DC-TMPC: A tube-based MPC algorithm for systems that can be expressed as a difference of convex functions.
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Updated
Jul 28, 2022 - Python
DC-TMPC: A tube-based MPC algorithm for systems that can be expressed as a difference of convex functions.
Learning-based robust tube based MPC of nonlinear systems via difference of convex radial basis functions
This simulation file demonstrates a variant of Robust Tube MPC in which the initial nominal state is a decision variable. Theoretical background can be found at "Mayne, David Q., María M. Seron, and S. V. Raković. "Robust model predictive control of constrained linear systems with bounded disturbances." Automatica 41.2 (2005): 219-224."
Tube-Based Zonotopic Data Driven Predictive Control
Self-Tuning Tube-Based MPC Controller
Computationally tractable learning-based nonlinear tube MPC using difference of convex neural network dynamic approximation
This repository contains simulation demonstration for the paper: "MPC for tracking piecewise constant references for constrained linear systems" - D. Limon et al.
Simulation for a robust steering assist controller
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