Adaptive Optimal Flight Control for a Fixed-wing Unmanned Aerial Vehicle using Incremental Value Iteration

Yifei Li, E. Kampen
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Abstract

This paper deals with the design of an adaptive optimal controller for a fixed-wing Unmanned Aerial Vehicle(UAV) using an incremental value iteration algorithm. The incremental model is firstly introduced to linearize a nonlinear system. The recursive least squares(RLS) identification algorithm is then used to identify the incremental model. Based on incremental control, the incremental value iteration algorithm is developed for a nonlinear optimal control problem. Moreover, this algorithm is applied to longitudinal attitude tracking of a fixed-wing unmanned aerial vehicle. Simulation results show that the designed adaptive flight controller is robust to variations in initial value of the angle of attack.
基于增量值迭代的固定翼无人机自适应最优飞行控制
本文研究了一种基于增量值迭代算法的固定翼无人机自适应最优控制器的设计。首先引入增量模型对非线性系统进行线性化。然后采用递归最小二乘(RLS)识别算法对增量模型进行识别。针对一类非线性最优控制问题,提出了基于增量控制的增量值迭代算法。并将该算法应用于固定翼无人机的纵向姿态跟踪。仿真结果表明,所设计的自适应飞行控制器对迎角初始值的变化具有较强的鲁棒性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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