.png){kind=icon}
Return
Constrained quadratic programming techniques for control allocation
.png){kind=icon}
PRE
AI
DOI：10.1109/TCST.2005.860516.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
The paper considers the objective of optimally specifying redundant control effectors under constraints, a problem commonly referred to as control allocation. The problem is posed as a mixed l(2)-norm optimization objective and converted to a quadratic programming formulation. The implementation of an interior-point algorithm is presented. Alternative methods including fixed-point and active set methods are used to evaluate the reliability, accuracy and efficiency of a primal-dual interior-point method. While the computational load of the interior-point method is found to be greater for problems of small size, convergence to the optimal solution is also more uniform and predictable. In addition, the properties of the algorithm scale favorably with problem size.
Keywords:
control allocation
flight control
interior-point methods
quadratic programming
redundant control effectors
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
IF:
3.9
Papers:
4.9K
Citations:
1.7W
Organization
No organization information available
Cited Papers
.png){kind=icon}
ShareSave
ShareSaveShareSaveShareSaveShareSave
ShareSave
View more