Model Predictive Control and Proportional-Integral-Derivative Control in JuliaSim

Learn advanced control system design techniques in this comprehensive webinar focused on multiple-input, multiple-output (MIMO) systems with state and input constraints. Progress through increasingly sophisticated control methodologies, beginning with the fundamentals of autotuning Proportional-Integral-Derivative (PID) controllers and advancing to complex nonlinear Model Predictive Control (MPC) implementations. Explore these concepts using JuliaSim, a cutting-edge cloud-based modeling and simulation platform that combines scientific machine learning techniques with equation-based digital twin modeling to achieve up to 500x acceleration in simulation performance. Gain practical insights into implementing control strategies for complex systems while leveraging the powerful capabilities of modern simulation tools.