Why the Riccati Equation Is important for LQR Control

This Tech Talk looks at an optimal controller called linear quadratic regulator, or LQR, and shows why the Riccati equation plays such an important role in solving it efficiently.

The talk walks through three different ways that the LQR problem can be solved: an intuitive, but ultimately inefficient brute force way; a more efficient learning algorithm way; and then the most efficient approach, which is accomplished analytically using the algebraic Riccati equation.

Want to see all the references in a nice, organized list? Check out this journey on Resourcium: https://bit.ly/3NOIWeg

- Design and Simulate Kalman Filter Algorithms: https://bit.ly/3Obq3n5
- Explanation of “Completing the Square” for LQR by Laurent Lessard: https://bit.ly/3Dio9e5
- Train Custom LQR Agent: https://bit.ly/450RxBN
- Linear-Quadratic Regulator (LQR) Design: https://bit.ly/44EX5l5

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