From regulation basics to advanced control

1. From regulation basics to advanced control Sébastien Cabaret - October 2007

2. Overview • Regulation: what is a control loop? • What is a PID controller? • What is advanced control? • Identifying, Modeling …. Tuning • Advanced control example: predictive control • Schneider tool for Modeling and Tuning available in ITCO • Application for GCS: MultiController Sébastien Cabaret - October 2007

3. Regulation: what is a control loop? “I want to see a measured value which corresponds to my request” Sébastien Cabaret - October 2007

4. Desired Temperature (ex: 150C) Acts on heating power (4-20mA) (0-500W) Controller or human! Temperature Sensor TE Reaction: The water temperature reacts on heating power changes Regulation: what is a control loop? Sébastien Cabaret - October 2007

5. Regulation: what is a control loop? • Control Loop system Representation • Example: Open Loop representation Sébastien Cabaret - October 2007

6. Regulation: what is a control loop? • Control Loop system Representation • Example: Closed Loop representation Sébastien Cabaret - October 2007

7. Temperature Sensor (y) TE G(p) Desired Temperature (SP, 150C) C(p) Acts on heating power (u, 4-20mA) Reaction: The water temperature reacts on heating power changes Sébastien Cabaret - October 2007

8. What is a PID controller? • PID means Proportional, Derivative Integrative. • In a classic control loop system, the PID is the controller placed before the process: Sébastien Cabaret - October 2007

9. What is a PID controller? • PID Elementary actions • Proportional Sébastien Cabaret - October 2007

10. What is a PID controller? • PID Elementary actions • Integrative Ti is the coefficient given to increase or decrease the integrative action Sébastien Cabaret - October 2007

11. What is a PID controller? • PID Elementary actions • Derivative Td is the coefficient given to increase or decrease the derivative action Sébastien Cabaret - October 2007

12. What is a PID controller? • PID Elementary actions • Sum up Sébastien Cabaret - October 2007

13. Advanced Control System complexity Basic corrections Others Fuzzy, Neuronal network, … Advanced strategies GPC, PFC, RST, IMC… PID • Other strategies Need for process identification What is advanced control? Sébastien Cabaret - October 2007 Advanced Control - Sébastien Cabaret – 9 Feb. 2006

14. Methods Data acquisition IdentificationModeling Identifying, Modeling… Tuning • Process to tune a controller • We should have the knowledge of the system • We should give information to the controller for its tuning Controller parameters TUNING Ex: P,I and D for PID System information Sébastien Cabaret - October 2007

15. Advanced control example: predictive control • The predictive control method is an advanced control strategy • It is a good compromise between performance and complexity • It is based on a model for the prediction of the process output and on a determinate horizon • It also uses a reference trajectory to attempt the desire response • Several predictive controls exist due to various mathematical approaches of automation people. Sébastien Cabaret - October 2007

16. A process model is integrated into the controller SetPoint Process Output Action The controller has the system knowledge and is able to calculate future action to have a desire output behavior The predictive control is closed to human driver behavior The controller contains the model of the process to drive The driver has built a «mental picture» of its car behaviors He knows the efficiency of the brakes and knows the effect to his car The model allows to predict the effect of the action to the system output Sébastien Cabaret - October 2007

17. Predictive Control • The model used by the controller is a dynamic representation of the input/output relationships (ex: mental model of the car vs. the road) • The reference trajectory is known by the controller (ex: car trajectory) • The horizon definition is specified (ex: 20 seconds) Sébastien Cabaret - October 2007

18. Model Set Point Horizon Real trajectory Reference trajectory Sébastien Cabaret - October 2007

19. Future Sébastien Cabaret - October 2007

20. Schneider tool for Modeling and Tuning available in ITCO DataStore Optireg • Some predictive • algorithms • PID • Schneider PLC Sébastien Cabaret - October 2007

21. Application: MultiController object in GCS project Sébastien Cabaret - October 2007

22. Application: MultiController object in GCS project Smith Predictor IF1 MultiController • The MultiController is a standard UNICOS object for Schneider PLC and PVSS SCADA system • Replace UNICOS PID controller • UNICOS compatible (modes, connection, hierarchy) • It has a single interface for all regulation algorithms • The design allows the addition of new control loop algorithms without changing the object interface • It has been design to offer a recipe mechanism. It allows the process expert to keep and reuse pertinent sets of tuning parameters PID RST PFC generalized SF1 DC3 Sébastien Cabaret - October 2007

23. Application: MultiController object in GCS project • The MultiController is a standard UNICOS object for Schneider PLC and PVSS SCADA system • It has a unique Human Machine Interface with different views • It is composed of a synoptic, trend views, navigation buttons • It allows a global control of the regulation loop via a centralized object representation in the HMI with different views Sébastien Cabaret - October 2007

24. MultiController operation under PVSS Sébastien Cabaret - October 2007

25. Model representation: Ex: first order in discrete approach B1.z-1 H(z)= 1+A1.z-1 y A1, B1 u GPC Parameters MultiController Set Point MultiController future application: adaptive control System to control Online Model Identification under PLC GPC tuning Mechanism in PLC (Predictive strategy) Sébastien Cabaret - October 2007

26. Advanced Control Questions Sébastien Cabaret - October 2007