Control using wireless measurements

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The DeltaV PIDPlus is based on a modification of the PID reset and rate calculation to account for non-periodic measurement updates. An alternate approach is to use PID with a modified Kalman filter or modified Smith Predictor. Test results are presented that compare the PIDPlus to these alternate approaches.

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Control using wireless measurements

  1. 1. Control Using Wireless Measurements PIDPlus vs an Observer with PID
  2. 2. Presenters  Terry Blevins  Mark Nixon
  3. 3. Introduction In this workshop we show how an observer may be modified for use with a wireless measurement and compare control performance to that achieve using DeltaV PIDPlus.  Background on observers and development of PIDPlus  Modification of Kalman filter and Smith Predictor for use with a Wireless Measurement in Control applications  Test Results –PIDPlus, Modified Kalman Filter and Smith Predictor  Summary  Where To Get More Information
  4. 4. Traditional Approach in Control  Controllers are commonly designed to over-sample the measurement by a factor of 2-10X.  To minimize control variation feedback control is executed 4X to 10X times faster than the process response time i.e. process time constant plus process delay.  However, the underlying assumption in the control design (using z transform, difference equations) and digital implementation of the PID is that the algorithm is executed on a periodic basis.
  5. 5. Control Data Sample Rate
  6. 6. Control Using Wireless Measurements To minimize the power consumed in communicating new measurement values the transmitter may use Window communication according to the following rules:  The transmitter will periodically sample the measurement 4-10x faster than the process response time.  If the magnitude of the difference between the new measurement value and the last communicated measurement value is greater than a specified resolution or if the time since the last communication exceeds a refresh time the new value is communicated. When the measurement is not updated, the calculated reset and derivative action may not be appropriate.
  7. 7. PIDPLUS for Wireless Control  The PID is restructured to reflect the reset contribution for the expected process response since the last measurement update.  The rate contribution is recomputed and updated only when a new measurement is received - using the elapsed time since the last new measurement.
  8. 8. Use of Observers in Wireless Control The DeltaV Future architecture team has investigated whether an observer can be used for PID control with a wireless measurement. Two types of observers were considered:  Kalman Filter  Smith Predictor It was necessary to modify these observers to work correctly in control using a PID and wireless measurement
  9. 9. Kalman Filter - Modificatons for Noise with Non-zero Mean  Composite is available through Application exchange for use with a continuous measurement  See workshop 124381, Emerson Exchange 2013, “Addressing Control in the Presence of Process and Measurement Noise”
  10. 10. Kalman Filter - Modificatons for Wireless Measurement and Noise with Non-zero Mean  The calculation of the residual must be modified to account for the slow, non- periodic update of the process measurement
  11. 11. Application of Smith Predictor With PID  Smith Predictor is a standard module in the DeltaV library.  Most commonly used in continuous process control applications that are dominated by large deadtime.
  12. 12. Smith Predictor – Modification for Wireless Measurement  The calculation of the residual must be modified to account for the slow, non-periodic update of the process measurement
  13. 13. Comparing Performance - Test Conditions A first order plus deadtime process was used to compare the performance of PIDPlus to PID with observers modified for wireless control.  Process Gain = 1  Process Time Constant = 6 sec  Process Deadtime = 2 sec The PI control was tuned for a lambda factor of 1.  GAIN = 1/Process Gain  RESET = Process Time Constant + Process Deadtime The process input and output were scaled 0-100%. The simulated wireless transmitter is configured for 1% change and 10 sec default period using Windowed communications. The module execution rate was set at 0.5 sec.
  14. 14. Test Environment – Wireless Control Using Kalman Filter vs wired PID
  15. 15. Modified Kalman vs. Wired PID
  16. 16. Test Environment – Wireless Control Using Smith Predictor vs Wired PID
  17. 17. Modified Smith Predictor vs Wired PID
  18. 18. Test Environment – Wireless Control Using PIDPlus vs Wired PID
  19. 19. PIDPlus vs Wired PID
  20. 20. Wireless Control Performance  Test were performed under ideal conditions where the model used in the Kalman filter and Smith predictor are based on the process gain and response.  All methods provide good control. As measured by IAE, the PIDPlus did significantly better than the modified Smith Predictor and slight worse that the modified Kalman filter.  PIDPlus does not require that the user entry process model parameters.
  21. 21. Conclusion  A method for dealing with non-periodic measurement updates is a requirement when closed loop control is implemented using wireless transmitters.  The DeltaV PIDPlus is designed to use non-periodic, slow measurement updates. Alternative approach based on using PID with a modifed Kalman filter or a Smith Predictor may also be used but requires setup of the process model.  The PIDPlus is preferred for wireless control since it is more robust for changes in process gain, dynamics, and noise level.
  22. 22. Where To Get More Information  Workshop 12-4381, Emerson Exchange 2013, Wojsznis and Blevins, “Addressing Control in the Presence of Process and Measurement Noise” (Using Kalman Filter)  E. Cheever. “Introduction to Kalman Filter”, http://www.swarthmore.edu/NatSci/echeeve1/Ref/Kalman/ScalarKalman.html  Application Exchange, “Kalman Filtering in DeltaV – Control in the Presence of Noise”, http://www2.emersonprocess.com/en- US/brands/deltav/interactive/Pages/Interactive.aspx  S. Han, X. Zhu, K.M. Aloysius, M. Nixon, T. Blevins, D. Chen, “Control over WirelessHART Network”, 36th Annual Conference of the IEEE Industrial Electronics Society, 2010  F. Siebert, and T. Blevins, “WirelessHART Successfully Handles Control”, Chemical Process, January, 2011
  23. 23. Thank You for Attending! Enjoy the rest of the conference.

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