Incremental twisting fault tolerant control for hypersonic vehicles with partial model knowledge

A passive fault tolerant control scheme is proposed for the full reentry trajectory tracking of a hypersonic vehicle in the presence of modelling uncertainties, external disturbances, and actuator faults. To achieve this goal, the attitude error dynamics with relative degree two is formulated first by ignoring the nonlinearities induced by the translational motions. Then, a multivariable twisting controller is developed as a benchmark to ensure the precise tracking task. Theoretical analysis with the Lyapunov method proves that the attitude tracking error and its first-order derivative can simultaneously converge to the origin exponentially. To depend less on the model knowledge and reduce the system uncertainties, an incremental twisting fault tolerant controller is derived based on the incremental nonlinear dynamic inversion control and the predesigned twisting controller. Notably, the proposed controller is user friendly in that only fixed gains and partial model knowledge are required

Robust Adaptive Neural Control of Morphing Aircraft with Prescribed Performance

This study proposes a low-computational composite adaptive neural control scheme for the longitudinal dynamics of a swept-back wing aircraft subject to parameter uncertainties. To efficiently release the constraint often existing in conventional neural designs, whose closed-loop stability analysis always necessitates that neural networks (NNs) be confined in the active regions, a smooth switching function is presented to conquer this issue. By integrating minimal learning parameter (MLP) technique, prescribed performance control, and a kind of smooth switching strategy into back-stepping design, a new composite switching adaptive neural prescribed performance control scheme is proposed and a new type of adaptive laws is constructed for the altitude subsystem. Compared with previous neural control scheme for flight vehicle, the remarkable feature is that the proposed controller not only achieves the prescribed performance including transient and steady property but also addresses the constraint on NN. Two comparative simulations are presented to verify the effectiveness of the proposed controller

A machine learning based approach to gravitational lens identification with the International LOFAR Telescope

We present a novel machine learning based approach for detecting galaxy-scale gravitational lenses from interferometric data, specifically those taken with the International LOFAR Telescope (ILT), which is observing the northern radio sky at a frequency of 150 MHz, an angular resolution of 350 mas and a sensitivity of 90  µJy beam−1 (1σ). We develop and test several Convolutional Neural Networks to determine the probability and uncertainty of a given sample being classified as a lensed or non-lensed event. By training and testing on a simulated interferometric imaging data set that includes realistic lensed and non-lensed radio sources, we find that it is possible to recover 95.3 per cent of the lensed samples (true positive rate), with a contamination of just 0.008 per cent from non-lensed samples (false positive rate). Taking the expected lensing probability into account results in a predicted sample purity for lensed events of 92.2 per cent. We find that the network structure is most robust when the maximum image separation between the lensed images is ≥3 times the synthesized beam size, and the lensed images have a total flux density that is equivalent to at least a 20σ (point-source) detection. For the ILT, this corresponds to a lens sample with Einstein radii ≥0.5 arcsec and a radio source population with 150 MHz flux densities ≥2 mJy. By applying these criteria and our lens detection algorithm we expect to discover the vast majority of galaxy-scale gravitational lens systems contained within the LOFAR Two Metre Sky Survey

Fractional Order Fault Tolerant Control - A Survey

In this paper, a comprehensive review of recent advances and trends regarding Fractional Order Fault Tolerant Control (FOFTC) design is presented. This novel robust control approach has been emerging in the last decade and is still gathering great research efforts mainly because of its promising results and outcomes. The purpose of this study is to provide a useful overview for researchers interested in developing this interesting solution for plants that are subject to faults and disturbances with an obligation for a maintained performance level. Throughout the paper, the various works related to FOFTC in literature are categorized first by considering their research objective between fault detection with diagnosis and fault tolerance with accommodation, and second by considering the nature of the studied plants depending on whether they are modelized by integer order or fractional order models. One of the main drawbacks of these approaches lies in the increase in complexity associated with introducing the fractional operators, their approximation and especially during the stability analysis. A discussion on the main disadvantages and challenges that face this novel fractional order robust control research field is given in conjunction with motivations for its future development. This study provides a simulation example for the application of a FOFTC against actuator faults in a Boeing 747 civil transport aircraft is provided to illustrate the efficiency of such robust control strategies

Fault tolerant control for nonlinear aircraft based on feedback linearization

The thesis concerns the fault tolerant flight control (FTFC) problem for nonlinear aircraft by making use of analytical redundancy. Considering initially fault-free flight, the feedback linearization theory plays an important role to provide a baseline control approach for de-coupling and stabilizing a non-linear statically unstable aircraft system. Then several reconfigurable control strategies are studied to provide further robust control performance:- A neural network (NN)-based adaption mechanism is used to develop reconfigurable FTFC performance through the combination of a concurrent updated learninglaw. - The combined feedback linearization and NN adaptor FTFC system is further improved through the use of a sliding mode control (SMC) strategy to enhance the convergence of the NN learning adaptor. - An approach to simultaneous estimation of both state and fault signals is incorporated within an active FTFC system.The faults acting independently on the three primary actuators of the nonlinear aircraft are compensated in the control system.The theoretical ideas developed in the thesis have been applied to the nonlinear Machan Unmanned Aerial Vehicle (UAV) system. The simulation results obtained from a tracking control system demonstrate the improved fault tolerant performance for all the presented control schemes, validated under various faults and disturbance scenarios.A Boeing 747 nonlinear benchmark model, developed within the framework of the GARTEUR FM-AG 16 project “fault tolerant flight control systems”,is used for the purpose of further simulation study and testing of the FTFC scheme developed by making the combined use of concurrent learning NN and SMC theory. The simulation results under the given fault scenario show a promising reconfiguration performance

A feasibility study of orbiter flight control experiments

The results of a feasibility study of orbiter flight control experiments performed are summarized. Feasibility studies were performed on a group of 14 experiments selected from a candidate list of 35 submitted to the study contractor by the flight control community. Concepts and requirements were developed for the 14 selected experiments and they were ranked on a basis of technical value, feasibility, and cost. It was concluded that all the selected experiments can be considered as potential candidates for the Orbiter Experiment program, which is being formulated for the Orbiter Flight Tests and subsequent operational flights, regardless of the relative ranking established during the study. None of the selected experiments has significant safety implications and the cost of most was estimated to be less than $200K

Optimal fault-tolerant flight control for aircraft with actuation impairments

Current trends towards greater complexity and automation are leaving modern technological systems increasingly vulnerable to faults. Without proper action, a minor error may lead to devastating consequences. In flight control, where the controllability and dynamic stability of the aircraft primarily rely on the control surfaces and engine thrust, faults in these effectors result in a higher extent of risk for these aspects. Moreover, the operation of automatic flight control would be suddenly disturbed. To address this problem, different methodologies of designing optimal flight controllers are presented in this thesis. For multiple-input multiple-output (MIMO) systems, the feedback optimal control is a prominent technique that solves a multi-objective cost function, which includes, for instance, tracking requirements and control energy minimisation. The first proposed method is based on a linear quadratic regulator (LQR) control law augmented with a fault-compensation scheme. This fault-tolerant system handles the situation in an adaptive way by solving the optimisation cost function and considering fault information, while assuming an effective fault detection system is available. The developed scheme was tested in a six-degrees-of-freedom nonlinear environment to validate the linear-based controller. Results showed that this fault tolerant control (FTC) strategy managed to handle high magnitudes of the actuator’s loss of effciency faults. Although the rise time of aircraft response became slower, overshoot and settling errors were minimised, and the stability of the aircraft was maintained. Another FTC approach has been developed utilising the features of controller robustness against the system parametric uncertainties, without the need for reconfiguration or adaptation. Two types of control laws were established under this scheme, the H∞ and µ-synthesis controllers. Both were tested in a nonlinear environment for three points in the flight envelope: ascending, cruising, and descending. The H∞ controller maintained the requirements in the intact case; while in fault, it yielded non-robust high-frequency control surface deflections. The µ-synthesis, on the other hand, managed to handle the constraints of the system and accommodate faults reaching 30% loss of effciency in actuation. The final approach is based on the control allocation technique. It considers the tracking requirements and the constraints of the actuators in the design process. To accommodate lock-in-place faults, a new control effort redistribution scheme was proposed using the fuzzy logic technique, assuming faults are provided by a fault detection system. The results of simulation testing on a Boeing 747 multi-effector model showed that the system managed to handle these faults and maintain good tracking and stability performance, with some acceptable degradation in particular fault scenarios. The limitations of the controller to handle a high degree of faults were also presented

Finite-time Sliding Mode and Super-twisting Control of Fighter Aircraft

The development of two nonlinear robust higher-order flight control systems for roll-coupled maneuvers of fighter aircraft with uncertain parameters is discussed in this article. The objective is to independently control the output variables (roll angle, pitch angle and sideslip angle) using aileron, elevator and rudder control surfaces. For a nominal model of aircraft, first a finite time stabilizing (FTS) control law, based on the notion of geometric homogeneity, is designed. Then for robust control in the presence of parameter uncertainties, (i) a discontinuous sliding mode (DSM) control law and (ii) a super-twisting (STW) continuous control law is designed. It is shown that in the composite closed-loop system consisting of either (a) the FTS and DSM control laws or (b) the FTS and STW control systems, the output trajectory tracking error and its first-order derivative converge to the origin in finite time. Digital simulation results for a swept-wing fighter aircraft, including the two composite control systems, are obtained. These results show that each of the designed flight controllers accomplishes precise simultaneous large longitudinal and lateral maneuvers, despite uncertainties in the aerodynamic and inertia parameters, turbulence, and partial loss of control surface effectiveness

2004 Research Engineering Annual Report

Selected research and technology activities at Dryden Flight Research Center are summarized. These activities exemplify the Center's varied and productive research efforts

Nonlinear robust H∞ control.

A new theory is proposed for the full-information finite and infinite horizontime robust H∞ control that is equivalently effective for the regulation and/or tracking problems of the general class of time-varying nonlinear systems under the presence of exogenous disturbance inputs. The theory employs the sequence of linear-quadratic and time-varying approximations, that were recently introduced in the optimal control framework, to transform the nonlinear H∞ control problem into a sequence of linearquadratic robust H∞ control problems by using well-known results from the existing Riccati-based theory of the maturing classical linear robust control. The proposed method, as in the optimal control case, requires solving an approximating sequence of Riccati equations (ASRE), to find linear time-varying feedback controllers for such disturbed nonlinear systems while employing classical methods. Under very mild conditions of local Lipschitz continuity, these iterative sequences of solutions are known to converge to the unique viscosity solution of the Hamilton-lacobi-Bellman partial differential equation of the original nonlinear optimal control problem in the weak form (Cimen, 2003); and should hold for the robust control problems herein. The theory is analytically illustrated by directly applying it to some sophisticated nonlinear dynamical models of practical real-world applications. Under a r -iteration sense, such a theory gives the control engineer and designer more transparent control requirements to be incorporated a priori to fine-tune between robustness and optimality needs. It is believed, however, that the automatic state-regulation robust ASRE feedback control systems and techniques provided in this thesis yield very effective control actions in theory, in view of its computational simplicity and its validation by means of classical numerical techniques, and can straightforwardly be implemented in practice as the feedback controller is constrained to be linear with respect to its inputs