«

»

Jun
23

Review of Deminar #6 – PID Tuning for Near-Integrating Processes

PID Tuning for Near-Integrating Processes - Greg McMillan Deminar

You can click on the above to view and hear the recording of the Deminar.

Would you like to find tuning settings and develop a real time simulator for the more important loops in your plant in less than 10% of the time normally required? If this is of interest, check out Deminar #6. The test, triggered by a setpoint or output change, only needs to last about 3 deadtimes. Since the process time constant for the composition, pH, pressure, and temperature response of vessels and columns is 6 to 100 times the observed deadtime and the time to steady state is 4 time constants plus the deadtime, the time savings varies from 90% to 98%. The reduction in test time also minimizes the possibility of the test being disrupted by a disturbance. One of the problems we have with testing large columns to identify the dynamics for tuning or model predictive control is that the time to steady state is a day or more. Day to night temperature changes, feed changes, and shift changes usually disrupt the test of these columns. With the near-integrator approach the test time is a matter of hours and if there is a disruption, the test can be readily repeated. Also, the upset to the process from the test is significantly less because the excursion during the shorter test is much smaller.

The near-integrator gain parameter used to dramatically shorten the test time leads to a simpler expression for the controller gain that is just a function of the near-integrator gain and the observed deadtime. All of the tuning methods reduce to this same expression for maximum disturbance rejection as shown in “Appendix C – The Unification of Controller Tuning Relationships” in the ISA bookNew Directions in Bioprocess Modeling and Control. The controller gains differ by a factor that varies from about 0.5 for a Lambda tuning with a closed loop time constant equal to the process deadtime to 1.0 for the Ziegler Nichols Reaction Curve (ZNRC) method (not to be confused with the widely remembered and unpopular Ziegler Nichols ultimate oscillation method). Note that the ZNRC method requires an open loop test (change in manual output of the controller) and waits for the process to reach steady state to construct a tangent to the inflection point and find its intersection with the final value. The near-integrator method finds the maximum ramp rate for a step change in the controller output regardless of PID mode (e.g. triggered by a setpoint change or a remote output change for batch control).

What about the secondary time constants? If these time constants are much less than the primary process time constant, these secondary time constants result in an increase in the observed deadtime. Keying on a multiple of the observed deadtime self-compensates for this situation. For non-interacting secondary process time constants that approach the primary time constant (an interesting but relatively rare case), the search for the maximum ramp rate would need to be extended for several more deadtime intervals. The search can stop if the ramp rate is not increasing. For equal interacting time constants, the secondary process time constant is about 1/6 of the primary time constant. This methodology can be readily automated to identify the dynamics whenever there is a step change in controller output significantly larger than the final control element (e.g. valve) resolution limit.

For a simple real time process simulation that uses standard function blocks, the controller output and process variables from a scan or snapshot of the actual process for a representative relatively quiet operating point can be used to create deviation variables and provide a correction of the model.

The Deminar focuses on self-regulating processes that look like integrating processes because the process response ramps in the control region. The appearance can be caused by a time to steady state that is beyond the practical time range for observation or by a steady state that is beyond the operating limits of the equipment. For example, an increase in vessel pressure can force more flow out the vent valve but the vessel pressure required for the vent flow to balance the incoming or generated gas flows can be beyond the pressure relief valve setting. The time constant or ramp rate for gas pressure is generally order(s) of magnitude faster than for liquid temperature but the pressure loop deadtime is even faster. For example, the deadtime and time constant for a column pressure response might be 5 and 100 seconds, respectively whereas the deadtime and time constant for column temperature might be 5000 and 30,000 sec, respectively.

The near-integrator method can also be applied to true integrating processes which means level loops and composition, pH, pressure, and temperature loops in batch besides continuous processes can be rapidly tuned and simulated. Loops not suitable for this method are liquid pressure and flow loops and inline (pipeline) blending, pH, and temperature loops because the observed deadtime is comparable or even larger than the process time constant. However, the time to steady state for these loops is a matter of 2 to 20 seconds so that the test time is already fast and conventional methods can be employed.