Adaptive backstepping nonsingular terminal sliding-mode attitude control of flexible airships with actuator faults

This paper studies the attitude tracking control of a flexible airship subjected to wind disturbances, actuator saturation and control surface faults. Efficient flexible airship models, including elastic deformation, rigid body motions, and their coupling, are established via Lagrange theory. A fast-nonsingular terminal sliding-mode (NTSM) combined with a backstepping control is proposed for the problem. The benefits of this approach are NTSM merits of high robustness, fast transient response, and finite time convergence, as well as the backstepping control in terms of globally asymptotic stability. However, the major limitation of the backstepping NTSM is that its design procedure is dependent on the prior knowledge of the bound values of the disturbance and faults. To overcome this limitation, a wind observer is designed to compensate for the effect of the wind disturbances, an anti-windup compensator is designed to compensate for actuator saturation, and an adaptive fault estimator is designed to estimate the faults of the control surfaces. Globally exponential stability of the closed-loop control system is guaranteed by using the Lyapunov stability theory. Finally, simulation results demonstrate effectiveness and advantages of the proposed control for the Skyship-500 flexible airship, even in the presence of unknown wind disturbances, control surface faults, and different stiffness variants

IEEE Access Special Section: Recent Advances in Fault Diagnosis and Fault-Tolerant Control of Aerospace Engineering Systems

With the rapid development of automation technologies, aerospace engineering systems, including aircraft, satellite, and spacecraft, have become increasingly susceptible to system/component malfunctions. Failure to take appropriate responses to even relatively minor defects can result in highly destructive events. A conventional feedback control design may result in an unsatisfactory performance or even instability in the event of malfunctions. Because of this, fault diagnosis (FD) and fault-tolerant control (FTC) technologies that can ensure the safety of handicapped systems have attracted significant interest. FTC design and relevant techniques have provided a flexible framework for dealing with these challenges since the 1970s. There has been significant progress since the 1970s by the active research community, through symposiums and seminars, as well as the vast number of publications on the subject. The research illustrates that FD and FTC are effective and applicable in many engineering plants, especially for aerospace engineering systems. However, it still remains a challenging research area in applications relating to aircraft, spacecraft, and satellites

Estimation of airship states and model uncertainties using nonlinear estimators

This Airships are lighter than air vehicles and due to their growing number of applications, they are becoming attractive for the research community. Most of the applications require an airship autonomous flight controller which needs an accurate model and state information. Usually, airship states are affected by noise and states information can be lost in the case of sensor's faults, while airship model is affected by model inaccuracies and model uncertainties. This paper presents the application of nonlinear and Bayesian estimators for estimating the states and model uncertainties of neutrally buoyant airship. It is considered that minimum sensor measurements are available, and data is corrupted with process and measurement noise. A novel lumped model uncertainty estimation approach is formulated where airship model is augmented with six extra state variables capturing the model uncertainty of the airship. The designed estimator estimates the airship model uncertainty along with its states. Nonlinear estimators, Extended Kalman Filter and Unscented Kalman Filter are designed for estimating airship attitude, linear velocities, angular velocities and model uncertainties. While Particle filter is designed for the estimation of airship attitude, linear velocities and angular velocities. Simulations have been performed using nonlinear 6-DOF simulation model of experimental airship for assessing the estimator performances. 1− uncertainty bound and error analysis have been performed for the validation. A comparative study of the estimator's performances is also carried out

Neural network observer based LPV fault tolerant control of a flying-wing aircraft

For the problem of fault tolerant trajectory tracking control for a large Flying-Wing (FW) aircraft with Linear Parameter-Varying (LPV) model, a gain scheduled H ∞ controller is designed by dynamic output feedback. Robust synthesis of this gain scheduled H ∞ control is carried out by an affine Parameter Dependent Lyapunov Function (PDLF). The problem of trajectory tracking control for the LPV plant is transformed into solving an infinite number of linear matrix inequalities by the PDLF design, and the linear matrix inequalities are solved by convex optimization techniques. To overcome model uncertainties due to linearization and external disturbances, a radial basis function neural network disturbance observer is proposed, and to estimate actuator faults, an LPV fault estimator is designed. Furthermore, a composite controller is proposed to realize fault tolerant trajectory tracking control, which combines the LPV control with the fault estimator and disturbance observer, as well as an active-set based control allocation to avoiding actuator saturation. The approach is tested by simulation of two scenarios that show responses of the altitude, speed and heading angle to (i) unknown disturbances and (ii) actuator faults. The results show that the proposed neural network observer based LPV control has better performances for both disturbance rejecting and fault-tolerant trajectory tracking

Design of Flight Control Laws for a Novel Stratospheric Dual-Aircraft Platform

Dual-aircraft platform (DAP) is a novel concept that features two glider-like unmanned aerial systems (UAS) tethered via a thin adjustable cable allowing them to sail back-and-forth, without propulsion, using vertical wind shear. DAP offers the potential of a low-cost atmospheric satellite. This thesis presents the results of an initiative to demonstrate this novel flight concept through modeling, simulation, and flight testing at Embry-Riddle Aeronautical University (ERAU). A realistic simulation environment, described herein, was developed to support the development and testing of flight control systems. This environment includes nonlinear aerodynamic models for the aircraft, a multi-element cable dynamics model, propeller-motor thrust model, control surface actuator models, and permits time-varying wind profiles. This simulator offers both pilot-in-the-loop control and autonomous sailing flight control, and X-Plane interface to provide visualization cues. An intensive flight test program, described herein, was conducted to support the validation of the DAP concept. MAXA Pro 4m gliders were assembled, instrumented, and flight tested in an effort to physically demonstrate the sailing mode of flight. The flight test program described here focuses on the capability to sail with one aircraft (i.e., fly without propulsion) while towing (i.e., pulling) a moving truck as an intermediate step towards the more complex scenario of sailing with two connected aircraft. Two vital elements of the flight software are implemented and analyzed herein. The accuracy of wind estimation techniques is evaluated using flight testing. The robustness of an L1 adaptive controller is evaluated within the flight simulation environment by comparing its performance with a conventional controller

Aeronautical Engineering. A continuing bibliography with indexes, supplement 142

This bibliography lists 398 reports, articles, and other documents introduced into the NASA scientific and technical information system in November 1981

Aeronautical engineering: A continuing bibliography with indexes (supplement 211)

A continuing bibliography (NASA SP-7037) lists 519 reports, journal articles and other documents originally announced in February 1987 in Scientific and Technical Aerospace Reports (STAR) or in the International Aerospace Abstracts (IAA). The coverage includes documents on the engineering and theoretical aspect of design, construction, evaluation, testing, operation, and performance of aircraft (including aircraft engines) and associated components, equipment, and systems. It also includes research and development in aerodynamics, aeronautics, and ground support equipment for aeronautical vehicles. Each entry in the bibliography consists of a standard bibliographic citation accompanied in most cases by an abstract. The listing of the entries is arranged by the first nine STAR specific categories and the remaining STAR major categories. The arrangement offers the user the most advantageous breakdown for individual objectives. The citations include the original accession numbers from the respective announcement journals. The IAA items will precede the STAR items within each category. Seven indexes entitled subject, personal author, corporate source, foreign technology, contract number, report number, and accession number are included

Disturbance observer enhanced neural network LPV control for a blended-wing-body large aircraft

The problem of trajectory tracking control for a Blended-Wing-Body (BWB) large aircraft with model parameter uncertainties and unknown disturbances is considered. A Linear Parameter-Varying (LPV) model is derived from the nonlinear dynamics of the BWB aircraft from which a robust linear parameter-varying controller is designed to track a desired trajectory. Using a Single Quadratic Lyapunov Function (SQLF) and an infinite number of linear matrix inequalities to be evaluated at all vertices, a pair of positive definite symmetric matrix solutions is determined via Lyapunov stability theory and linear matrix inequality technique. Furthermore, a disturbance-observer is designed to process the unknown disturbances. Considering the plant exists some model errors except for disturbances, a Radial Basis Function Neural Network (RBFNN) approximation is embedded into the SQLF LPV controller to improve tracking performances, and a composite disturbance-observer based Neural Network Single Quadratic Lyapunov Function (NNSQLF) controller can realize desired trajectory tracking of the linear parameter-varying system through regulating performance weighting functions. The closed-loop system of trajectory tracking control is proved to be asymptotically stable by using Lyapunov theory. Simulation results of forward flight speed and altitude tracking control of the BWB aircraft show that the proposed disturbance-observer based NNSQLF control can robustly stabilize the LPV system and precisely track the desired trajectory by comparing with conventional SQLF control and Parameter-Dependent Lyapunov Functions (PDLF) control, even in unknown exterior disturbances and model uncertainties

Aeronautical engineering: A continuing bibliography with indexes (supplement 247)

This bibliography lists 437 reports, articles, and other documents introduced into the NASA scientific and technical information system in December, 1989. Subject coverage includes: design, construction and testing of aircraft and aircraft engines; aircraft components, equipment and systems; ground support systems; and theoretical and applied aspects of aerodynamics and general fluid dynamics

Aerial Vehicles

This book contains 35 chapters written by experts in developing techniques for making aerial vehicles more intelligent, more reliable, more flexible in use, and safer in operation.It will also serve as an inspiration for further improvement of the design and application of aeral vehicles. The advanced techniques and research described here may also be applicable to other high-tech areas such as robotics, avionics, vetronics, and space