Wide-speed-range vehicles are characterized by high flight altitude and high speed, with significant changes in the flight environment. Due to the strong uncertainty of its aerodynamic characteristics, higher requirements are imposed on attitude control. In this paper, an adaptive prescribed performance control method based on online aerodynamic identification is proposed, which consists of two parts: an online aerodynamic parameter identification method and an adaptive attitude control method based on the pre-defined parameters of the control system. The aerodynamic parameter identification is divided into offline design and online design. In the offline design, neural networks are used to fit nonlinear aerodynamic characteristics. In the online design, a nonlinear recursive identification method is used to correct the errors of the offline fitted model. The adaptive attitude control is based on the conventional control method and updates the control gain in real time according to the desired system parameters to enhance the robustness of the controller. Finally, the effectiveness of the offline neural network and online discrimination correction is verified by mathematical simulations, and the effectiveness and robustness of the adaptive control proposed in this paper are verified by comparative simulation.
The control system design for the reusable launch vehicles (RLVs), especially in the autonomous horizontal takeoff phase, is a highly challenging task. Significant issues arise due to the high nonlinearity, large uncertainties of aerodynamic coefficients as well as strong coupling among axes of the airframe. This paper studies autonomous takeoff control problem of the RLVs by the means of trajectory linearization control (TLC) and model predictive control (MPC) theory. The six degree of freedom dynamic model is firstly established, and the flight strategy of takeoff and climb stage is provided through the characteristic analysis of RLVs. Furthermore, the guidance law for the climbing phase is proposed via the TLC method against the high nonlinearity, and a speed based gain-schedule strategy is given under the consideration of both aerodynamic force and friction force. In order to eliminate the ground effect interference, an improved model predictive control approach is presented by introducing the online parameter estimation of the ground effect interaction coefficient, and a coupled model predictive controller is designed by introducing the feedback of sideslip angle into the roll control channel to eliminate the coupling effect. Finally, the performance of the design method for autonomous takeoff control of RLVs is demonstrated through the comparison simulation analysis.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.