线性二次高斯控制
控制理论(社会学)
最优投影方程
控制器(灌溉)
鲁棒控制
线性二次调节器
工程类
控制工程
噪音(视频)
理论(学习稳定性)
最优控制
控制系统
计算机科学
数学
数学优化
控制(管理)
图像(数学)
农学
人工智能
生物
机器学习
电气工程
标识
DOI:10.1061/(asce)as.1943-5525.0000712
摘要
Against a background of various techniques for gust load alleviation (GLA), this paper aims at proposing an improved linear quadratic Gaussian (LQG) method, which is robust to variations of flight parameters, structural parameters, and modeling errors and suitable for application in structure/control design optimization. This new technique differs from the traditional LQG methodology by the introduction of properly constructed fictitious high-frequency noise. Furthermore, to accurately measure the stability margins of the multi-input multi-output (MIMO) controllers, a variable-structure μ analysis method is proposed. The parameters of the Dryden continuous gust model are adjusted according to the structural natural frequencies to meet the design requirements, and model reduction combined with input signal scaling is applied to reduce the controller order. Using a general transport aircraft (GTA) model, the robust performance and robust stability of the improved LQG method are compared with those of modern robust controllers, including the H∞ controller and the μ-synthesis controller. The numerical results demonstrate the successful application of this new technique.
科研通智能强力驱动
Strongly Powered by AbleSci AI