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Implementation of mixed-integer programming on embedded system

By Jakub Novák and Petr Chalupa


One o. The most widespread modern control strategies i. The discrete-time Model Predictive Control (MPC) method which require. The solution o. The quadratic programming problem. For systems with binary input variable. The quadratic problem is replaced by more challenging Mixed-Integer Quadratic Programming (MIQP) problem. The objective of this work i. The implementation of MIQP problem solver in a low power embedded computing platform with limited computational power and limited memory. The MIQP problem is solved using branch-and-bound method an. The solution o. The relaxed original quadratic problems with equality and inequality constraints solved i. The nodes of a binary tree is found with interior-point algorithm. A simulation study o. The reserve constrained economic dispatch problem for power generators with prohibited zones is presented. Simulation results sho. The applicability o. The proposed solver for small size MIQP problems. © 2015 The Authors. Published by Elsevier Ltd. This is an open access article unde. The CC BY-NC-ND license

Topics: Branch-and-bound, Economic dispatch, Embedded system, Mixed-integer quadratic programming, Optimization
Publisher: Elsevier BV
Year: 2015
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