Optimized FPGA Implementation of Model Predictive Control for Embedded Systems Using High-Level Synthesis Tool
IEEE Transactions on Industrial Informatics
Model predictive control is an optimization-based strategy for high-performance control that is attracting increasing interest. While model predictive control (MPC) requires the online solution of an optimization problem, its ability to handle multivariable systems and constraints makes it a very powerful control strategy specially for MPC of embedded systems, which have an ever increasing amount of sensing and computation capabilities. We argue that the implementation of MPC on field
... on field programmable gate arrays (FPGAs) using automatic tools is nowadays possible, achieving cost-effective successful applications on fast or resource-constrained systems. The main burden for the implementation of MPC on FPGAs is the challenging design of the necessary algorithms. We outline an approach to achieve a software-supported optimized implementation of MPC on FPGAs using high level synthesis tools and automatic code generation. The proposed strategy exploits the arithmetic operations necessaries to solve optimization problems to tailor an FPGA design, which allows a trade-off between energy, memory requirements, cost, and achievable speed. We show the capabilities and the simplicity of use of the proposed methodology on two different examples and illustrate its advantages over a microcontroller implementation. Index Terms-Field programmable gate array, model predictive control, high level synthesis. Fig. 1. Model predictive control.