Open AccessTake-Off Trajectory Optimization of Tilt-rotor Aircraft Based on Direct Allocation Method
Author(s) -
Jiaxin Gao,
Qian Zhang,
Jiyang Chen,
Xueyun Wang
Publication year - 2020
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/768/4/042004
Subject(s) - trajectory optimization , control theory (sociology) , trajectory , nonlinear programming , rotor (electric) , computer science , tilt (camera) , matlab , nonlinear system , optimal control , process (computing) , state variable , mathematical optimization , engineering , control (management) , mathematics , mechanical engineering , physics , astronomy , artificial intelligence , quantum mechanics , thermodynamics , operating system
During the take-off stage, the tilt-rotor aircraft’s actuator is redundant and difficult to control. In order to take off more quickly and safety reach horizontal flight state with less power consumption, the take-off trajectory is necessary to be optimized. this paper introduces the direct allocation method to optimize the take-off trajectory of tilt-rotor aircraft. Firstly, the dynamic model of the take-off stage of the tilt-rotor aircraft is established. According to the actual flight conditions, the constraints and the optimization objective function of the take-off process are established. Then, the entire take-off process is divided into several segments according to time, and the continuous optimal control problem is discretized into a nonlinear programming problem by using the direct allocation method. The state and control variables at each segment point and midpoint are taken for optimization. and then the optimized variables are fitted by the third-order Simpson method. Finally, GPOPS toolbox in MATLAB was used to solve the nonlinear programming problem. The simulation results show that the optimized take-off trajectory can well meet the boundary constraints, and its solutions are stable.