控制理论(社会学)
四轴飞行器
PID控制器
增益调度
非线性系统
控制器(灌溉)
系统标识
控制工程
噪音(视频)
控制系统
递归最小平方滤波器
工程类
计算机科学
自适应滤波器
控制(管理)
温度控制
算法
人工智能
物理
农学
电气工程
软件工程
量子力学
数据建模
图像(数学)
生物
航空航天工程
作者
Leszek Cedro,Krzysztof Wieczorkowski,Adam Szcześniak
出处
期刊:Acta Mechanica et Automatica
日期:2023-12-30
卷期号:18 (1): 29-39
标识
DOI:10.2478/ama-2024-0004
摘要
Abstract In adaptive model-based control systems, determining the appropriate controller gain is a complex and time-consuming task due to noise and external disturbances. Changes in the controller parameters were assumed to be dependent on the quadcopter mass, which was the process variable. A nonlinear model of the plant was used to identify the mass, employing the weighted recursive least squares (WRLS) method for online identification. The identification and control processes involved filtration using differential filters, which provided appropriate derivatives of signals. Proportional integral derivative (PID) controller tuning was performed using the Gauss–Newton optimisation procedure on the plant. Differential filters played a crucial role in all the developed control systems by significantly reducing measurement noise. The results showed that the performance of classical PID controllers can be improved by using differential filters and gain scheduling. The control and identification algorithms were implemented in an National Instruments (NI) myRIO-1900 controller. The nonlinear model of the plant was built based on Newton’s equations.
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