Open AccessAutopilot Design for a Compound Control Small-Scale Solid Rocket in the Initial Stage of Launch
Author(s) -
Tian Dong,
Zhao Chang,
Zhiguo Song
Publication year - 2019
Publication title -
international journal of aerospace engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.361
H-Index - 22
eISSN - 1687-5974
pISSN - 1687-5966
DOI - 10.1155/2019/4749109
Subject(s) - autopilot , control theory (sociology) , thrust , engineering , aerodynamics , solid fuel rocket , actuator , aerodynamic force , controller (irrigation) , attitude control , robustness (evolution) , rocket (weapon) , sliding mode control , aerospace engineering , control engineering , computer science , propellant , control (management) , physics , agronomy , biochemistry , chemistry , electrical engineering , nonlinear system , artificial intelligence , quantum mechanics , gene , biology
In this paper, an autopilot design method for a compound control small-scale solid rocket is proposed. The rocket has multiple actuators, including a flexible nozzle for pitching and yawing channels, aerodynamic fins for rolling channel, and lateral thrusters which work in on-off mode for all three channels. In order to keep the aircraft steady in the initial stage of launch when the dynamic pressure is low, the autopilot is aimed at optimizing the cooperation among the actuators. Firstly, without considering the discontinuous lateral thrust, the control law for flexible nozzle and aerodynamic fins is achieved via the sliding mode control approach. On this basis, an object to be controlled with choiceness is obtained for the lateral thrusters controlled loop. Secondly, the operation logic of lateral thrusters is programmed, regarding rolling moment as priority. Thirdly, after a continuous controller is obtained, a discretization method for the lateral thrusters control law is designed combining the characteristics of sliding mode control and Lyapunov’s stableness theorem. Finally, the fundamental cause why compound control improves the system stability is given theoretically. Simulation results validate the improved response performance and robustness against uncertainties and disturbance of the autopilot.