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JuliaHub Modeling Platform - JuliaSim Control Non-Linear

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.

Register for Webinar Now

 
WEBINAR
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:

  • Build: simple dynamical models using Julia

  • Specify: reference trajectories and other constraints to be satisfied by the controller

  • 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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Meet Your Speaker

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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.

 

JuliaSim Control 

  • Model-predictive control (MPC) for linear and nonlinear systems

  • Robust MPC for uncertain systems

  • GUI apps for autotuning and model reduction

  • PID autotuning to automate workflows and quickly tune PID controllers