| Citation: | LI Xiaobing, ZHAO Siyuan, BU Xiangwei, et al. Design of prescribed performance backstepping control method for hypersonic flight vehicles[J]. Journal of Beijing University of Aeronautics and Astronautics, 2019, 45(4): 650-661. doi: 10.13700/j.bh.1001-5965.2018.0463(in Chinese)
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In order to solve the flight control problem of the air-breathing hypersonic vehicle, a new design method of neural inversion controller with prescribed performance was proposed. By constructing a prescribed performance function, it is ensured that the velocity tracking error and the altitude tracking error can converge to a desired area according to the prescribed convergence speed, overshoot amount and steady state error, and satisfy the preset transient performance and steady state accuracy of the system. Under the backstepping control design structure, the radial basis function(RBF) neural network was introduced to approximate the model unknown function and uncertainties, which improved the robustness of the control system. Only one parameter of the introduced RBF neural network needed to be updated online, which effectively improved the control accuracy, avoided the "differential expansion problem" in the backstepping control method, and reduced the burden of calculation. Finally, the simulation experiments verify the effectiveness and feasibility of the designed control system.
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