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Maximizing the return on your control investment meet the experts sessions part 1
Maximizing the return on your control investment meet the experts sessions part 1
Maximizing the return on your control investment meet the experts sessions part 1
Maximizing the return on your control investment meet the experts sessions part 1
Maximizing the return on your control investment meet the experts sessions part 1
Maximizing the return on your control investment meet the experts sessions part 1
Maximizing the return on your control investment meet the experts sessions part 1
Maximizing the return on your control investment meet the experts sessions part 1
Maximizing the return on your control investment meet the experts sessions part 1
Maximizing the return on your control investment meet the experts sessions part 1
Maximizing the return on your control investment meet the experts sessions part 1
Maximizing the return on your control investment meet the experts sessions part 1
Maximizing the return on your control investment meet the experts sessions part 1
Maximizing the return on your control investment meet the experts sessions part 1
Maximizing the return on your control investment meet the experts sessions part 1
Maximizing the return on your control investment meet the experts sessions part 1
Maximizing the return on your control investment meet the experts sessions part 1
Maximizing the return on your control investment meet the experts sessions part 1
Maximizing the return on your control investment meet the experts sessions part 1
Maximizing the return on your control investment meet the experts sessions part 1
Maximizing the return on your control investment meet the experts sessions part 1
Maximizing the return on your control investment meet the experts sessions part 1
Maximizing the return on your control investment meet the experts sessions part 1
Maximizing the return on your control investment meet the experts sessions part 1
Maximizing the return on your control investment meet the experts sessions part 1
Maximizing the return on your control investment meet the experts sessions part 1
Maximizing the return on your control investment meet the experts sessions part 1
Maximizing the return on your control investment meet the experts sessions part 1
Maximizing the return on your control investment meet the experts sessions part 1
Maximizing the return on your control investment meet the experts sessions part 1
Maximizing the return on your control investment meet the experts sessions part 1
Maximizing the return on your control investment meet the experts sessions part 1
Maximizing the return on your control investment meet the experts sessions part 1
Maximizing the return on your control investment meet the experts sessions part 1
Maximizing the return on your control investment meet the experts sessions part 1
Maximizing the return on your control investment meet the experts sessions part 1
Maximizing the return on your control investment meet the experts sessions part 1
Maximizing the return on your control investment meet the experts sessions part 1
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Maximizing the return on your control investment meet the experts sessions part 1

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The design and commissioning of the controls associated with a continuous or batch process directly impact plant operating efficiency and production quality and throughput. In this session we review …

The design and commissioning of the controls associated with a continuous or batch process directly impact plant operating efficiency and production quality and throughput. In this session we review techniques that may be used to identify control opportunities to reduce production costs, minimize variations in product quality and to maximize production within the limits set by market demand. Several common application examples from the process industry will be used to illustrate how plant production rate and product quality are directly influenced by process control variation and constraints in plant operation. Starting with an assessment of control loop utilization and automatic control performance, a step by step process is outlined that may be used to identifying and addressing areas where it is possible to justified the time and material costs required to improve control performance. In particular, information will be provided on how to quickly tune single loop control of self-regulating or integrating process and to recognize when variations in control loop performance are not associated with loop tuning. An overview will be provided of tools and techniques that may be used to achieve best control performance over a wide variety of operating conditions. Also, guidance will be provided on when it is possible to justify the cost associated with the installation and commissioning of multi-loop techniques such as feedforward control, ratio and override control. The steps required to commission multi-loop control strategies will be address along with common mistakes to avoid. Also, input will be provided on how to recognize when advanced control techniques such as Fuzzy logic or MPC are needed to achieve the desired control performance. At the end of this session a drawing will be held to give away 10 copies of “Control Loop Foundation – Batch and Continuous Processes”. Many of the ideas discussed in this session are addressed in this book.

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  • 1. Maximizing the Return onYour Control Investment Part 1 of 2 Meet the Experts Sessions
  • 2. Presenters  James Beall  Terry Blevins
  • 3. Session Objective  Provide a roadmap that may be used to maximize the return on your control investment
  • 4. Agenda  Assessment of control loop utilization and automatic control performance,  Identifying areas where it is possible to justified the cost of improving control performance.  Tools and techniques to achieve best control performance. Identifying and correcting field problems.
  • 5. Evaluating Control System Utilization  Product quality and manufacturing efficiency may be impacted by variation in key parameters.  When production is process limited, then throughput may be increase by reducing process variation and operating closer to the limit.  The control must operate as designed to achieve these benefits.
  • 6. Control Utilization Control utilization is an indicator that can be used to quickly determine if control and measurement problems exist within a control system. Surveys indicate that the primary reasons for control not being fully utilized fall into two areas:  Field measurement or control element  Process or control design An immediate improvement in control utilization will be achieved by addressing these problems. To achieve full utilization, improved communications between maintenance and operations is important.
  • 7. Example – Case StudyAt one pulp and paper plant a snapshot of the control utilization wascollected to quantify the state of the process control. This survey showed: Control Normal Loops Mode Utilization Bleach Plant 78 60 76% Power House 185 130 70% Pulp Mill 174 116 66% Paper Mill 236 134 56% An instrumentation team was formed to investigate loops that were notrunning in their normal design mode. This team was responsible for makingsure measurement, control valve, and process problems were addressed ina timely fashion. The reduction in variability led to significant improvementsin plant throughput and product quality
  • 8. Example – Another Case StudyAt refinery and petrochemical complex a snapshot of the control utilizationwas collected to quantify the state of the process control. This surveyshowed: System Loops Utilization PX 471 67.3% APS&VPS、CLE、Sulfur Recovery 469 59.7% Refinery 478 60.9% IGCCAuxiliary Boiler 946 52.7% Ethylene 1355 77.5% FCCU 475 48% C4 164 68.9%
  • 9. Examining Control Utilization Summarizes performance for System or by Area, Cell, or Units Abnormal Control Conditions indicated for Problem Loops: – Control Service Status: • Not in Normal mode • Limited control output • Bad/Uncertain input – Control Performance Status: • Standard Deviation • Variability Index • Oscillation Index • Tuning Index
  • 10. DeltaV InSight Control Performance Reports
  • 11. Roadmap to Improved Control Transmitter Broken/Unreliable Fix or Replace Transmitter Reason? Tuning Poor Valve/Actuator Problem Investigate Performance Changing Process Gain Process Dynamics No Loop InteractionStarting Point Control Loop in Normal Mode? Yes Use DeltaV Insight to examine loop tuning Use DeltaV Insight to Determine Control Utilization
  • 12. DeltaV Insight – On-demand Tuning  Allows control loop tuning to be quickly established
  • 13. Examine Tuning Impact
  • 14. DeltaV InSight - Adaptive Tuning Provides Tuning Based on Normal Operator Changes  InSight automatically calculates dynamic Before vs. After models from operator changes  Model Quality and Learning Status  Tuning criteria and desired speed of response  Tuning Recommendation  No Testing Required
  • 15. Tips for Using On-Demand Tuning  Set step size large enough to insure the response to the PID output changing is larger that the measurement noise and influence of process disturbances.  Select “Integrating” if the process is not self- regulating.  If the process has low or high gain, then selected Default Process and set the process type to match the expected behavior.
  • 16. Manual Tuning (Not a DeltaV System) When commissioning PID control associated with a self-regulating process, this procedure may be quickly applied to both old and new control systems to determine the tuning for PI control. The size of the step should be just large enough to easily distinguish the resulting change in the controlled process output.
  • 17. Manual Tuning - (Not a DeltaV System)Alternate When commissioning PID control associated with a self-regulating process, this procedure may be quickly applied to both old and new control systems to determine the tuning for PI control. The size of the step should be just large enough to easily distinguish the resulting change in the controlled process output. Tune as follows: – Place the PV and OUT on a trend. – Place the controller in Manual and allow the process to reach steady sate. – Impose a step change in OUT and observe the response – Set the RESET equal to ¼ of the time it takes to “almost” line out (98% of final value) – Set the GAIN equal to 1/3 of process gain, Kp where – Kp = ((Δ%PV) / (Δ%OUT) (Be sure to convert to % of span!) – Place the loop in automatic and make small adjustments to the Setpoint and observe the response. Adjust ONLY the GAIN to achieve the desired response.
  • 18. Impact of Sticky Valve  When a control loop is placed in automatic Setpoint (SP) control, it is easy to detect if a valve or Controlled Parameter (PV) damper is not responding to the Implied Valve Position (OUT)Value control system by observing the Stem Position) response of the controlled parameter to control system Time changes in the PID output.  Cycling can not be eliminated through tuning.
  • 19. Valve Positioner Recommendation The most common problems in commissioning a control system can often be traced to the fact that a positioner has not been provided with the valve, or the positioner provided with the valve has not been properly installed or has malfunctioned. – The rule of thumb is that to achieve best control performance, all regulating valves should be equipped with a positioner. – Without a positioner, the control performance that may be achieved is very limited when a valve is sticking – which is inherent in most valves. – The cyclic behavior caused by a sticky valve (with no positioner) cannot be eliminated through tuning. Changes in tuning will only impact the period of the cycle that develops. The only way to eliminate this type of behavior is to install a valve positioner.
  • 20. Installed Characteristics. 7000  From a control perspective, it is highly desirable that the process 6000 gain be constant. If the process gain is constant, then the same 5000 proportional gain may be used over the entire operating range ofGas Flow (SCFH) 4000 the control loop.  If the valve characteristic was not 3000 been selected based on the process requirements, then the 2000 installed characteristic could be non-linear. 0  As illustrated in this example, the 0 20 40 60 80 100 Valve Position (%) process gain varies from 0.5 to 4; that is, the process gain changes by a factor of eight.
  • 21. Impact of Non-linear Installed Characteristics Non-linear Process Example  Process gain and dynamics may change as a function of operating conditions such as valve position or feed rate.
  • 22. Linearizing Response  To compensate for the changes in process gain, a characterizer block may be installed between the PID and Analog Output blocks. Select the option to inverse the calculation done in the forward path for the PID back calculation to allow bumpless transfer.
  • 23. Characterizer Setup  The relationship between Characterizer 100 IN OUT the primary inputs and the Linear Relationship 0 0 90 Characterizer In-Out 5 1.5 output of the characterizer 10 3 80 15 20 5.5 8,5 block may be defined by 70 25 30 10 11.5 21 x,y pairs over the final 60 35 40 13 17 control element operating 50 45 20 range.Process Output (%) 50 22 40 55 26 30 60 65 31 36  Input values that fall 20 70 75 42 48 between these points are 10 80 85 54 63 automatically determined 0 90 95 74 86 by the characterizer block 100 100 using linear interpolation.  The curve defined by the characterizer points 0 10 20 30 40 50 60 70 80 90 100 appears as the inverse of Valve Position (%) the plot of the final control element installed characteristic. Figure 12-8
  • 24. Identifying Model - DeltaV InSight Gain Process Insight with Model Analysis  Last 200 Models automatically stored for each control loop in a model database  Various plot options to analyze impact of operating conditions on process models  Average of selected models may be utilized to establish the recommended tuning
  • 25. Non-linear Process Models
  • 26. DeltaV InSight – Adaptive Control
  • 27. DeltaV InSight – Adaptive Control Adaptive Control Enabled
  • 28. Split Range Control One of the most common ways of addressing multiple process inputs is known as split-range control. The splitter block may be used to define a fixed relationship between the controller output and each manipulated process input – appearing as one valve to the PID block The setup must account for the gain associated with each process input to achieve consistent control behavior.
  • 29. Example – Steam Header Pressure To allow the plant to continue operation if the turbine or generator fails and must be shut down, pressure reducing valves (PRVs) between the high pressure header and the lower pressure header may be adjusted to meet the lower pressure header steam demand and to maintain the header pressure constant. This may be accomplished by using a splitter block in conjunction with a PID block to adjust the pressure reducing valves.
  • 30. Steam Header – Splitter Characterization If the valve sizes or operating conditions for the valves are different, then it is necessary to characterize the splitter to compensate for these differences. For example, if the flow ratings in thousand of pounds per hour, KPPH, of the valves used in split-range control were as shown below: – Valve 1 flow rating = 50 KPPH – Valve 2 flow rating = 150 KPPH Then the controller output range of adjustment associated with Valve 1 would be:
  • 31. Interactive Loops C1  The fighting between M2 C2 interactive loops is most M2 often addressed by simply detuning one of Flow the control loops by Controller reducing the proportional C1 gain. Composition Controller M1  The valve associated Outlet Flow with the detuned loop Feed Valve(M1) Mixing (C1) will change very slowly. C2AdditiveValve(M2) Process Composition Thus, the two loops will (C2) M1 tend not to interact but at the expense of the detuned loop having slow response.
  • 32. Roadmap to Improved Control Transmitter Broken/Unreliable Fix or Replace Transmitter Reason? Tuning Poor Valve/Actuator Problem Investigate Performance Changing Process Gain Split range Setup incorrect No Process Dynamics Loop InteractionStarting Point Normal Mode? Determine Yes Low/acceptable Monitor for Control Change Utilization Variation on Control High Changing Process Gain Investigate Process Disturbance Unacceptable Process Dynamics Loop Interaction Changing Limit Condition
  • 33. Utilize Process Capacity to Absorb Variability Step change in load (inflow) Outflow = inflow Controller Output changing outflow PV Back to SP in smoothly! PV 6 x Lambda Change in Setpoint LIC PV stopped Lambda Inflow Outflow
  • 34. Utilize Process Capacity to AbsorbVariability  Choose the arrest time “slow” enough to provide a variability sink yet maintain level within the allowable variation  Lambda = __2 * ALV___ Kp * MLD – ALV = Allowable Level Variation – Kp = Integrating process gain – MLD = Maximum Load Disturbance (converted to % of level controller output scale)
  • 35. Utilize Process Capacity to Absorb Variability Before After Level Level Manipulated Variable Manipulated Variable
  • 36. Reducing Control Variation When tuning is not sufficient to achieved the desired level of variation in critical control parameter or to maintain it at an operating limit, then multi-loop techniques may sometimes be applied to improve control. Three common multi-loop techniques are:  Feedforward Control  Cascade Control  Override Control
  • 37. Summary  An on-line measurement of control utilization and variability is provided by DeltaV Insight.  Exploring the causes of poor utilization is the first step in resolving measurement, actuator or control issues.  When single loop control is not sufficient to achieve the desired level of control the multi-loops solutions should be explored.
  • 38. Where To Get More Information  Many of the ideas discussed in this session are addressed “Control Loop Foundation – Batch and Continuous Processes”. Information on this book may be found at the book’s web site: – http://controlloopfoundation.com/ Also, by going to this web site you can use your web browser to perform the 19 workshops that go with this book.

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