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Explore the implementation of a Kalman Filter in Matlab using an inverted pendulum on a cart example. Dive into this comprehensive lecture that follows Chapter 8 of "Data-Driven Science and Engineering: Machine Learning, Dynamical Systems, and Control" by Brunton and Kutz. Learn about common filters, calm filters, dynamical systems, and simulation techniques. Gain practical insights into control theory and state estimation through this hands-on demonstration. Access additional resources, including chapter materials and the full textbook, to deepen your understanding of data-driven approaches in science and engineering.
Syllabus
Introduction
Kalman Filter
Common Filter
Calm Filter
Dynamical System
Simulation
Simulate
Taught by
Steve Brunton