Control Systems Based on the Work of Professor Andrew Alleyne Copyright © 2012 Board of Trustees, University of Illinois. All rights reserved.

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Presentation transcript:

Control Systems Based on the Work of Professor Andrew Alleyne Copyright © 2012 Board of Trustees, University of Illinois. All rights reserved.

2 What is a control system? A system designed to control an object automatically Decision making –Get information –Decide on action –Tell object to perform action Essential in nanotechnology

3 A toaster Question – how can we control a toaster? We want the bread to be brown, but not burned.

4 A toaster Question – how can we control a toaster? We can watch the bread. - Cheap to control - But we might forget

5 A toaster Question – how can we control a toaster? System can watch the bread. - Very accurate - Very expensive

6 A toaster Question – how can we control a toaster? We can time the bread. - Cheap control - Often works well enough

7 You try it Design a Lego Mindstorm system to travel from one end of the room to the other.

8 Control systems You will use Lego Mindstorms to follow a black line

9 Some important parts

10 Controller and IR tower Download program to RCX from IR tower Controls robot Runs program with green button RCX IR tower

11 Motor Use to make left wheel and right wheel turn Need 2, one for each side

12 Skid Use in place of front wheels Lower friction, tight turns

13 Let’s begin!

14 A toilet Question – how can we control a toilet? We want the water to fill, but not overfill.

15 A toilet Question – how can we control a toilet? We can watch the toilet. - Cheap to control - Might forget - Don’t want to wait

16 A toilet Question – how can we control a toilet? We can time the fill. - Cheap to control - Could be disastrous!

17 System can get feedback. - Very accurate A toilet Question – how can we control a toilet?

18 A toilet Question – how can we control a toilet? Answer – use water level to shut off valve

19 Controlling a system A key distinction is whether the system gets feedback Open loop – no feedbackClosed loop - feedback

20 Open loop The controller doesn’t monitor the consequences of its decisions Desired result Control command Controller Controlled system Actual result

21 Closed loop The controller DOES monitor the consequences of its decision. Modifies commands it gives to the system Desiredresult Control command Controller Controlled system Actual result Feedback(!) error Comparison

22 Example: Thermoregulation sweat glands nerve cells ref=98.6 body temp Disturbances High temp High activity core body temp body  Classic example of a Closed Loop Control System

23 The toaster Remember the toaster. Does it monitor the consequences of its actions? Is the toaster open loop or closed loop?

24 The toilet Is the toilet open loop or closed loop?

25 Open loop Engineers use open loop when they need to save money and performance isn’t critical Often timer based Toaster WasherDishwasher

26 Closed loop Used when high performance demands it

27 The present New features on cars are largely due to more microprocessors on board (more than 50 on today’s cars) Ford ECU

28 The future Trend is towards more and more control systems –Engine management –ABS systems –Cruise control –Climate control –Windows, doors, lights Control systems are not going away! Average Computer Content per Car (in Dollars)

29 Staying on the line How can we keep the robots on the straight line more precisely and consistently? What kind of controls can we use?

30 Light sensor Detect light on both sides of black line Need 2 Should be about 2 LEGO pegs apart

31 90° angle Use piece to point light sensor down

32 Let’s begin! Create a computer program with closed controls that will run your robot on a line Make adjustments to the robot and program as needed

33 Nanotechnology Was following a line a challenge? Imagine working with atoms and molecules!

34 Nanomanufacturing Aims to control, place, and sense nanometer scale elements of matter Positioning at the nanoscale is not easy Building nanostructures atom by atom requires control systems John Rogers Nick Fang and Placid Ferreira Picture from Professor John Rogers, UIUC

35 Scale

36 Scale

37 Nanoscale patterning

38 Conclusion Remember: –Controls pervasive in natural and human-made systems. –Difference between open loop and closed loop control. –High relevance to nanomanufacturing.