控制理论(社会学)
反推
稳健性(进化)
参数统计
计算机科学
非线性系统
控制器(灌溉)
四元数
趋同(经济学)
自适应控制
控制工程
控制(管理)
工程类
数学
人工智能
生物
基因
统计
几何学
量子力学
物理
生物化学
经济
化学
经济增长
农学
作者
Tao Jiang,Jiangshuai Huang,Bin Li
标识
DOI:10.1016/j.jfranklin.2020.03.021
摘要
This work draws inspiration from prescribed performance control, where a prescribed performance finite-time control framework is developed. A new finite-time form of performance function is defined to constrain the trajectory tracking errors. The proposed scheme provides a less-complex finite-time convergence guarantee for the closed-loop system. Besides, some required transient performances and steady-state precision can be preseted. Furthermore, the proposed framework combined with quaternion-based backstepping is employed to address the tracking problem of disturbed quadrotors. To amplify the robustness, composite learning approach which combines adaptive neural controller with nonlinear disturbance observer, is conducted to counteract the adverse effects from parametric uncertainties and time-varying external perturbations. Some comparative simulation results illustrate the superiority of the proposed flight controller. Additionally, the flight experiments are implemented to further demonstrate the effectiveness of the prescribed performance scheme.
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