Abstract
In this article, an adaptive neural tracking controller is designed for near-space vehicles with stochastic disturbances and unknown parametric uncertainties. Based on the great nonlinear function approximation capability of neural networks, the unknown system uncertainties are tackled using the radial basis function neural networks. Furthermore, on the basis of stochastic Lyapunov stability theory, an adaptive tracking control scheme is developed for near-space vehicle which can guarantee the closed-loop system stability. Under the developed adaptive neural control scheme, all closed-loop system signals are bounded in the sense of probability, and the tracking error converges to a small neighborhood of the origin. Finally, simulation results are provided to illustrate the proposed adaptive neural control scheme that can guarantee the satisfactory tracking performance for the attitude motion of the near-space vehicle with stochastic disturbances.
Highlights
Near-space vehicles (NSVs) are novel aerospace vehicles that have attracted more and more attention
The novel global neural dynamic surface tracking control scheme is presented for hypersonic flight vehicle in the study by Xu et al.[16]
The guaranteed transient performance-based attitude control scheme was proposed for NSV with input saturation by Chen et al.[17]
Summary
Near-space vehicles (NSVs) are novel aerospace vehicles that have attracted more and more attention. The novel global neural dynamic surface tracking control scheme is presented for hypersonic flight vehicle in the study by Xu et al.[16] The guaranteed transient performance-based attitude control scheme was proposed for NSV with input saturation by Chen et al.[17] In the study by Chen et al.,[18] a robust sliding mode control strategy was presented for attitude dynamics of NSV. Over the past few decades, the disturbance observer–based control schemes have been well studied in the literature.[20,21,22,23,24,25,26,27,28,29,30] To efficiently handle the unknown disturbance based on the dynamic information of disturbance, the adaptive dynamic surface control scheme based on disturbance observer was proposed for the NSV with input saturation by Chen and Yu.[31] In the study by Chen et al.,[32] on the basis of terminal sliding mode technique and disturbance observer method, an anti-disturbance control scheme was developed for the hypersonic flight vehicles with input saturation. F is the s-algebra of the subsets of sample space X, and P is the probability measure
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