Difference between revisions of "Is there room for learning in control systems theory?"
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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. | 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). | |||
--[[User:Fuller|Sawyer Fuller]] 00:21, 2 October 2007 (PDT) | --[[User:Fuller|Sawyer Fuller]] 00:21, 2 October 2007 (PDT) | ||
Revision as of 22:50, 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)
