Title :
Brief Paper - Universal Kriging control of hypersonic aircraft model using predictor model without back-stepping
Author :
Bin Xu ; Zhongke Shi
Author_Institution :
Sch. of Autom., Northwestern Polytech. Univ., Xi´an, China
Abstract :
This study describes the design of adaptive universal Kriging (UK) controller for the longitudinal dynamics of a generic hypersonic flight vehicle (HFV). The altitude subsystem is transformed into the explicit four-step ahead state predictor model, which provides the relationship between states and future outputs. Furthermore, the input--output predictor model is derived to obtain the input information for the UK estimator. The UK takes advantages of the parametric regression model and simple Kriging model to describe the systematic aspects and local fluctuations of unknown functions simultaneously. With the state prediction feedback and input--output UK estimation, the controller is synthesised. The control scheme is considerably simpler than the ones based on back-stepping since only one Kriging system is employed to approximate the lumped system uncertainty. Owing to the prediction function and the UK structure, the novel stochastic Lyapunov function-based stability analysis is conducted. The closed-loop system achieves almost surely boundedness. The effectiveness of the proposed control approach is verified by step tracking.
Keywords :
Lyapunov methods; adaptive control; aircraft control; approximation theory; closed loop systems; control system synthesis; predictive control; regression analysis; stability; state feedback; stochastic systems; uncertain systems; adaptive UK controller design; adaptive universal Kriging controller design; altitude subsystem; closed loop system; controller synthesis; explicit four-step ahead state predictor model; hypersonic aircraft model; hypersonic flight vehicle; input-output UK estimation; input-output predictor model; local fluctuations; longitudinal dynamics; lumped system uncertainty approximation; parametric regression model; prediction function; predictor model; state prediction feedback; step tracking; stochastic Lyapunov function-based stability analysis; unknown functions;
Journal_Title :
Control Theory & Applications, IET
DOI :
10.1049/iet-cta.2012.0876