1
How to Improve your PID Controller

           Javier Gutierrez
      LabVIEW Product Marketing



                       ...
Benefits of Advanced Control and Tuning
                                       Model-based              Manual
• A poorly ...
Agenda

• What is PID?
• How to improve performance
   Hardware considerations
   Upgrade PID Algorithm
   Advanced Con...
Agenda

• What is PID?
• How to improve performance
   Hardware considerations
   Upgrade PID Algorithm
   Advanced Con...
What is PID
•   Set Point (SP) – Desired control point
•   Output (OP) – Controller output
•   Process Variable (PV) – Pla...
PID Parameters
• Proportional
      Drive to setpoint
      Error → 0, OP → 0
      “Steady-state error”
• Integral
   ...
System to control




                    8
PID Implementation Demo




                          9
PID Control – Pros and Cons

• Advantages
   Proven
   Easy to implement

• Disadvantages
   Not easy to tune
   Not s...
Agenda

• What is PID?
• How to improve performance
   Hardware considerations
   Upgrade PID Algorithm
   Advanced Con...
How to program PID


                        Function Blocks
Windows/Real Time




 FPGA                Control and Simula...
Benefits of Higher Loop Rates




                           13
PID Loop rates



                                    1 MHz

                          100 kHz

                 25 kHz


...
Die Casting Machine
The movement of the aluminium injection plunger controlled in a steady
closed loop at a speed varying ...
Agenda

• What is PID?
• How to improve performance
   Hardware considerations
   Improve PID Algorithm
   Advanced Con...
Upgrade your PID


Disturbances       Feed-forward
Non Linear         Gain Scheduling
Time Variant       Adaptive PID




...
Feed-Forward
• Commonly used to compensate for a
  measurable external disturbance before it affects
  a controlled variab...
Gain Scheduling
• Used to change gain on real-time depending on
  OV.
• Bumpless transfers




                           ...
Adaptive PID
• Mixed of On-Line system identification and
  common PID control.
• Can handle time-variant systems




    ...
Agenda

• What is PID?
• How to improve performance
   Hardware considerations
   Upgrade PID Algorithm
   Advanced Con...
Advanced Controllers

National Instruments
•   Optimal Controllers (LQR, LQG)
•   Model Predictive Control (MPC)
•   Kalma...
How to create an advanced Controller


                           Control Design
• Datalogging                            ...
Temp Chamber - Experiment




                        24
Plant Modeling - Validation




                              25
MPC Control Design




                     26
MPC Control Prototype




                        27
Advanced Controllers

• Pros/Cons




                       28
Agenda

• What is PID?
• How to improve performance
   Hardware considerations
   Upgrade PID Algorithm
   Advanced Con...
Conclusions

• PID
• Consider
   Upgrading hardware
   Enhance PID Algorithm
   Upgrading Control Algorithm




       ...
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How To Improve PID

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Presentation given during NIWeek 2008 about basics on PID and tips on how to improve it

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How To Improve PID

  1. 1. 1
  2. 2. How to Improve your PID Controller Javier Gutierrez LabVIEW Product Marketing 2
  3. 3. Benefits of Advanced Control and Tuning Model-based Manual • A poorly tuned control control < 1% control valve costs additional $880/year* • A bad pH loop incurred chemical waste of $50,000/month* • A bad kiln temp loop cost $30,000/month* PID needs PID is fine manual tuning *Sources: Cybosoft and ExperTune 3
  4. 4. Agenda • What is PID? • How to improve performance  Hardware considerations  Upgrade PID Algorithm  Advanced Controllers • Conclusion 4
  5. 5. Agenda • What is PID? • How to improve performance  Hardware considerations  Upgrade PID Algorithm  Advanced Controllers • Conclusion 5
  6. 6. What is PID • Set Point (SP) – Desired control point • Output (OP) – Controller output • Process Variable (PV) – Plant/process output • Error = SP - PV error OP SP PV 6
  7. 7. PID Parameters • Proportional  Drive to setpoint  Error → 0, OP → 0  “Steady-state error” • Integral  Eliminate steady state error  OP proportional to ∫ error • Derivative  Increase response rate  OP proportional to rate of change of error 7
  8. 8. System to control 8
  9. 9. PID Implementation Demo 9
  10. 10. PID Control – Pros and Cons • Advantages  Proven  Easy to implement • Disadvantages  Not easy to tune  Not suitable for all systems • Backlash, friction, and so on 10
  11. 11. Agenda • What is PID? • How to improve performance  Hardware considerations  Upgrade PID Algorithm  Advanced Controllers • Conclusion 11
  12. 12. How to program PID Function Blocks Windows/Real Time FPGA Control and Simulation 12
  13. 13. Benefits of Higher Loop Rates 13
  14. 14. PID Loop rates 1 MHz 100 kHz 25 kHz 600 Hz 14
  15. 15. Die Casting Machine The movement of the aluminium injection plunger controlled in a steady closed loop at a speed varying from 0 up to 10 m/sec. 15 Copyright 2007 © EUROelectronics srl – ITALY -
  16. 16. Agenda • What is PID? • How to improve performance  Hardware considerations  Improve PID Algorithm  Advanced Controllers • Conclusion 16
  17. 17. Upgrade your PID Disturbances Feed-forward Non Linear Gain Scheduling Time Variant Adaptive PID 17
  18. 18. Feed-Forward • Commonly used to compensate for a measurable external disturbance before it affects a controlled variable. • e.g. product feed rate changes 18
  19. 19. Gain Scheduling • Used to change gain on real-time depending on OV. • Bumpless transfers 19
  20. 20. Adaptive PID • Mixed of On-Line system identification and common PID control. • Can handle time-variant systems 20
  21. 21. Agenda • What is PID? • How to improve performance  Hardware considerations  Upgrade PID Algorithm  Advanced Controllers • Conclusion 21
  22. 22. Advanced Controllers National Instruments • Optimal Controllers (LQR, LQG) • Model Predictive Control (MPC) • Kalman Filters • Fuzzy Logic Third Party Partners • Neural Networks • Genetic Algorithms • Model Free Adaptive 22
  23. 23. How to create an advanced Controller Control Design • Datalogging • Deployment • System • Design • Test Identification • Simulation • Model Validation Plant Modeling Implementation 23
  24. 24. Temp Chamber - Experiment 24
  25. 25. Plant Modeling - Validation 25
  26. 26. MPC Control Design 26
  27. 27. MPC Control Prototype 27
  28. 28. Advanced Controllers • Pros/Cons 28
  29. 29. Agenda • What is PID? • How to improve performance  Hardware considerations  Upgrade PID Algorithm  Advanced Controllers • Conclusion 29
  30. 30. Conclusions • PID • Consider  Upgrading hardware  Enhance PID Algorithm  Upgrading Control Algorithm 30
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