complete the on-line intelligent diagnosis to achieve the goal of early warning as possible as quickly. In the end, the two common faults of the UAV sensor, namely the stuck fault and the constant deviation fault, are simulated and compared with the back propagation (BP) neural network model represented by the shallow neural network to verify the effectiveness of the proposed method in the paper.

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