How MPC will Take Over More of the Role of PID Tips

This post, How MPC will Take Over More of the Role of PID Tips, first appeared in the Control Talk blog on ControlGlobal.com.

The power of the PID largely remains untapped. I have recently documented the extensive capability of the PID but being a realist, I expect MPC is going to take over more and more of the role of the PID. Here we look at the reasons why there is a brighter future for MPC and if there is an opportunity to reverse the decline in PID expertise.

When I taught process control at Washington University in St. Louis to Chemical engineers after retiring from Solutia-Monsanto in 2002, I used MPC more than PID control in the lectures and labs because the application of MPC is more automated and the principles more relatable in terms of the process response than PID control. While a process model is the first step and basis in getting good PID tuning settings, the hundreds of tuning rules and extensive disagreements between the developers of the rules are confusing and discouraging as noted in the white paper “So Many Tuning Rules, So Little Time”.

First let’s clear up misconceptions. I have nothing to sell. I am largely retired. I am not trying to sell my services. The royalties from a book are good for a night out. I write because I don’t want expertise lost. So here is a quick perspective revealing that the PID can do more than recognized and the MPC can learn from the extensive flexibility and capability of the PID.

The PID can do dead time compensation by the simple insertion of a dead time block in the external reset path of the PID. Only a dead time parameter needs to be set whereas the Smith Predictor also required the identification and setting of the process gain and time constant. This dead time can be written to. The online calculation and setting of the dead time is critical particularly when the source is a transportation delay. Furthermore the normal application thought to be of greatest benefit (dead time dominant loops) does not see as much improvement as in lag dominant loops and can cause oscillations for just a 10% overestimate of the dead time. This is counter intuitive since we are normally concerned about underestimates of the dead time. The PID reset time can be greatly reduced if the dead time setting is accurate. The benefit of dead time compensation is not seen until the reset time is reduced to much lower values than found from tuning rules.

The PID can provide directional move suppression that is also computable and settable online by the use of setpoint rate limits in the secondary loop or analog output block and external reset feedback (e.g., dynamic reset limit). The PID can also inherently prevent oscillations from violation of the cascade rule by the use of external reset feedback of the secondary loop PV and fast digital valve controller (DVC) readback of actual valve position. The PID can stop limit cycles from backlash and stick-slip by the integral deadband or an enhancement of the PID where integral action is suspended if there is no appreciable change in the process variable. The enhanced PID can also suppress oscillations and eliminate the need for detuning when an analyzer cycle time is larger than the process dead time and process time constant. The PID can do feedforward control and decoupling with dynamic compensation so the preemptive correction signal arrives at the same place at the same time in the process as the disturbance. Different PID structures can be chosen, some critical (e.g., no integral action due to unidirectional response). All of these features help in the implementation of valve position control to provide a gradual optimization, a fast getaway for upsets, and prevention of limit cycles. Auto tuners, adaptive controllers, and the “Rule of Five” scheduled for my April 12 Control Talk Blog make the PID able to deal with an extensive spectrum of difficult situations and different objectives.

Sounds great, but the expertise required is largely undocumented and not automated. My latest book Tuning and Control Loop Performance – 4th Edition, attempts to remedy this situation but even after 556 pages, there are still gaps. Besides, who has time to read and study that much material? I just finished the 4th edition of my Good Tuning Pocket Guide available in April to help provide a more concise directed view. Still, your best bet is to get a consultant onsite.

Meanwhile, the MPC implementation is very much automated and the tuning often simplifies to just setting a move suppression parameter (e.g., penalty on move). In other cases another parameter is set to provide more or less emphasis on a controlled variable or constraint (e.g., penalty on error). The dynamics of decoupling, feedforward, optimization for multiple variables are inherently addressed and signal characterization can be used for gain nonlinearities. If MPC move suppression and model dead time and remaining nonlinearities can be adapted online, and something akin to external reset feedback is available the lone remaining advantages of the PID are largely gone and come down to the applications where a special PID structure (e.g., unidirectional response), high PID gain and rate time for open loop unstable processes (e.g., highly exothermic reactors), or where a fast PID execution rate due to process dead times and times constants less than 1 second (e.g., compressor and polymer pressure control) is needed.

For more on what MPC and PID can do, see the following Control Talk Blogs and the referenced Control Talk Columns with MPC and PID experts.

MPC Best Practices for ISA Certification of Automation Professionals

When do I use MPC rather than PID for Advanced Regulatory Control?

When do I use PID, MPC or FLC for Basic Control?

Checklist for Best PID Performance

PID Structure Tips

PID Form Trick or Treat Tips