Algebraic Dynamics, Optimization, and Control

AlgebraicControl.jl

Model predictive control (MPC) is an optimal control technique which involves solving a sequence of constrained optimization problems across a given time horizon. We present a novel Julia library that leverages our theoretical results to automate the implementation of correct-by-construction MPC problems in software.

Project team

Name	Member since	Degree	Program
Tyler Hanks	2021	PhD	CISE
Samuel Cohen	2024	—	—
Richard Samuelson	2024	PhD	—

Project articles

A Compositional Framework for First-Order Optimization

T. Hanks, M Klawonn, M Hale, E Patterson, JP FairbanksarxivSubmitted 2024

DOI

Generalized Gradient Descent is a Hypergraph Functor

T Hanks, M. Klawonn, J. FairbanksApplied Category TheorySubmitted March 2024

Modeling Model Predictive Control: A Category Theoretic Framework for Multistage Control Problems

Tyler Hanks, Baike She, Matthew Hale, Evan Patterson, Matthew Klawonn, James FairbanksAmerican Control ConferenceJul 2024

DOI

Characterizing Compositionality of LQR from the Categorical Perspective

Baike She, Tyler Hanks, James Fairbanks, Matthew HaleIEEE Conf. Decision and Control2023

DOI

An Algebraic Framework for Structured Epidemic Modeling

S. Libkind, A. Baas, M. Halter, E. Patterson, and J. P. FairbanksProc. of the Royal Society Phil. Trans.Aug 2022

DOI

Typed and stratified models with slice categories

S. Libkind (speaker), E. Patterson, A. Baas, M. Halter, J. FairbanksApplied Category Theory 2022Jul 2022

Operadic Modeling of Dynamical Systems: Mathematics and Computation

S. Libkind, A. Baas, E. J. Patterson, J. P. FairbanksApplied category Theory (Proceedings)Jul 2021

Link

AlgebraicDynamics: Compositional dynamical systems

S. Libkind, J. P. FairbanksJuliaCon, OnlineJul 2021