Embedded Online Optimization for Model Predictive Control at Megahertz Rates
Embedded Online Optimization for Model Predictive Control at Megahertz Rates
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DOI：
10.1109/tac.2014.2351991
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发表时间：
2013-03
影响因子：
6.8
通讯作者：
J. Jerez;P. Goulart;S. Richter;G. Constantinides;E. Kerrigan;M. Morari
中科院分区：
文献类型：
--
作者：
J. Jerez;P. Goulart;S. Richter;G. Constantinides;E. Kerrigan;M. Morari
Faster, cheaper, and more power efficient optimization solvers than those currently possible using general-purpose techniques are required for extending the use of model predictive control (MPC) to resource-constrained embedded platforms. We propose several custom computational architectures for different first-order optimization methods that can handle linear-quadratic MPC problems with input, input-rate, and soft state constraints. We provide analysis ensuring the reliable operation of the resulting controller under reduced precision fixed-point arithmetic. Implementation of the proposed architectures in FPGAs shows that satisfactory control performance at a sample rate beyond 1 MHz is achievable even on low-end devices, opening up new possibilities for the application of MPC on embedded systems.
