Evolutionary design of a full-envelope full-authority flight control system for an unstable high-performance aircraft

The use of an evolutionary algorithm in the framework of H1 control theory is being considered as a means for synthesizing controller gains that minimize a weighted combination of the infinite norm of the sensitivity function (for disturbance attenuation requirements) and complementary sensitivity function (for robust stability requirements) at the same time. The case study deals with a complete full-authority longitudinal control system for an unstable high-performance jet aircraft featuring (i) a stability and control augmentation system and (ii) autopilot functions (speed and altitude hold). Constraints on closed-loop response are enforced, that representing typical requirements on airplane handling qualities, that makes the control law synthesis process more demanding. Gain scheduling is required, in order to obtain satisfactory performance over the whole flight envelope, so that the synthesis is performed at different reference trim conditions, for several values of the dynamic pressure, used as the scheduling parameter. Nonetheless, the dynamic behaviour of the aircraft may exhibit significant variations when flying at different altitudes, even for the same value of the dynamic pressure, so that a trade-off is required between different feasible controllers synthesized at different altitudes for a given equivalent airspeed. A multiobjective search is thus considered for the determination of the best suited solution to be introduced in the scheduling of the control law. The obtained results are then tested on a longitudinal non-linear model of the aircraft

Robustness Analysis for Terminal Phases of Re-entry Flight

Advancements in the current practices used in robustness analysis for FCS design refinement by introducing a method that takes into account nonlinear effects of multiple uncertainties over the whole trajectory, to be used before robustness is finally assessed with MC analysis has been reported. Current practice in FCS robustness analysis for this kind of application mainly relies on the theory of linear time-invariant (LTI) systems. The method delivers feedback on the causes of requirement violation and adopts robustness criteria directly linked to the original mission or system requirements, such as those employed in MC analyses. The nonlinear robustness criterion proposed in the present work is based on the practical stability and/or finite time stability concepts. The practical stability property improves the accuracy in robustness evaluation with respect to frozen-time approaches, thus reducing the risk of discovering additional effects during robustness verification with Monte Carlo techniques

Optimisation-based verification process of obstacle avoidance systems for unmanned vehicles

This thesis deals with safety verification analysis of collision avoidance systems for unmanned vehicles. The safety of the vehicle is dependent on collision avoidance algorithms and associated control laws, and it must be proven that the collision avoidance algorithms and controllers are functioning correctly in all nominal conditions, various failure conditions and in the presence of possible variations in the vehicle and operational environment. The current widely used exhaustive search based approaches are not suitable for safety analysis of autonomous vehicles due to the large number of possible variations and the complexity of algorithms and the systems. To address this topic, a new optimisation-based verification method is developed to verify the safety of collision avoidance systems. The proposed verification method formulates the worst case analysis problem arising the verification of collision avoidance systems into an optimisation problem and employs optimisation algorithms to automatically search the worst cases. Minimum distance to the obstacle during the collision avoidance manoeuvre is defined as the objective function of the optimisation problem, and realistic simulation consisting of the detailed vehicle dynamics, the operational environment, the collision avoidance algorithm and low level control laws is embedded in the optimisation process. This enables the verification process to take into account the parameters variations in the vehicle, the change of the environment, the uncertainties in sensors, and in particular the mismatching between model used for developing the collision avoidance algorithms and the real vehicle. It is shown that the resultant simulation based optimisation problem is non-convex and there might be many local optima. To illustrate and investigate the proposed optimisation based verification process, the potential field method and decision making collision avoidance method are chosen as an obstacle avoidance candidate technique for verification study. Five benchmark case studies are investigated in this thesis: static obstacle avoidance system of a simple unicycle robot, moving obstacle avoidance system for a Pioneer 3DX robot, and a 6 Degrees of Freedom fixed wing Unmanned Aerial Vehicle with static and moving collision avoidance algorithms. It is proven that although a local optimisation method for nonlinear optimisation is quite efficient, it is not able to find the most dangerous situation. Results in this thesis show that, among all the global optimisation methods that have been investigated, the DIviding RECTangle method provides most promising performance for verification of collision avoidance functions in terms of guaranteed capability in searching worst scenarios

Surrogate - Assisted Optimisation -Based Verification & Validation

This thesis deals with the application of optimisation based Validation and Verification (V&V) analysis on aerospace vehicles in order to determine their worst case performance metrics. To this end, three aerospace models relating to satellite and launcher vehicles provided by European Space Agency (ESA) on various projects are utilised. As a means to quicken the process of optimisation based V&V analysis, surrogate models are developed using polynomial chaos method. Surro- gate models provide a quick way to ascertain the worst case directions as computation time required for evaluating them is very small. A sin- gle evaluation of a surrogate model takes less than a second. Another contribution of this thesis is the evaluation of operational safety margin metric with the help of surrogate models. Operational safety margin is a metric defined in the uncertain parameter space and is related to the distance between the nominal parameter value and the first instance of performance criteria violation. This metric can help to gauge the robustness of the controller but requires the evaluation of the model in the constraint function and hence could be computationally intensive. As surrogate models are computationally very cheap, they are utilised to rapidly compute the operational safety margin metric. But this metric focuses only on finding a safe region around the nominal parameter value and the possibility of other disjoint safe regions are not explored. In order to find other safe or failure regions in the param- eter space, the method of Bernstein expansion method is utilised on surrogate polynomial models to help characterise the uncertain param- eter space into safe and failure regions. Furthermore, Binomial failure analysis is used to assign failure probabilities to failure regions which might help the designer to determine if a re-design of the controller is required or not. The methodologies of optimisation based V&V, surrogate modelling, operational safety margin, Bernstein expansion method and risk assessment have been combined together to form the WCAT-II MATLAB toolbox

Small-body encounters using solar sail propulsion

Cometary Rendezvous and Flybys have large V requirements, which impose almost unattainable, and sometimes prohibitive, demands on the propellant budget of conventional, chemical propulsion. Ion Propulsion is a viable alternative, but as the number and difficulty of target objectives increases then the potential of this technology becomes rapidly less attractive. Solar sails exhibit an extremely high effective specific impulse over long mission durations. No propellant is required so that large changes in V could be realised without necessitating the introduction of complex gravity assists, which prolong mission duration and restrict launch opportunities. The endurance of the structures and materials are thus the only limiting factors dictating the number and range of bodies with which the solar-sail propelled vehicle can encounter throughout its lifetime. In this paper we have analysed a number of high-energy, small-body mission scenarios using a parameterised approach to sail control representation. The sail cone and clock angle histories were characterised by linear interpolation across a set of discrete nodes. The optimal control problem was thus transcribed to a Non-Linear Programming problem to select the optimal controls at the nodes that minimised the transfer time while enforcing the cartesian end-point boundary constraints (6 states for rendezvous, 3 for flypast). The Fortran77 optimisation package NPSOL 5.0 was used for this purpose with the variational equations of motion formulated in modified equinoctial orbital elements and integrated using a variable-order, adaptive step-size Adams-Moulton-Bashforth method. We present optimal rendezvous trajectories to Short-Period Comets such as 46P/Wirtanen in 484 days with a sail characteristic acceleration of 1.9 mms-2, and with 2P/Encke in 574 days with a characteristic acceleration of 1.0 mms-2. An analysis using high-performance sails has been conducted to permit fast flyby intercepts of newly discovered Long Period Comets (LPCs). Previous examples adopted were C/1995 O1/Hale- Bopp, C/1995 Y1/Hyakutake, C/1999 T1/McNaught-Hartley, C/1999 F1/Catalina, C/1999 N2/Lynn and C/1999 H1/Lee, to demonstrate the feasibility of a late launch to quickly intercept a new LPC using a solar sail. Since the time between discovery of a new LPC such as Hale-Bopp and perihelion passage was less then 2 years, this then leaves a very short time-span for orbit determination, preparation, planning and operational phases. Preliminary mission analysis shows that a Hale-Bopp perihelion flypast could have been achieved, with a sail characteristic acceleration of 5.0 mms-2, by launching just 209 days before comet perihelion passage. With a characteristic acceleration of 2.0 mms-2 Hale-Bopp could also have been intercepted at its descending node by launching 270 days before nodal descent. The sail could then have returned to rendezvous with the Earth 261 days later, giving a minimum total mission turn-around time of 531 days. An alternative, dual flyby scenario has been investigated, to continue on to C/1997 D1/Mueller, after which solar system escape was reached and arrival at Heliopause would occur in 12 years. Solar Electric Propulsion has been adopted as the primary propulsion system for the DAWN dual asteroid rendezvous mission scheduled for launch in 2006. The objective of this mission is to rendezvous with inner main-belt asteroids, Vesta and Ceres. We have also investigated solar sail adaptation to this mission, for the same launch date and 11 month orbiter stay-times. We have extended the mission objectives to two further asteroids, Lucina and Lutetia, with the aim of demonstrating a Mainbelt Asteroid Survey scenario

Cross Entropy-based Analysis of Spacecraft Control Systems

Space missions increasingly require sophisticated guidance, navigation and control algorithms, the development of which is reliant on verification and validation (V&V) techniques to ensure mission safety and success. A crucial element of V&V is the assessment of control system robust performance in the presence of uncertainty. In addition to estimating average performance under uncertainty, it is critical to determine the worst case performance. Industrial V&V approaches typically employ mu-analysis in the early control design stages, and Monte Carlo simulations on high-fidelity full engineering simulators at advanced stages of the design cycle. While highly capable, such techniques present a critical gap between pessimistic worst case estimates found using analytical methods, and the optimistic outlook often presented by Monte Carlo runs. Conservative worst case estimates are problematic because they can demand a controller redesign procedure, which is not justified if the poor performance is unlikely to occur. Gaining insight into the probability associated with the worst case performance is valuable in bridging this gap. It should be noted that due to the complexity of industrial-scale systems, V&V techniques are required to be capable of efficiently analysing non-linear models in the presence of significant uncertainty. As well, they must be computationally tractable. It is desirable that such techniques demand little engineering effort before each analysis, to be applied widely in industrial systems. Motivated by these factors, this thesis proposes and develops an efficient algorithm, based on the cross entropy simulation method. The proposed algorithm efficiently estimates the probabilities associated with various performance levels, from nominal performance up to degraded performance values, resulting in a curve of probabilities associated with various performance values. Such a curve is termed the probability profile of performance (PPoP), and is introduced as a tool that offers insight into a control system's performance, principally the probability associated with the worst case performance. The cross entropy-based robust performance analysis is implemented here on various industrial systems in European Space Agency-funded research projects. The implementation on autonomous rendezvous and docking models for the Mars Sample Return mission constitutes the core of the thesis. The proposed technique is implemented on high-fidelity models of the Vega launcher, as well as on a generic long coasting launcher upper stage. In summary, this thesis (a) develops an algorithm based on the cross entropy simulation method to estimate the probability associated with the worst case, (b) proposes the cross entropy-based PPoP tool to gain insight into system performance, (c) presents results of the robust performance analysis of three space industry systems using the proposed technique in conjunction with existing methods, and (d) proposes an integrated template for conducting robust performance analysis of linearised aerospace systems

Autonomous flight and remote site landing guidance research for helicopters

Automated low-altitude flight and landing in remote areas within a civilian environment are investigated, where initial cost, ongoing maintenance costs, and system productivity are important considerations. An approach has been taken which has: (1) utilized those technologies developed for military applications which are directly transferable to a civilian mission; (2) exploited and developed technology areas where new methods or concepts are required; and (3) undertaken research with the potential to lead to innovative methods or concepts required to achieve a manual and fully automatic remote area low-altitude and landing capability. The project has resulted in a definition of system operational concept that includes a sensor subsystem, a sensor fusion/feature extraction capability, and a guidance and control law concept. These subsystem concepts have been developed to sufficient depth to enable further exploration within the NASA simulation environment, and to support programs leading to the flight test

A comprehensive survey on cultural algorithms

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Aeronautical engineering: A continuing bibliography, supplement 122

This bibliography lists 303 reports, articles, and other documents introduced into the NASA scientific and technical information system in April 1980

Joint University Program for Air Transportation Research, 1991-1992

This report summarizes the research conducted during the academic year 1991-1992 under the FAA/NASA sponsored Joint University Program for Air Transportation Research. The year end review was held at Ohio University, Athens, Ohio, June 18-19, 1992. The Joint University Program is a coordinated set of three grants sponsored by the Federal Aviation Administration and NASA Langley Research Center, one each with the Massachusetts Institute of Technology (NGL-22-009-640), Ohio University (NGR-36-009-017), and Princeton University (NGL-31-001-252). Completed works, status reports, and annotated bibliographies are presented for research topics, which include navigation, guidance and control theory and practice, intelligent flight control, flight dynamics, human factors, and air traffic control processes. An overview of the year's activities for each university is also presented