Weiner Model Drop Test Identification of a Light Amphibious Airplane

The new approach of the Weiner model for identifying drop test dynamics of a light amphibious airplane is presented in this paper. Unlike the traditional identification method of the Hammerstein model using LS-SVM with Gaussian radial basis serving as the kernel function, the small-signal excitation input is used to estimate the linear block of the Weiner model. Then, the static nonlinearity function of the model is identified through LS-SVM. The RMSE of the proposed Weiner model is 0.48805 and 0.38246 for the strut and wheel of the landing gear. The proposed Weiner model has better identification performance than the Hammerstein model and the traditional governing equation of the landing gear. The drop experiment of the light amphibious airplane is carried out not only to prove standard airworthiness compliance but also to verify the identifiability, accuracy, and performance of system identification

Joint University Program for Air Transportation Research, 1989-1990

Research conducted during the academic year 1989-90 under the NASA/FAA sponsored Joint University Program for Air Transportation research is discussed. Completed works, status reports and annotated bibliographies are presented for research topics, which include navigation, guidance and control theory and practice, aircraft performance, human factors, and expert systems concepts applied to airport operations. An overview of the year's activities for each university is also presented

Future grid for a sustainable green airport: meeting the new loads of electric taxiing and electric aircraft.

Lao, Liyun - Associate SupervisorThis thesis proposes a novel electric grid in the airside to meet zero-emission targets for ground movement operations in future airports, as mandated by Aeronautics Research performance target in Europe's (ACARE) FlightPath 2050. The grid delivers power from a renewable energy source through a flexible powerline using an autonomous electric taxiing robot (A-ETR) based on the concept of Energy As A Service (EAAS) for taxiing large aircraft and charging stations for ground vehicles. Four layers of optimisation are required to realise the viability of this new grid. The first optimisation layer involves creating an analytical model of the A-ETR using real-world data from Cranfield University's Airport based solar PV system and its Boeing 737 research aircraft and optimising its performance and efficiency using vehicle-level data-driven machine learning- based optimisation. As a result, the proposed grid achieves zero-emission taxiing and a 91% reduction in fuel compared to a standard baseline. The second layer optimises energy management in the microgrid using machine learning-based forecasting models to predict PV output and optimise charging and discharging cycles of A-ETR batteries to match solar resources and electricity rates. The result shows that the support vector regression (SVR) model best predicted PV output and optimised BESS charge/discharge cycles to achieve zero-emission airport ground movement operations while reducing the microgrid operating costs. However, ground traffic and load profiles increase as the model expands to include commercial airports. Therefore, the third optimisation layer develops a machine learning-based data-driven energy prediction optimisation to ensure microgrid resilience under the increased load. The model employs the Facebook Prophet algorithm to enhance the precision of energy demand prediction for airport ground movement operations across three- time horizons. The results facilitate the generation of reliable forecasts for clean energy production and ground movement energy demand at the airport. A fourth layer of optimisation has been developed to address the limitations of solar PV energy, which depend on the weather and cannot be dispatched, as well iii as the increase in airport traffic. The layer uses wind power and data from a "green" airport to complement PV power output. This model uses the stochastic model predictive control-based cascade feedforward neural network (SMPC- CFFNN) to optimise power flow between the microgrid and RES sources and support V2G capabilities. The results demonstrate that a Zero-emission microgrid for ground movement at green airports can be achieved through optimal power flow management and time optimisation. Reliability and resilience are crucial for a proposed microgrid ecosystem. We consider different network configurations to connect the existing airport grid. Two microgrid architectures, LVAC and LVDC, are compared based on their point of common connections (PCC) to evaluate the technical and economic implications on the airport's distribution network. We verify and validate the model's performance in terms of power quality, short circuit fault levels, system protection requirements, voltage profile, power losses, and equipment/system overloading to determine the optimal architecture. The results indicate that the A-ETR can provide ancillary services to the grid and enable novel emergency response systems. The comprehensive results from the multi-layered system-level optimisation approach adopted in this thesis not only validate the novelty of the proposed study but also serve to provide compelling evidence for its potential to provide viable solutions to the electrification challenges for future green airports by creating an ecosystem between airport ground operations and on-site renewable energy generating sources.PhD in Energy and Powe

An optimal ride control system for an executive jet aircraft

Aircraft specifically designed for short take-off and landing (STOL) operations are particularly sensitive to atmospheric turbulence and produce relatively high levels of vertical and lateral accelerations. These acceleration levels cause discomfort, which is unacceptable in modern transport aircraft. Such aircraft ought to have their dynamics improved by the action of a ride quality control system (R.e.S.) which should effectively reduce these accelerations thereby improving comfort. Little attention has been given to date to the problem of designing R.e.S. for executive jets. But with the developing use of such aircraft which are increasingly of the STOL type the demand for an effective R.e.S. has intensified. A few earlier studies used conventional theory to derive the required control laws but so far the use of modern control theory to derive laws based on a multi variable description of the aircraft responses has not been widely tried. Multivariable control theories can be applied to STOL aircraft by making use of the active control technology (A.C.T.) concept. This research has employed both A.e.T. and modern control theory to derive a suitable optimal control system which uses several aerodynamic control surfaces in such a way that the required reduction of the acceleration levels can be achieved. The optimal control law used to provide ride quality control involved the use of elevator, rudder and ailerons, in conjunction with spoilers, and horizontal and vertical canards. The subject aircraft chosen for this work was a specially-modified NASA Jetstar. The uncoupled equations of motion of the aircraft, together with disturbances due to atmospheric turbulence, were simulated on a digital computer. Frequency response methods were also used to provide information for comparison with results from conventional control. The experimental investigations involved consideration of the combination of surface activity, the effects of non-linearities in the surface actuators and the dynamic response to both manoeuvre commands and stochastic disturbances, The best results, expressed in terms of reduction of the levels of the normal and lateral acceleration, were obtained when all available controls were activated simultaneously and reductions of the order of 40% were achieved. The effect of the optimal control law on the aircraft handling qualities was also investigated and compared with idealised model

Aeronautical engineering: A continuing bibliography with indexes (supplement 267)

This bibliography lists 661 reports, articles, and other documents introduced into the NASA scientific and technical information system in June, 1991. Subject coverage includes design, construction and testing of aircraft and aircraft engines; aircraft components, equipment and systems; ground support systems; theoretical and applied aspects of aerodynamics and general fluid dynamics; electrical engineering; aircraft control; remote sensing; computer sciences; nuclear physics; and social sciences

Existing and Required Modeling Capabilities for Evaluating ATM Systems and Concepts

ATM systems throughout the world are entering a period of major transition and change. The combination of important technological developments and of the globalization of the air transportation industry has necessitated a reexamination of some of the fundamental premises of existing Air Traffic Management (ATM) concepts. New ATM concepts have to be examined, concepts that may place more emphasis on: strategic traffic management; planning and control; partial decentralization of decision-making; and added reliance on the aircraft to carry out strategic ATM plans, with ground controllers confined primarily to a monitoring and supervisory role. 'Free Flight' is a case in point. In order to study, evaluate and validate such new concepts, the ATM community will have to rely heavily on models and computer-based tools/utilities, covering a wide range of issues and metrics related to safety, capacity and efficiency. The state of the art in such modeling support is adequate in some respects, but clearly deficient in others. It is the objective of this study to assist in: (1) assessing the strengths and weaknesses of existing fast-time models and tools for the study of ATM systems and concepts and (2) identifying and prioritizing the requirements for the development of additional modeling capabilities in the near future. A three-stage process has been followed to this purpose: 1. Through the analysis of two case studies involving future ATM system scenarios, as well as through expert assessment, modeling capabilities and supporting tools needed for testing and validating future ATM systems and concepts were identified and described. 2. Existing fast-time ATM models and support tools were reviewed and assessed with regard to the degree to which they offer the capabilities identified under Step 1. 3 . The findings of 1 and 2 were combined to draw conclusions about (1) the best capabilities currently existing, (2) the types of concept testing and validation that can be carried out reliably with such existing capabilities and (3) the currently unavailable modeling capabilities that should receive high priority for near-term research and development. It should be emphasized that the study is concerned only with the class of 'fast time' analytical and simulation models. 'Real time' models, that typically involve humans-in-the-loop, comprise another extensive class which is not addressed in this report. However, the relationship between some of the fast-time models reviewed and a few well-known real-time models is identified in several parts of this report and the potential benefits from the combined use of these two classes of models-a very important subject-are discussed in chapters 4 and 7

Nineteenth Annual Conference on Manual Control

No abstract availabl