Automatic control systems 2/15/05 10:07 AM

Automatic control systems Feedforward - open loop systems,

• early example: Jacquard loom of 1801

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• set of punched cards programmed the patterns to be woven by the loom, and no information from the process or results was used to correct the loom operation.

Feedback – closed loop systems

• systems feed back information from the process to control the operation of the machine

• earliest closed loop systems was that used by the Romans to maintain water levels in their aqueducts by means of floating valves

• • windmills were the spawning ground of several control systems,

for example the sails were automatically kept into the wind by means of a fantail (1745), as shown below; centrifugal governors were used to control the speed of the millstones (1783), and the speed of rotation of the sails was automatically controlled by roller reefing (1789)

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Why control systems?

• many variables can be controlled by humans, however: • in practice this may be

o impossible/difficult o costly o undesirable because of the need for continuous operation in a

hazardous environment (large forces, fast responses, etc.) • human reaction time is about 0.3 seconds – too slow!

Theoretical analysis of control systems

• first published by Maxwell, 19th century

• • theory enables computerized control

o industrial applications o animation applications

Feedback is essential!

• Closed loop systems are the way to go • Block diagram of a generic closed loop system:

• • The output can affect the input because of the feedback loop. • The Appendix to these notes contains an example of the analysis of

a simple control system. • Higher level control and state machines

o Consider a running human being

o Model the human as several rigid pieces connected by hinges this is an articulated figure, and we will study this more

as the class progresses

• • Prof. Jessica Hodgins (now at CMU) led many of the developments

in designing controllers to simulate human activities using dynamically-driven articulated figures.

• People are very attuned to the subtleties of human appearance and motion, so it’s a challenge!

• Let’s divide this task into a hierarchy of controls o LOW LEVEL – control each joint servo (a servo is a small

motor that applies torque to a joint) o MID LEVEL – control each phase of the gait (a gait is a

person’s manner of walking) o HIGH LEVEL – determine where the person should run

• How do we achieve these? o LOW LEVEL – simple closed-loop controller that has a desired

angular position or angular velocity and measures the current angular position/velocity.

o MID LEVEL – state machines, as we discuss below o HIGH LEVEL – Demetri Terzopoulos will discuss this on

Thursday • First, let’s talk about what we are trying to control, i.e., the human

body o a bunch of “rigid” pieces o connected by joints

o o sometimes knees and other joints can store energy (in

tendons), acting as a hinge spring

o we need to know some data about the body

o State machines

• running is a cyclic behavior • at each “stage” the muscles have different roles/responsibilities • some parts of the body may be active (i.e., a stance leg) or passive

(i.e., a swinging leg). o The active parts achieve the desired motion, o but the passive parts play a key role too: they move so as to

reduce the overall disturbance on the body. • State machines may be represented in a block diagram:

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• or they may be represented in a table:

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2/15/05 10:07 AM

2/15/05 10:07 AM