Control Theory in Industry, Robotics and Infrastructure

# Control Theory in Industry, Robotics and Infrastructure

## Control Theory in Industry, Robotics and Infrastructure

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##### Presentation Transcript

1. Control Theory in Industry, Robotics and Infrastructure Lachlan Blackhall and Tyler Summers

2. Motivating Example • You walk into your classroom and turn your air conditioning on to a temperature of 24 degrees. • The air conditioner turns on until the internal thermostat registers that the air temperature is 24 degrees then shuts off the air conditioner until the temperature rises again. • A simple controller is responsible for keeping you cool!

3. Systems Modelling

4. Control Components • A system • Possibly a mathematical model of that system. • A control goal • A sensor to observe the system • An actuator to influence the system • A control algorithm that tells the actuator how to behave based on the observations of the sensor. • A computer or analog circuit to link it together.

5. Differential Equations • Control is primarily concerned with systems that can be written as differential equations. • Almost everything can be written in this form so control really applies to any physical systems. • It all started with trying to apply external control to simple differential equations.

6. Industrial Applications • Control emerged as a way to automate: • Manufacturing • Assembly • Processing and Refinement • Has since been used successfully in additional areas: • Robotics • Infrastructure

7. Revisiting our Example • The thermostat is one of the simplest controllers you can create. • This type of controller is known as a bang-bang controller. • A bang–bang controller (on–off controller) is a feedback controller that switches abruptly between two states.

8. Bang-Bang Control • They are routinely used to control a plant that accepts a binary input, for example a heater or air conditioner. • Bang–bang controls are actually optimal controls in some cases, although they are also often implemented because of simplicity or convenience.

9. PID Control • PID stands for proportional–integral–derivative. • PID is a generic control loop feedback mechanism used in industrial control systems. • The control signal has three components based on the error between the observed operation and the nominal set point: • A proportional component • An integral component • A derivative component

10. PID Control (cont.) • Some history • Developed in the late 1800s • Initially trialled as a way to control US Navy ship steering. • Can be implemented mechanically, using analog electronics and now using digital electronics like FPGAs • Most commonly implemented in industry these days using programmable logic controllers.

11. PID Control (cont.) used with permission from http://commons.wikimedia.org/wiki/File:PID.svg

12. PID Control (cont.) • Heuristically: • P depends on the present error • I on the accumulation of past errors • D is a prediction of future errors, based on the current rate of change. • The weighted sum of these three actions is used to adjust the process via a control element or actuator.

13. PID Control (cont.) • In the absence of knowledge of the underlying process, a PID controller is the best controller. • The response of the controller can be described in terms of the responsiveness of the controller to an error, the degree to which the controller overshoots the set-point and the degree of system oscillation. • Note that the use of the PID algorithm for control does not guarantee optimal control of the system or system stability.

14. PID Control (cont.) • Some applications may require using only one or two actions to provide the appropriate system control. • This is achieved by setting the other parameters to zero. • A PID controller will be called a PI, PD, P or I controller in the absence of the respective control actions. • http://www.youtube.com/watch?v=ALVo4aJpcF0 – P vs PID Control

15. Demonstration • LEGO Mindstorms Line Following Robot – Bang-Bang vs P Controller • LEGO Mindstorms Segway Robot – PID Control

16. Applications of PID • Assembly • Robotics • SCADA • Building Control

17. Assembly • PID Controllers are vitally important to robots used for automated assembly. • Precision control was the technological breakthrough that allowed robotic assembly to become so commonplace. • Demonstrations: • http://www.youtube.com/watch?v=HPpTK2ezxL0 - 1936 Car Assembly Footage • http://www.youtube.com/watch?v=-_SxW_7v9is – BMW Assembly Plant Footage

18. Robotics • Beyond assembly industrial robots can perform a great many tasks including: • Welding • painting, • pick and place (such as packaging, palletizing and SMT) • product inspection, and testing • There are lots of other robots out there using PID control.

19. Robotics (cont.) • Demonstrations: • http://www.youtube.com/watch?v=Fxzh3pFr3Gs - Catching balls and darts (Lund) • http://www.youtube.com/watch?v=SOESSCXGhFo – ABB Challenge • http://www.youtube.com/watch?v=R8UeT9r4cmg - ASIMO • http://www.youtube.com/watch?v=cNZPRsrwumQ – BIG DOG

20. SCADA • How do you control a number of systems, and a number of controllers that are possibly spread out on a factory floor or over a large geographic footprint?

21. SCADA • SCADA (supervisory control and data acquisition) are industrial control systems (ICS) that monitor and control industrial, infrastructure, or facility-based processes. • Industrial processes include: • Manufacturing / production / assembly • Power generation, transmission and distribution • Wastewater collection and treatment • Oil and gas pipelines and refineries