In part 4 we start a list of best practices. The guidance is the result of decades of experience in plants by industry experts Michel Ruel and Jacques Smuts. The practices are insightful and apply to almost every control loop. The series will conclude next week with my offering. The Part 3 essential concepts and Parts 4-5 best practices will be featured in a future article coauthored with Michel Ruel and Jacques Smuts "What Every Engineer Needs to Know about Process Control"
Best Practices for Process Control
(1-8 by Jacques Smuts and 9-16 by Michel Ruel)
•1. Know your process. This item seems almost too obvious to be on the list, but it is often tempting to address a control problem through tuning without considering the broader process. Process knowledge provides guidance on the control objective, tuning rules to use, diagnostic tests to do, and the process conditions under which to do the tuning. Things to know about the process include: the process type (integrating or self-regulating), ratio of process lag to dead time, if the process' gain or dynamic characteristics might change under varying operating conditions, type of final control element being used and its flow characteristics, disturbances to the process and if they are measurable, possible negative side-effects from process-variable overshoot or a rapidly changing controller output.
•2. Determine the control objective. The control objective dictates the type of tuning method to use. The control objectives could be fast setpoint tracking or fast disturbance rejection (of which each could have sub-objectives such as minimum absolute error or minimum integral of error), zero process-variable overshoot, a specific process response to setpoint changes, minimum controller output movement, and no overshoot in the manipulated variable. Surge tank level loops, for example, should be tuned to minimize controller output movement while keeping the level between predefined limits.
•3. Review the control strategy. The control strategy should support the control objective, given the broader process with its disturbances, nonlinearities, and other nuances. For example, a simple feedback control loop will do an awful job if ratio control is actually needed. Cascade control should be used only if the inner loop is much faster than the outer loop. Feedforward control should be used to compensate for process disturbances, except when the disturbances directly affect the flow rate through the final control element - requiring cascade control. When done correctly, control strategies can significantly contribute to control loop stability and responsiveness. Unfortunately, the opposite is also true.
•4. Review the controller configuration. Modern, digital controllers offer a range of options to optimize their performance for various situations. Setpoints can be ramped or filtered internally to obtain a smooth control response even when the operator makes an abrupt change. Setpoint changes can also be hidden from the proportional and derivative control modes. External reset feedback prevents integral windup under adverse conditions, and rate-of-change limits can protect sensitive equipment downstream. If a process variable filter is used, its time constant should be reviewed to ensure that it is set appropriately and significantly shorter than the dominant process time constant.
•5. Test the final control element. An improperly working final control hurts control loop performance and can negate proper controller tuning methods. Typical problems include deadband, stiction, a nonlinear flow curve, and positioner problems. These problems may appear very similar to tuning problems, and an unknowing tuner may spend many hours of futile tuning if the problem lies with the control valve. A few simple process tests should be done to detect and diagnose final control element problems before any tuning is attempted.
•6. Use an appropriate tuning method. Contrary to popular belief, controller tuning is much more science than art. Loop tuning can be done quickly and accurately based on the control objective, process characteristics, and appropriate tuning rules. Process characteristics are determined by making a step-change in controller output and taking measurements from the resulting process response. Although trial-and-error tuning is popular, it should be used only as a last resort, for example with processes that are so volatile that it is impossible to get usable step-test data. As an alternative to manually calculating tuning parameters based on step-test results, loop tuning software offers many helpful features such as identification of process characteristics, producing tuning settings for different tuning objectives, providing simulations of anticipated loop response, analyzing control loop robustness, and more. However, tuning software is only a tool, and someone incapable of manually tuning controllers using step-test data and tuning rules will likely also find it difficult using tuning software.
•7. Tune from multiple step tests. Simulations may be 100% repeatable, but real processes are not. Process disturbances, interacting control loops, nonlinearities, and operating conditions can all affect measured process characteristics. Tuning from only one step test can result in poor tuning settings if the process response at that instance was not normal for whatever reason. It is essential to do multiple step tests to obtain "average" measurements of process characteristics, and an appreciation of how much they change under normal conditions.
•8. Cater for nonlinearities and changing process characteristics. The installed flow characteristic of a final control element is often not linear. In addition, the characteristics of many processes change under different process conditions (production rates, equipment in service, catalyst concentration, pH, etc.). Control valves and dampers might have to be linearized using a characterizer, and changing process characteristics might require the scheduling of controller parameters (called gain scheduling or adaptive tuning).
•9. Use dead time as the clock for the control loop if tuned to reject disturbances. When a loop is tuned to reject quickly a disturbance, tuning parameters (and formulas) depend mostly on dead time. Reducing dead time will improve greatly performance. Reducing dead time improve performance both in amplitude and time; the effects are multiplicative, so performance (integrated error) become proportional to inverse of dead time squared.
•10. Check relative size of PID parameters. For example, for Series and ISA Standard Form: Scan rate < PV filter < Derivative time < Dead time + Secondary time constant < Integral time < Settling time
•11. Use time constant as the clock for the control loop on a self-regulating process if tuned to smoothly follow a setpoint. Disturbance rejection tuning can be used if a setpoint filter is used that is equal to the primary process time constant. Slow self-regulating processes should be treated and tuned as near integrators to retain disturbance rejection.
•12. When troubleshooting a control loop, last step should be to retune the controller. A common mistake when a problem occurs is to retune the controller. If the behaviour was adequate on Tuesday but the loop is oscillating on Wednesday, detuning the loop will hide the real problem. One should find the cause and fix the problem. A rookie will retune the loop, not an experienced person.
•13. Oscillations should always be removed. In process control, oscillations are abnormal and should not be tolerated. Oscillations occur when the controller is tuned too aggressively or when loops interact. Too much Proportional will induce oscillations; too much Integral will also induce oscillations but a slower pace; finally, too much Derivative will induce oscillations at a higher frequency. Those oscillations (PV and controller output) will look like a sine wave.Oscillations also occur when the final element has stiction. In such cases, the oscillation of the controller output will look like a sawtooth and the PV oscillation will look like a square wave or a rounded square wave. Oscillations could also be generated by an external disturbance. If experts try to convince you to tolerate oscillations, fight hard!
•14. Tuning methods and formulas depend on algorithm. PID algorithm and structure vary and each system has its own flavor. Be careful when using tools or methods to determine first if the controller form is ideal (also named ISA), series or parallel. Ideal and series are similar (identical if no derivative is used) but parallel is a different animal and results will be different.
•15. Tune for worst case. Always find the worst situation before tuning a control loop. Test going up and down, at low rate and high rate, small change, large change, etc. If the goal is to reject a disturbance, worst case is higher process gain, larger dead time and smaller time constant. If performance has to be good for all situations and process model varies, use variable tuning parameters based on process conditions. If only process gain varies, a characterizer should be added.
•16. Realize control response must generally be more aggressive on a SP change than on a disturbance. When a disturbance occurs, it is filtered (smoothed) by the process and appears gradually. When a SP change occurs, the change is brutal and a step from proportional action occurs for the most commonly used PID structure. Conversely, if a loop is tuned for a gradual response to a SP change, the response could be sluggish when a disturbance occurs. Instead of detuning for a SP change, use a SP filter, SP Lead/Lag, or a structure of PD on PV with I on Error (only Integral is active on a SP change) to retain load disturbance tuning and achieve a gradual SP response.
Next week we conclude this series with my offering of best practices so we can move on to the remaining questions from Brian Hrankowsky in subsequent weeks.