Tuning PID controllers with TOPAS

A unique approach that gives the best results for all situations

Good controller tuning is important: it reduces e.g. the variations of product qualities or yields or allows to run closer to constraints. But also reducing the moves of the manipulated variable can bring significant advantages, for example by smoother operation of downstream units.

Yet, studies in industry have shown that only about 20 % of the controllers are delivering better performance than the operator. This is especially embarrassing with respect to the cost for installing a controller which typically range between 10 and 30 k€. It shows that finding “good” tuning for PID’s is still the key problem – but now we have an answer.

Self-regulating processes

Many methods for calculating PID tuning parameters exist, but most only work well in a certain range. Now TOPAS eliminates this shortcoming by combining the best resources: It uses over 20 methods, evaluates them specifically for the given situation and selects the best results. Besides our own method, highly recognized formulas like Astrom, Cohen-Coon, Chien-Hrones-Reswick, IMC, ITAE, etc. are included.

Tuning is calculated specifically for setpoint changes or load upsets and users can opt for best performance, smoothest control action or minimum consumption of the resource. The loop behaviour for the three best results is presented graphically. Further testing and refining such as for the effect of noise, sticking valves, process non-linearity or changes in the dynamics can be carried out with the integrated simulation environment.

For self-regulating processes, the process can be represented by a first or second order plus deadtime model. For the estimation of these process parameters TOPAS provides several easy and fast methods, using the results of a step test or a relay test or operating data or even those of a closed loop test. Unlike the well known Ziegler–Nichols approach there is no oscillation required.

An example, a self-regulating process, a first order model (step test result) is used.

Now the result of a closed loop test is used. This method provides both the process parameters and the PID tuning in one step - exact when carried out with a P-controller, with good approximation when done with a PI-controller. Some more details are given on the page about the Z-N approach

  Only 5 data points are needed from the response curve: 

Furthermore, with the RGA function in TOPAS the strength of the interaction can be checked and also the necessary de-tuning calculated.

Integrating processes

For integrating processes, general formulas are now available in addition to the ones for tight and average liquid level control. For smooth ("average") level control also the maximum allowable range for the level can be specified by the user.

Tuning level controllers in the plant poses a problem as we normally can only make setpoint changes - which the controller will hardly ever experience. We cannot trigger disturbances just to test the controller for its real task. With the simulation this can be done of course easily and fast. Since only a few data are needed (e.g. for a vertical drum just the drum diameter and the distance between the level measurements) one can tune and test the controller in the TOPAS environment, without any plant tests.

In the second test with the non-linear ("error squared") PID tuned for average control, the action on the process (i.e. the flow out, the green line) is much smoother than in the case of "standard" tuning. The level itself, the blue curve, is allowed much more freedom to move.

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ACT - D.I. Hans H. Eder KEG
Wienerstr. 10, 3443 Elsbach, Austria
Brussels office: Madeliefjeslaan 13, 3080 Tervuren
Phone ++32-(0)2-767-0895, e-mail: office@act-control.com