Embedded Online Optimization for Model Predictive Control at Megahertz Rates

DOI10.1109/TAC.2014.2351991zbMath1360.93235arXiv1303.1090OpenAlexW1977284223MaRDI QIDQ2982924

Eric C. Kerrigan, Manfred Morari, Stefan Richter, Paul J. Goulart, Juan L. Jerez, George A. Constantinides

Publication date: 16 May 2017

Published in: IEEE Transactions on Automatic Control (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1303.1090

Mathematics Subject Classification ID

Related Items (22)

A primal‐dual active‐set method for distributed model predictive control ⋮ An efficient bounded-variable nonlinear least-squares algorithm for embedded MPC ⋮ Proportional-integral projected gradient method for conic optimization ⋮ A Gauss-Seidel type solver for the fast computation of input-constrained control systems ⋮ Distributed model predictive control for linear systems under communication noise: algorithm, theory and implementation ⋮ Embedded MPC Controller Based on Interior-Point Method with Convergence Depth Control ⋮ Metric selection in fast dual forward-backward splitting ⋮ Massively parallelizable proximal algorithms for large‐scale stochastic optimal control problems ⋮ Energy-efficient real-time scheduling for two-type heterogeneous multiprocessors ⋮ Augmented Lagrangian optimization under fixed-point arithmetic ⋮ On closed-loop dynamics of ADMM-based MPC ⋮ OSQP: An Operator Splitting Solver for Quadratic Programs ⋮ Automatically generated embedded model predictive control: Moving an industrial PC‐based MPC to an embedded platform ⋮ Infeasibility detection in the alternating direction method of multipliers for convex optimization ⋮ A parallel Newton-type method for nonlinear model predictive control ⋮ FORCES NLP: an efficient implementation of interior-point methods for multistage nonlinear nonconvex programs ⋮ A Hamiltonian decomposition for fast interior-point solvers in model predictive control ⋮ Real-time model predictive control based on dual gradient projection: Theory and fixed-point FPGA implementation ⋮ Soft inequality constraints in gradient method and fast gradient method for quadratic programming ⋮ Symmetry and motion primitives in model predictive control ⋮ Using stochastic programming to train neural network approximation of nonlinear MPC laws ⋮ ParNMPC – a parallel optimisation toolkit for real-time nonlinear model predictive control

This page was built for publication: Embedded Online Optimization for Model Predictive Control at Megahertz Rates