The DuQuad optimization toolbox solves convex quadratic programs using Dual First Order Optimization Algorithms. The algorithms has predictable and fast convergence, low memory footprint, and uses only basic arithmetic and logical operations. DuQuad and is therefore suited to be utilized by real-time applications running on low-cost HW such as simple microcontrollers. DuQuad has an user friendly Matlab interface for maximum productivity, and the algorithms are implemented in efficient C-code. The SW is open source and can be downloaded from the git repository.
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References in zbMATH (referenced in 2 articles )
Showing results 1 to 2 of 2.
- Englert, Tobias; Völz, Andreas; Mesmer, Felix; Rhein, Sönke; Graichen, Knut: A software framework for embedded nonlinear model predictive control using a gradient-based augmented Lagrangian approach (GRAMPC) (2019)
- Necoara, Ion; Patrascu, Andrei; Nedić, Angelia: Complexity certifications of first-order inexact Lagrangian methods for general convex programming: application to real-time MPC (2015)