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Accelerating sequential least squares active set control allocation
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DOI：10.1016/j.conengprac.2025.106621.png)
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Abstract
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• The computational load of Sequential Least Squares Active Set is reduced by 50 %. • The QR decomposition is faster than the LDLT for Control Allocation problems. • Redistributed Scaled Pseudoinverse and Sequential Least Squares are equally accurate. • Aborting Active Set Control Allocation after m iterations is a valid compromise. • Warm-starting control allocation algorithms is not necessarily faster.
Keywords:
Control allocation
Sequential least squares
Quadratic programming
Numerical efficiency
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