Linear Quadratic Gaussian (LQG) regulators

In summary, LQG regulators work by using a quadratic cost to control a certain aspect. This can be further explored through textbooks such as Troutman and Burns for a better understanding.
  • #1
Dustinsfl
2,281
5
How do LQG regulators work?

I have read the Matlab page about them, Wikipedia, and a few schools notes on them but it isn't either clear to me or they are not adequately explaining how they work. All see is that we want to control something giving a quadratic cost.

Is there are more robust way to explain this (greater depth or detail for a better understanding besides control and quadratic cost)?
 
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  • #2
I can't say I know about LQR's as much as I should, but I do know that my graduate school was pretty big on them, and the standard book we used was Troutman. There's a discussion of it in there. I also notice that John Burns, a prof at VT known for this stuff, has a textbook which they're using for next year. Perhaps your school's library has these books. I should think the Burns book would be excellent. I always heard good things about Burns as a prof.
 

Related to Linear Quadratic Gaussian (LQG) regulators

1. What is a Linear Quadratic Gaussian (LQG) regulator?

A Linear Quadratic Gaussian (LQG) regulator is a control system designed to regulate a process in the presence of both process disturbances and measurement noise. It combines two control techniques, the Linear Quadratic Regulator (LQR) and the Kalman filter, to optimize the control performance in a noisy environment.

2. How does an LQG regulator work?

An LQG regulator works by using the LQR to calculate the optimal control inputs based on the current state of the system and the desired state. The Kalman filter then estimates the current state of the system based on noisy measurements. The estimated state is then used by the LQR to generate the optimal control inputs, which are applied to the system to regulate it.

3. What are the advantages of using an LQG regulator?

Some advantages of using an LQG regulator include its ability to handle both process disturbances and measurement noise, its ability to optimize control performance in a noisy environment, and its simple and efficient implementation compared to other control techniques.

4. What are the limitations of an LQG regulator?

One limitation of an LQG regulator is that it assumes a linear system and Gaussian noise. This means it may not perform well for highly nonlinear systems or systems with non-Gaussian noise. Additionally, the performance of an LQG regulator is highly dependent on the accuracy of the system model and noise estimates.

5. In what applications is an LQG regulator commonly used?

An LQG regulator is commonly used in applications where precise control is required, such as aerospace and automotive systems, robotics, and industrial processes. It is also commonly used in systems that are subject to disturbances and noise, such as navigation and tracking systems.

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