Neural Networks Approximator Based Robust Adaptive Controller Design of Hypersonic Flight Vehicles Systems Coupled with Stochastic Disturbance and Dynamic Uncertainties. (18th September 2017)

• Record Type: Journal Article
• Authors: Zhu, Guoqiang; Sun, Lingfang; Zhang, Xiuyu
• Other Names: Zhang Weihai Academic Editor.
• Is Part Of: Mathematical problems in engineering. Volume 2017(2017)
• Publication Date: 2017-09-18
• Subjects: Engineering mathematics -- Periodicals; 510.2462
• DOI: 10.1155/2017/7864375
• Languages: English
• ISSNs: 1024-123X

Abstract

Abstract : A neural network robust control is proposed for a class of generic hypersonic flight vehicles with uncertain dynamics and stochastic disturbance. Compared with the present schemes of dealing with dynamic uncertainties and stochastic disturbance, the outstanding feature of the proposed scheme is that only one parameter needs to be estimated at each design step, so that the computational burden can be greatly reduced and the designed controller is much simpler. Moreover, by introducing a performance function in controller design, the prespecified transient and performance of tracking error can be guaranteed. It is proved that all signals of closed-loop system are uniformly ultimately bounded. The simulation results are carried out to illustrate effectiveness of the proposed control algorithm.