Tools for Non-Linear Model Predictive Control
Learn non-linear Model-Predictive Control (MPC) to develop a lane-changing controller in this real-time demo using JuliaSim Control.
Wednesday, March 29th | 12:30 PM ET (US)
Tools for Non-Linear Model Predictive Control (MPC)
Learn non-linear Model-Predictive Control (MPC) to develop a lane-changing controller in this real-time demo using JuliaSim Control. In non-linear MPC you have the advantage of incorporating a plant model with non-linear dynamics; a non-quadratic cost function with high interpretability; and non-linear constraints. In this webinar, we will review JuliaSim Control's suite of tools to design model predictive controllers.
Using a realistic case study of controlling a self-driving car, you'll learn to:
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Build: simple dynamical models using Julia
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Specify: reference trajectories and other constraints to be satisfied by the controller
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Analyze: the final synthesized controller to understand its performance
Basic familiarity with modeling and simulation is all you need to amplify your skills. Register Now.
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Dr. Ranjan Anantharaman
Sales Engineer
Ranjan has a PhD in Mathematics & Computational Science from the Massachusetts Institute of Technology. He is a sales engineer at JuliaHub, where he helps customers leverage modern computational methods through JuliaSim.