In this section
@inproceedings{Khusainov:2017:10.1016/j.ifacol.2017.08.1413,
author = {Khusainov, B and Kerrigan, EC and Suardi, A and Constantinides, GA},
doi = {10.1016/j.ifacol.2017.08.1413},
pages = {11877--11882},
publisher = {IFAC / Elsevier},
title = {Nonlinear predictive control on a heterogeneous computing platform},
url = {http://dx.doi.org/10.1016/j.ifacol.2017.08.1413},
year = {2017}
}
TY - CPAPER
AB - Nonlinear Model Predictive Control (NMPC) is an advanced control technique that often relies on computationally demanding optimization and integration algorithms. This paper proposes and investigates a heterogeneous hardware implementation of an NMPC controller based on an interior point algorithm. The proposed implementation provides flexibility of splitting the workload between a general-purpose CPU with a fixed architecture and a field-programmable gate array (FPGA) to trade off contradicting design objectives, namely performance and computational resource usage. A new way of exploiting the structure of the Karush-Kuhn-Tucker (KKT) matrix yields significant memory savings, which is crucial for reconfigurable hardware. For the considered case study, a 10x memory savings compared to existing approaches and a 10x speedup over a software implementation are reported. The proposed implementation can be tested from Matlab using a new release of the Protoip software tool, which is another contribution of the paper. Protoip abstracts many low-level details of heterogeneous hardware programming and allows quick prototyping and processor-in-the-loop verification of heterogeneous hardware implementations.
AU - Khusainov,B
AU - Kerrigan,EC
AU - Suardi,A
AU - Constantinides,GA
DO - 10.1016/j.ifacol.2017.08.1413
EP - 11882
PB - IFAC / Elsevier
PY - 2017///
SP - 11877
TI - Nonlinear predictive control on a heterogeneous computing platform
UR - http://dx.doi.org/10.1016/j.ifacol.2017.08.1413
UR - http://hdl.handle.net/10044/1/45094
ER -