Robust Adaptive Control For Hypersonic Vehicles Based On Backstepping Technique

Hypersonic vehicle(HSV) has become one of the most important developmentdirections in the field of aerospace and its development level embodies the technologycapabilities and comprehensive strength of a country directly. The control systemdesign for HSV is one of the key technologies to realize the flight mission. HSV hasthe characteristics of high speed, large flight envelope, significant coupling anduncertainty which make the flight control system design more difficult and morechallenging. This dissertation focuses on the problem of control system design forHSV both in the cruise and reentry phases.Firstly, an adaptive backsteping control scheme is designed for a flexible HSV inthe cruise phase with aerodynamic uncertainty. To reduce the complexity of controllerdesign, a control-oriented model (COM) is derived where the flexible dynamics areregarded as perturbations and the aerodynamic uncertainty is included. Based on theanalysis of that, the COM is decomposed into velocity subsystem and altitudesubsystem. An adaptive law is used to estimate the unknown bound of the uncertainty.Then dynamic inversion (DI) and adaptive control are combined to design thecontroller of the velocity subsystem. Besides, the control of altitude is carried out bythe control of flight path angle (FPA), and then an adaptive backstepping controlshceme is designed for the dynamics of FPA, angle of attack and pitch rate.Simulation results show the performance of the proposed controller.Secondly, a robust adaptive dynamic surface control (DSC) scheme is designedfor a flexible HSV with input constraint and aerodynamic uncertainty. The COM isdecomposed into velocity subsystem and altitude subsystem. The unknown nonlinearfunction is approximated by the function neural network (RBFNN). Minimal-learningparameter technique is used to reduce the computational burden caused by theestimation of ideal weight vectors. Then DI, RBFNN and robust adaptive control arecombined to design the controller of the velocity subsystem, while DSC and RBFNNare combined to design the controller of the altitude subsystem. Additional systemsare designed to handle input constraints, and the states of them are employed at thelevel of controller design and stability analysis. Lyapunov-based stability analysisassures that the tracking errors converge to arbitrary small region around zero.Simulations results show the effectiveness of the presented control scheme.Thirdly, a robust adaptive backstepping control strategy is proposed for attitudecontrol of a HSV in reentry phase under inertia matrix uncertainty and moment disturbances. A COM is derived and it includes the uncertainty that does not satisfythe linearizaiton parameterization assumption. An adaptive law is used to estimate theunknown bound of the uncertainty in the attitude angle subsytem. Morevoer, theuncertianty in the attitude angle rate subsystem are handled by a robust term. TheLyapunov stability analysis proven that the tracking error converges to random smallneighborhood around zero. Simulations on6-degree-of-freedom (6-DOF) model showthe tracking performance of the proposed controller.At last, a robust adaptive filter backstepping control strategy is presented for theattitude control of a HSV during reentry phase under the consideration of inputconstriant, inertia matrix uncertainty and moment disturbances. An robust adaptivelaw is utilized to estimate the unknown bound of the uncertainty. The second-orderfilters are employed to overcome the “explosion of terms” problem inherent intraditional backstepping control. To cope with input constraints, an additional systemis introduced to analyze the impact of them. The stability of the closed-loop system isproven, and the tracking error can be forced into an arbitrarily small neighborhoodaround zero. The6-DOF model based simulation results are presented to verify theeffectiveness of the control strategy.