A co-processor FPGA platform for the implementation of real-time model predictive control

In order to effectively control nonlinear and multivariable models, and to incorporate constraints on system states, inputs and outputs (bounds, rate of change), a suitable (sometimes necessary) controller is model predictive control (MPC). MPC is an optimization-based control scheme that requires a...

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Bibliographic Details
Main Authors: Bleris, L.G., Vouzis, P.D., Arnold, M.G., Kothare, M.V.
Format: Conference Proceeding
Language:English
Subjects:
Arithmetic
Coprocessors
Embedded software
Field programmable gate arrays
Hardware
Matrix decomposition
Nonlinear control systems
Optimal control
Predictive control
Predictive models
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Description
Summary:In order to effectively control nonlinear and multivariable models, and to incorporate constraints on system states, inputs and outputs (bounds, rate of change), a suitable (sometimes necessary) controller is model predictive control (MPC). MPC is an optimization-based control scheme that requires abundant matrix operations for the calculation of the optimal control moves. In this work we propose a mixed software and hardware embedded MPC implementation. Using a codesign step and based on profiling results, we decompose the optimization algorithm into two parts: one that fits into a host processor and one that fits into a custom made unit that performs the computationally demanding arithmetic operations. The profiling results and information on the co-processor design are provided
ISSN:0743-1619
2378-5861
DOI:10.1109/ACC.2006.1656499