CDS 110b: Linear Quadratic Regulators
|CDS 110b||← Schedule →||Project|
This lecture provides a brief derivation of the linear quadratic regulator (LQR) and describes how to design an LQR-based compensator. The use of integral feedback to eliminate steady state error is also described.
- Lecture Presentation
- Homework 3 - due 30 Jan 08
- pvtol_lqr.m - MATLAB script demonstrating LQR design
References and Further Reading
- R. M. Murray, Optimization-Based Control. Preprint, 2008: Chapter 2 - Optimal Control
- Lewis and Syrmos, Section 3.4 - this follows the derivation in the notes above. I am not putting in a scan of this chapter since the course text is available, but you are free to have a look via Google Books.
- Friedland, Ch 9 - the derivation of the LQR controller is done differently, so it gives an alternate approach.
Frequently Asked Questions
Q: What do you mean by penalizing something, from "penalizes" state error?
According to the form of the quadratic cost function , there are three quadratic terms such as , , and . When and if is relative big, the value of will have bigger contribution to the value of . In order to keep small, must be relatively small. So selecting a big can keep in small value regions. This is what the "penalizing" means.
So in the optimal control design, the relative values of , , and represent how important , , and are in the designer's concerns.
Zhipu Jin,13 Jan 03