Understanding Kalman Filters, Part 7: How to Use an Extended Kalman Filter in Simulink

This video demonstrates how you can estimate the angular position of a nonlinear pendulum system using an extended Kalman filter in Simulink. Download examples and code - Design and Simulate Kalman Filter Algorithms: https://bit.ly/2Iq8Hks Design and use Kalman filters in MATLAB and Simulink: https://goo.gl/SVA9IK Download model: http://bit.ly/2Qi3hgw Watch other MATLAB Tech Talks: https://goo.gl/jD0uOH Get a free Product Trial: https://goo.gl/C2Y9A5 In this video, a simple pendulum system is modeled in Simulink using Simscape Multibody™. The angular position of the nonlinear pendulum system is estimated using the Extended Kalman Filter block that is available in Control System Toolbox™. The video shows how to specify Extended Kalman Filter block parameters such as the state transition and measurement functions, initial state estimates, and noise characteristics. If you want to run state estimation on your hardware in real time, you can generate C/C++ code from the Extended Kalman Filter block in Simulink, and deploy it to your hardware. : You can find the Simulink model used in this video here: https://goo.gl/XSVvJx