Tracking performance and global stability guaranteed neural control of uncertain hypersonic flight vehicle

Tao Teng,Shi-Lu Dai,Chenguang Yang,Min Wang

doi:10.1177/1729881416678140

Abstract

In this article, a global adaptive neural dynamic surface control with predefined tracking performance is developed for a class of hypersonic flight vehicles, whose accurate dynamics is hard to obtain. The control scheme developed in this paper overcomes the limitations of neural approximation region by employing a switching mechanism which incorporates an additional robust controller outside the neural approximation region to pull the transient state variables back when they overstep the neural approximation region, such that globally uniformly ultimately bounded stability can be guaranteed. Especially, the developed global adaptive neural control also improves the tracking performance by introducing an error transformation mechanism, such that both transient and steady-state performance can be shaped according to the predefined bounds. Simulation studies on the hypersonic flight vehicle validate that the designed controller has good velocity modulation and velocity stability performance.

Highlights

Hypersonic flight vehicles (HFVs) with the unique superiority of its own meet the increasing commercial and military demands for space access very well
HFVs are the focus of recent research in various space powers, but the flight aerodynamic environment is complex, and its model uncertainty increases because of its high speed, which makes the design of guidance and control system difficult
Since the work condition faced in HFVs is extremely complex, which is always unknown, dynamic and nonlinear, little knowledge about HFVs dynamics parameters is available in real applications

Summary

Introduction

Hypersonic flight vehicles (HFVs) with the unique superiority of its own (such as high speed, quick response and strong penetration power) meet the increasing commercial and military demands for space access very well. While in the study by Dai et al.,[30] an adaptive neural controller achieves predefined transient tracking performance by employing an error transformation mechanism. In the study by Chen et al.,[31] backstepping technique is embedded into the design of guaranteed transient performance-based attitude control with control input saturation. Inspired by the aforementioned work, in this design, an NN employed dynamic surface control (DSC) technique[12,32,33] is devised for HFVs with guaranteed tracking performance and global stability. This overall structure is as follows: dynamics of HFVs is characterized in ‘Problem formulation’ section.

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Conclusion