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How to Implement a Kalman Filter in Simulink

This video demonstrates how you can estimate position using a Kalman filter in Simulink. Using MATLAB and Simulink, you can implement linear time-invariant or time-varying Kalman filters. In this video, a inverted pendulum system is modeled in Simulink using Simscape Multibody™. The angle of the pendulum and position of the cart are estimated using the Kalman filter block which is available in the Control System Toolbox™. The video shows how to configure Kalman filter block parameters such as the system model, initial state estimates, and noise characteristics. - Kalman Filter video series: https://bit.ly/3z8Nvrz - Deriving the state space model: https://bit.ly/3w4beXY - Design and use Kalman filters in MATLAB and Simulink: https://bit.ly/3v0wzR4 0:00 Background 0:14 Inverted Pendulum Simulink Model 0:55 Why use a Kalman Filter 1:40 Implementing Kalman Filter in Simulink 3:40 Results and Improved Filters -------------------------------------------------------------------------------------------------------- Get a free product trial: https://goo.gl/ZHFb5u Learn more about MATLAB: https://goo.gl/8QV7ZZ Learn more about Simulink: https://goo.gl/nqnbLe See what's new in MATLAB and Simulink: https://goo.gl/pgGtod © 2021 The MathWorks, Inc. MATLAB and Simulink are registered trademarks of The MathWorks, Inc. See www.mathworks.com/trademarks for a list of additional trademarks. Other product or brand names may be trademarks or registered trademarks of their respective holders.