Intelligent Aircraft Research Articles

Разработка базы знаний для интеллектуального контура управления летательным аппаратом

Разработка базы знаний для интеллектуального контура управления летательным аппаратом

NEURAL NETWORK INTERPOLATION PARAMETERS OF A MULTI-MODE DYNAMIC MODEL OF THE AIRCRAFT ENGINE

The foundations of the concept of creation of intelligent aircraft engine control systems based on the decomposition of control processes within the architecture of open information systems are considered. Unlike well-known approaches, the suggested approach allows achieving the management goal based on the principle of minimum entropy by redistributing system resources in conditions of their shortage, as well as adapting system characteristics when changing the management situation based on self-learning and self-organization of intelligent control systems. Based on an analysis of the development trends of aircraft engines, as well as development trends of production and technological systems, including the creation of new composite materials and new technologies for the manufacture and control of parts and components of aircraft engines, the intellectualization of their automatic control systems is discussed. Moreover, the development trends of aircraft engine control systems are considered from the development of their structures, functions, properties, and abilities for new qualitative changes. The article gives the general characteristics and the main directions of the design of intelligent control systems for aircraft engines as complex technical objects. The problem of designing nonlinear dynamic models of aircraft engines using artificial neural networks is discussed. The statement of this problem and possible approaches to its solution are being formed. The results of the neural network identification of an aircraft engine are compared using the least-squares method. Such a technique for designing a model of aircraft engines makes it possible to indirectly calculate engine coordinates inaccessible to measurement - traction, fuel consumption, etc. The suggested approach allows calculation of the design of neural networks simulating aircraft engines at each step using standard procedures, which makes it possible to automate the creation of neural networks. To reduce the computation time, it is suggested using the optimization algorithms taking into account changes in the state entropy. This simplifies the implementation of the neural network model of an aircraft engine in real time as part of an onboard computer complex.

Research on rapid planning of intelligent aircraft trajectory under multiple constraints

Intelligent aircraft trajectory planning is an important support to ensure the successful completion of the mission of the aircraft, and it is also a key component of the intelligent aircraft mission planning system. Due to system performance constraints and environmental constraints, the positioning system of the intelligent aircraft cannot be accurately positioned during flight, which will cause flight errors. Excessive flight errors will lead to the failure of the mission. Therefore, error correction plays an increasingly important role in trajectory planning. This paper studies the rapid trajectory planning of intelligent aircraft under the limitation of system positioning accuracy. Based on the optimization theory, with the error generation rules and correction rules of the intelligent aircraft in flight as constraints, establishes the optimization model, and uses the fast non-dominated multi-objective optimization algorithm (NSGA-II) with elite retention strategy. This paper corrects the vertical and horizontal errors during the flight, and finally designs a reasonable intelligent aircraft trajectory that meets the minimum trajectory length and the minimum number of corrections during the flight.

Route Planning of Intelligent Aircraft under Multiple Constraints

In the study of multi-constraint route planning, the commonly used methods include genetic algorithm (GA), particle swarm optimization (PSO) etc. However, these algorithms are often too complex in practical applications and often get local optimal solutions when the number of calculations is too small. In this paper, we proposed the tangential progressive correction (TPC) model to solve the problem of route planning, it’s a kind of guided model with the characteristics of simple realization, good results and high calculation speed for planning aircraft route problem. At the end of the paper, we provided the simulation for relevant data.

Research on the Intelligent Aircraft Design based on STM32

Research on the Intelligent Aircraft Design based on STM32

A Design of the Intelligent Aircraft based on STM32

A Design of the Intelligent Aircraft based on STM32

Разработка алгоритма построения самоорганизующихся моделей в интеллектуальной системе управления летательными аппаратами

Разработка алгоритма построения самоорганизующихся моделей в интеллектуальной системе управления летательными аппаратами

Aero-servo-elastic design of a morphing wing trailing edge system for enhanced cruise performance

The Adaptive Trailing Edge Device (ATED) was a sub-project inside SARISTU (Smart Intelligent Aircraft Structures, 2011–2015), an L2 level project of the 7th EU Framework programme coordinated by Airbus, aimed at developing technologies for realizing a morphing wing for the improvement of general aircraft performance. That study, divided into design, manufacturing and testing phases, involved universities, research centers and leading industries of the European consortium. The aim of the present work is to predict the aero-servo-elastic impact of a full-scale morphing wing trailing edge on a CS-25 category aircraft. Within SARISTU, many FE models were realized, taking into account the complete and complex adaptive wing structure behavior. Those numerical representations referred to the 5.5 m wing section that was then employed for wind tunnel tests; such segment included the winglet and was representative of the outer wing segment (namely, the so-called “aileron region”). Those models were taken as reference to develop numerical representation of the considered wing that better suited the complete wing segment, from the fuselage attachment to the end of the flap region. Therefore, a scaling process was necessary, aimed at translating the former architectures to the new geometries. This kind of extrapolation had the advantage to take into account larger rooms to host the complex actuator system with all its components. MSC Nastran® FE models were elaborated to estimate stiffness and inertial distributions that allowed constructing the stick-beam mock-up of the complete structure. Several cases of flutter analysis were investigated by an in-house code, SANDY 3.0, to verify the safety requirements imposed by the applicable aviation regulations (paragraph 25.629, parts a and b-1). Moreover, dynamic stability assessment was performed with respect to single and combined failures of the actuation line and kinematic chain enabling morphing in order to support FHA (Fault and Hazard Analysis).

一类新算法研究智能飞行器航迹规划问题

一类新算法研究智能飞行器航迹规划问题

Composition and Application of Aircraft Towing Tractor Automatic Control System

The airports construction level is improved and the construction scale is constantly expanded with the rapid development of society, economy and science and technology, which brings a good development prospect for aircraft towing tractors. On the basis of summarizing the current research and application of aircraft towing tractors, the traction characteristics of towbar and towbarless aircraft tractors were analyzed, and the mechanical, electric, hydrodynamic and hydraulic transmission automatic control system were compared. The composition, working principle and application of hydraulic steering control system, hydraulic braking control system, hydraulic clamping and lifting mechanism and hydraulic hybrid power system of aircraft towing tractors were emphatically discussed. The results show that the configuration of towbarless traction is flexible and the traction capability is strong. Hydraulically controlled aircraft towing tractor has good traction, braking and control characteristics. Electronic hydraulic braking system is precisely controllable, and the hydraulic hybrid technology is beneficial to reduce the energy consumption of aircraft towing tractors. The demand for aircraft towing tractors is increasing with the expansion of the airport distribution and construction, on the basis of constantly improving the existing aircraft towing tractor and according to the needs of airport operation, it is necessary to adopt innovative technology to develop energy-saving, environment-friendly and intelligent aircraft towing tractors, so as to adapt the development needs of aviation industry.

An optical soft-sensor based shape sensing using a bio-inspired pattern recognition technique to realise fly-by-feel capability for intelligent aircraft operation

ABSTRACTInformation regarding deformations in large and complex systems is necessary in the prediction of structural failures caused by un-natural flexural occurrences. Sensing systems which are used to predict shapes, in order to develop a global surface picture require high precision and lower time lag. In this work, a unique bio-inspired training mechanism for support vector regression is presented for shape sensing in structures mounted with Fiber Bragg Gratings. Experimental validation was carried out on a simply supported beam, loaded at different positions and an aircraft wing model for different types of bending. The resulting deflections at specified locations along the length of the beam and on both surfaces of the wing were interpreted from the wavelength shifts of the corresponding Fiber Bragg Gratings through the specially modified Support Vector Regression. The method has shown high accuracy, low computational requirements and enhanced prediction times. The proposed bio-inspired training method has also been compared with two conventional training methodologies.

Design and integration sensitivity of a morphing trailing edge on a reference airfoil: The effect on high-altitude long-endurance aircraft performance

Trailing edge modification is one of the most effective ways to achieve camber variations. Usual flaps and aileron implement this concept and allow facing the different needs related to take-off, landing, and maneuver operations. The extension of this idea to meet other necessities, less dramatic in terms of geometry change yet useful a lot to increase the aircraft performance, moves toward the so-called morphing architectures, a compact version of the formers and inserted within the frame of the smart structures’ design philosophy. Mechanic (whether compliant or kinematic), actuation and sensor systems, together with all the other devices necessary for its proper working, are embedded into the body envelope. After the successful experiences, gained inside the SARISTU (SmARt Intelligent Aircraft STrUctures) project where an adaptive trailing edge was developed with the aim of compensating the weight variations in a medium-size commercial aircraft (for instance, occurring during cruise), the team herein exploits the defined architecture in the wing of a typical airfoil, used on high-altitude long-endurance aircraft such as the Global Hawk. Among the peculiarities of this kind of aerial vehicle, there is the long endurance, in turn, associated with a massive fuel storage (approximately around 50% of the total weight). A segmented, finger-like, rib layout is considered to physically implement the transition from the baseline airfoil to the target configurations. This article deals with an extensive estimation of the possible benefits related to the implementation of this device on that class of planes. Parametric aerodynamic analyses are performed to evaluate the effects of different architectural layouts (in-plane geometry extension) and different shape envelopes (namely, the rotation boundaries). Finally, the expected improvements in the global high-altitude long-endurance aircraft performance are evaluated, following the implementation of the referred morphing device.

Electrical, Thermal and Mechanical Properties of CNT Treated Prepreg CFRP Composites

This study is part of Smart Intelligent Aircraft Structures (SARISTU) project, which aims considerable improvements in aircraft damage tolerance, electrical conductivity and weight reduction besides producibility in industrial scale. In this study, the effect of multiwalled carbon nanotube reinforcement on electrical, thermal and mechanical properties of T800/M21 carbon fibre reinforced plastic is studied experimentally. T800/M21 is a commercial prepreg carbon fibre/epoxy composite material considered for CNT treatment by means of CNT-doped thermoplastic-based dry powder. The CNTs are deposited on top of prepreg material uniformly using a controlled spraying machine selecting the best state-of-the art and innovative performing technology from the candidate technologies within the project. The electrical conductivity of the composite material with/without CNT is measured in longitudinal, transverse and thickness directions. The changes occurring in the electrical conductivity of the composite materials are investigated. In order to investigate thermal behaviour of the composite materials, differential scanning calorimetry and thermogravimetric analyses are performed. Detailed thermal analysis is conducted for with/without carbon nanotube reinforced material to obtain the thermal conductivity, specific heat and thermal expansion coefficient of the material. Finally, the effect of carbon nanotube reinforcement on mechanical behaviours is studied by tensile, bending and shear tests.

Tracking feature extraction based on manifold learning framework

Manifold learning is a fast growing area of research recently. The main purpose of manifold learning is to search for intrinsic variables underlying high-dimensional inputs which lie on or are close to a low-dimensional manifold. Different from current theoretical works and applications of manifold learning approaches, in our work manifold learning framework is transferred to tracking feature extraction for the first time. The contributions of this article include three aspects. Firstly, in this article, we focus on tracking feature extraction for dynamic visual tracking on dynamic systems. The feature extracted in this article is based on manifold learning framework and is particular for dynamic tracking purpose. It can be directly applied to system control of dynamic systems. This is different from most traditional tracking features which are used for recognition and detection. Secondly, the proposed tracking feature extraction method has been successfully applied to three different dynamic systems: dynamic robot system, intelligent vehicle system and aircraft visual navigation system. Thirdly, experimental results have proven the validity of the tracking method based on manifold learning framework. Particularly, in the tracking experiments the vision system is dynamic. The tracking method is also compared with the well-known mean-shift tracking method, and tracking results have shown that our method outperforms the latter.

Professional knowledge sharing in aircraft maintenance: a new complexity dynamics

Aircraft maintenance can be described as a complex and interactive technical system. The ever increasing complex system of aircraft maintenance places much greater demands on the professionals carrying out this work including the leadership and management roles. This ethnographical study analyses this complex and intelligent aircraft maintenance work. Sharing of professional knowledge is of vital importance enhancing the innovative and creative work done in this domain. The aim of this paper is to highlight the challenges for the leadership and the management teams to effectively link complexity to the highly collective human intelligence that flourishes in this military domain. The challenges will be based on the empirical findings showing how the intrinsic leadership, collective intelligence and social dimensions such as cooperation, professional knowledge and management skills are played out within the communities of aircraft maintenance.

Analysis and comparison of aircraft landing control using recurrent neural networks and genetic algorithms approaches

This paper presents an intelligent aircraft automatic landing controller that uses recurrent neural networks (RNN) with genetic algorithms (GAs) to improve the performance of conventional automatic landing system (ALS) and guide the aircraft to a safe landing. Real-time recurrent learning (RTRL) is applied to train the RNN that uses gradient-descent of the error function with respect to the weights to perform the weights updates. Convergence analysis of system error is provided. The control scheme utilizes five crossover methods of GAs to search optimal control parameters. Simulations show that the proposed intelligent controller has better performance than the conventional controller.

Intelligent aircraft maintenance support system using genetic algorithms and case-based reasoning

The maintenance of aircraft components is crucial for avoiding aircraft accidents and aviation fatalities. To provide reliable and effective maintenance support, it is important for the airline companies to utilise previous repair experience with the aid of advanced decision support technology. Case-based reasoning (CBR) is a machine learning method that adapts previous similar cases to solve current problems. To effectively retrieve similar aircraft maintenance cases, this research proposes using a CBR system to aid electronic ballast fault diagnosis of Boeing 747-400 airplanes. By employing genetic algorithms (GA) to enhance dynamic weighting and the design of non-similarity functions, the proposed CBR system is able to achieve superior learning performance as compared to those with either equal/varied weights or linear similarity functions.

Joint development partnership for an intelligent aircraft circuit breaker

Joint development partnership for an intelligent aircraft circuit breaker

The intelligent aircraft

A modern fighter's sensors produce more information than one person can possibly comprehend in real time. Artificial-intelligence techniques offer the key to filtering and presenting the information and providing the means for the pilot to act on it.

The UK Mission Management Aid Project

In the 21st century combat aircraft necessarily will be complex and sophisticated to counter aggressors, on land, sea, or in the air, anywhere in the world. Along with new and improved sensors and weapons, cockpit facilities are being enhanced, bringing more and varied information to be absorbed and handled by aircrew. In this environment, to optimise situational awareness and mission effectiveness, some form of computerised assistance will be needed. UK Industry and Government are collaborating in a Mission Management Aid (MMA) project, to investigate this problem, by rapid prototyping the functional requirements and examining the real-time interface between man and his intelligent aircraft; he must remain in command, but can delegate control when and where he wishes. This paper outlines the current work on the MMA, and covers the core topics of Sensor Fusion, Situation & Threat Assessment, Dynamic Planning, Tactical Response, and how the system might integrate into an aircraft.