Adaptive Neural Back-Stepping Control with Constrains for a Flexible Air-Breathing Hypersonic Vehicle

The design of an adaptive neural back-stepping control for a flexible air-breathing hypersonic vehicle (AHV) in the presence of input constraint and aerodynamic uncertainty is discussed. Based on functional decomposition, the dynamics can be decomposed into the velocity subsystem and the altitude subsystem. To guarantee the exploited controller’s robustness with respect to parametric uncertainties, neural network (NN) is applied to approximate the lumped uncertainty of each subsystem of AHV model. The exceptional contribution is that novel auxiliary systems are introduced to compensate both the tracking errors and desired control laws, based on which the explored controller can still provide effective tracking of velocity and altitude commands when the actuators are saturated. Finally, simulation studies are made to illustrate the effectiveness of the proposed control approach in spite of the flexible effects, system uncertainties, and varying disturbances

Adaptive Backstepping Control for Air-Breathing Hypersonic Vehicles with Input Nonlinearities

This paper addresses the control problem of air-breathing hypersonic vehicles subject to input nonlinearities, aerodynamic uncertainties and flexible modes. An adaptive backstepping controller and a dynamic inverse controller are developed for the altitude subsystem and the velocity subsystem, respectively, where the former eliminates the problem of “explosion of terms” inherent in backstepping control. Moreover, a modified smooth inverse of the dead-zone is proposed to compensate for the dead-zone effects and reduce the computational burden. Based on this smooth inverse, an input nonlinear pre-compensator is designed to handle input saturation and dead-zone nonlinearities, which leads to a simpler control design for the altitude subsystem subject to these two input nonlinearities. It is proved that the proposed controllers can guarantee that all closed-loop signals are bounded and the tracking errors converge to an arbitrarily small residual set. Simulation results are carried out to demonstrate the effectiveness of the proposed control scheme

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

Adaptive fault-tolerant attitude tracking control for hypersonic vehicle with unknown inertial matrix and states constraints

This paper proposes an adaptive fault-tolerant control (FTC) method for hypersonic vehicle (HSV) with unexpected centroid shift, actuator fault, time-varying full state constraints, and input saturation. The occurrence of unexpected centroid shift has three main effects on the HSV system, which are system uncertainties, eccentric moments, and variation of input matrix. In order to ensure the time-varying state constraints, a novel attitude state constraint control strategy, to keep the safe flight of HSV, is technically proposed by a time-varying state constraint function (TVSCF). A unified controller is designed to handle the time-varying state constraints according to the proposed TVSCF. Then, the constrained HSV system can be transformed into a novel free-constrained system based on the TVSCF. For the variation of system input matrix, input saturation and actuator fault, a special Nussbaum-type function is designed to compensate for those time-varying nonlinear terms. Additionally, the auxiliary systems is designed to compensate the constraint of system control inputs. Then, it is proved that the proposed control scheme can guarantee the boundedness of all closed-loop signals based on the Lyapunov stability theory. At last, the simulation results are provided to demonstrate the effectiveness of the proposed fault-tolerant control scheme.</p

Nonlinear Constrained Adaptive Backstepping Tracking Control for a Hypersonic Vehicle with Uncertainty

The control problem of a flexible hypersonic vehicle is presented, where input saturation and aerodynamic uncertainty are considered. A control-oriented model including aerodynamic uncertainty is derived for simple controller design due to the nonlinearity and complexity of hypersonic vehicle model. Then it is separated into velocity subsystem and altitude subsystem. On the basis of the integration of robust adaptive control and backstepping technique, respective controller is designed for each subsystem, where an auxiliary signal provided by an additional dynamic system is used to compensate for the control saturation effect. Then to deal with the “explosion of terms” problem inherent in backstepping control, a novel first-order filter is proposed. Simulation results are included to demonstrate the effectiveness of the adaptive backstepping control scheme

Adaptive Multivariable Integral TSMC of a Hypersonic Gliding Vehicle with Actuator Faults and Model Uncertainties

This paper presents a fault-tolerant control (FTC) strategy for a hypersonic gliding vehicle (HGV) subject to actuator malfunctions and model uncertainties. The control-oriented model of the HGV is estabilished according to the HGV kinematic and aerodynamic models. A single-loop design for HGV FTC under actuator faults is subsequently developed, where newly developed multivariable integral terminal sliding mode control (TSMC) and adaptive techniques are integrated. The multivariable integral TSMC is capable of ensuring the finite-time stability of the closed-loop system in the presence of actuator malfunctions and model uncertainties, while the adaptive laws are employed to tune the control parameters in response to the HGV status. Simulation studies based on a six degree-of-freedom (DOF) nonlinear model of the HGV are illustrated to highlight the effectiveness of the developed FTC scheme

Backstepping control with fixed-time prescribed performance for fixed wing UAV under model uncertainties and external disturbances

In this paper, a novel backstepping control scheme with fixed-time prescribed performance is proposed for the longitudinal model of fixed wing UAV subject to model uncertainties and external disturbances. The novel performance function with arbitrarily preassigned fixed-time convergence property is developed, which imposes priori performance envelops on both altitude and airspeed tracking errors. By using error transformed technology, the constrained fixed-time performance envelops are changed into unconstrained equivalent errors. Based on modified error compensation mechanism, a novel backstepping approach is proposed to guarantee altitude tracking equivalent error converges to the specified small neighborhood and presents excellent robustness against model uncertainties and external disturbances, and airspeed controller with fixed-time prescribed performance is designed. The proposed methodology guarantees the transient and steady-state performance of altitude and airspeed tracking errors within constrained fixed-time performance envelops in spite of lumped disturbances. Finally, numerical simulations are used to verify the effectiveness of the proposed control schem

Aeronautical engineering: A continuing bibliography with indexes (supplement 293)

This bibliography lists 476 reports, articles, and other documents introduced into the NASA scientific and technical information system in July, 1992. 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

Adaptive neural fault-tolerant control of a 3-DOF model helicopter system

In this paper, an adaptive neural fault-tolerant control scheme is proposed for the three degrees of freedom model helicopter, subject to system uncertainties, unknown external disturbances, and actuator faults. To tackle system uncertainty and nonlinear actuator faults, a neural network disturbance observer is developed based on the radial basis function neural network. The unknown external disturbance and the unknown neural network approximation errors are treated as a compound disturbance that is estimated by another nonlinear disturbance observer. A disturbance observer-based adaptive neural fault-tolerant control scheme is then developed to track the desired system output in the presence of system uncertainty, external disturbance, and actuator faults. The stability of the whole closed-loop system is analyzed using the Lyapunov method, which guarantees the convergence of all closed-loop signals. Finally, the simulation results are presented to illustrate the effectiveness of the new control design techniques.Mou Chen, Peng Shi and Cheng-Chew Li