Neural networks approximator based adaptive prescribed performance tracking control for hypersonic flight vehicles systems

An adaptive dynamic surface control(DSC) strategy, combined with RBF neural network technology, is presented for the altitude subsystem of hypersonic flight vehicles. A performance function has been used, so that the altitude tracking error enters a pre-set range. Through the use of minimal learning techniques, the computational burden is drastically reduced. It has been proved that the closed-loop system is uniformly stable. Finally, the simulation examples show the effectiveness of the proposed control strategy.