Difference between revisions of "Is there room for learning in control systems theory?"
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* Adaptive control can be considered a type of learning (based on | * Adaptive control can be considered a type of learning (based on | ||
adjusting either a model of the plant or the parameters of a control). | adjusting either a model of the plant or the parameters of a control). | ||
--[[User:Fuller|Sawyer Fuller]] 00:21, 2 October 2007 (PDT) | --[[User:Fuller|Sawyer Fuller]] 00:21, 2 October 2007 (PDT) | ||
updated 15:52, 8 October 2007 (PDT) | |||
[[Category: CDS 101/110 FAQ - Lecture 1-1]] | [[Category: CDS 101/110 FAQ - Lecture 1-1]] | ||
[[Category: CDS 101/110 FAQ - Lecture 1-1, Fall 2007]] | [[Category: CDS 101/110 FAQ - Lecture 1-1, Fall 2007]] | ||
Latest revision as of 22:52, 8 October 2007
In the "sensing," "computation," and "actuation" blocks of a control system, learning happens in the computation block. Broadly speaking learning involves techniques for exploring the parameter space and measuring the system's performance relative to a set of criteria. For example, one might use a learning controller to optimize the gains in a PID controller (proportional-integral-derivative, this is a standard controller type we'll learn more about later in the course). We won't be covering machine learning in this course, but it is an interesting area in controls.
from Richard:
- In robotics, there is a large literature on iterative learning
control, when you are performing a repetitive task. This mainly involves turning the trajectory generation (feedforward).
- Adaptive control can be considered a type of learning (based on
adjusting either a model of the plant or the parameters of a control).
--Sawyer Fuller 00:21, 2 October 2007 (PDT)
updated 15:52, 8 October 2007 (PDT)
