Title
Design and implementation of an FPGA-based piecewise affine Kalman Filter for Cyber-Physical Systems
Degree Type
Dissertation
Date of Award
2016
Degree Name
Doctor of Philosophy
Department
Electrical and Computer Engineering
Major
Computer Engineering
First Advisor
Joseph Zambreno
Abstract
The Kalman Filter is a robust tool often employed as a process observer in Cyber-Physical Systems. However, in the general case the high computational cost, especially for large plant models or fast sample rates, makes it an impractical choice for typical low-power microcontrollers. Furthermore, although industry trends towards tighter integration are supported by powerful high-end System-on-Chip software processors, this consolidation complicates the ability for a controls engineer to verify correct behavior of the system under all conditions, which is important in safety-critical systems and systems demanding a high degree of reliability.
Dedicated Field-Programmable Gate Array (FPGA) hardware can provide application speedup, design partitioning in mixed-criticality systems, and fully deterministic timing, which helps ensure a control system behaves identically to offline simulations. This dissertation presents a new design methodology which can be leveraged to yield such benefits. Although this dissertation focuses on the Kalman Filter, the method is general enough to be extended to other compute-intensive algorithms which rely on state-space modeling.
For the first part, the core idea is that decomposing the Kalman Filter algorithm from a strictly linear perspective leads to a more generalized architecture with increased performance compared to approaches which focus on nonlinear filters (e.g. Extended Kalman Filter). Our contribution is a broadly-applicable hardware-software architecture for a linear Kalman Filter whose operating domain is extended through online model swapping. A supporting application-agnostic performance and resource analysis is provided.
For the second part, we identify limitations of the mixed hardware-software method and demonstrate how to leverage hardware-based region identification in order to develop a strictly hardware-only Kalman Filter which maintains a large operating domain. The resulting hardware processor is partitioned from low criticality software tasks running on a supervising software processor and enables vastly simplified timing validation.
Copyright Owner
Aaron Mills
Copyright Date
2016
Language
en
File Format
application/pdf
File Size
98 pages
Recommended Citation
Mills, Aaron, "Design and implementation of an FPGA-based piecewise affine Kalman Filter for Cyber-Physical Systems" (2016). Graduate Theses and Dissertations. 15774.
https://lib.dr.iastate.edu/etd/15774