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System and method for solving quadratic programming problems with bound constraints utilizing a semi-explicit quadratic programming solver
System and method for solving quadratic programming problems with bound constraints utilizing a semi-explicit quadratic programming solver
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机译:利用半显式二次规划求解器求解具有约束约束的二次规划问题的系统和方法
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摘要
A system and method for solving a quadratic programming optimization problem with bound constraints using a semi-explicit QP solver with respect to an embedded platform is presented. A linear system of equations associated with a matrix (e.g., a Karush-Kuhn-Tucker matrix, KKT system) can be solved at each iteration of the solver based on a factorization approach. A set of partial factors with respect to the QP problem can be pre-computed off-line and stored into a memory. The factorization process of the KKT matrix can then be finished on-line in each iteration of the semi-explicit QP solver in order to effectively solve the QP optimization problems. The QP problem can be solved utilizing a standard active-set approach and/or a partial explicit approach based on a processor utilization and memory usage.
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