The main problems identified by the consultant and corrected were:
- oscillatory tuning of the reactor temperature controller;
- oscillatory tuning of the jacket temperature controller;
- excessive dead zone in the jacket split range logic; and
- control valve setup problems.
The plant personnel hadn’t been trained in modern loop-tuning methods such as Lambda tuning, which gives nonoscillatory response at the speed required by the production objectives. The tests required for systematic tuning also revealed the nonlinearities in the split range logic and control valves. After applying corrections to three reactors, energy savings on steam alone paid for the consulting project in less than three months.
Figure 4. Response was far too slow for a set-point step on a 3,600-L reactor with the reactor loop in auto and the jacket loop in cascade.
The as-found auto response was too slow, taking more than two hours to reach the new set point (Figure 4). Note for the reactor (master) loop the units of the SP, PV and output all are °C. For integrating processes, fast closed-loop response requires driving the output beyond the PV for some period of time. Due to the slow tuning, the operators preferred to make frequent manual adjustments to the jacket set point until the correct reactor temperature was achieved. This interfered with the operators’ primary duties such as sampling for quality control.
Due to nonlinearities in the control logic, it wasn’t possible to find the best controller tuning parameters by hand calculation. Instead the consultant built a computer simulation using test data acquired from manual step responses. This led to much better tuning of the controller and allowed the operators to keep the reactor loop in auto mode — as designed.
The tests also identified several limitations in the jacket response (Figure 5). The response was much faster to cooling than to heating. The cooling response showed initial oscillation followed by a very slow attempt to recover to 40° C. The asymmetry in heating versus cooling indicates the need for a gain scheduling controller, which applies one set of tuning parameters for cooling and another for heating. Manual step testing of the jacket also showed that inappropriate derivative and filtering values had been installed for the jacket controller. Finally, ideal cooling response would require a different inherent flow characteristic in the cooling valve. Fixing all these problems in the jacket loop would further improve the reactor response.
Methods for success
In the typical chemical plant, there’re several obstacles to achieving optimal control. Plant design and construction often emphasize chemistry, cost and safety instead of control. Academic control courses typically leave the plant engineer ill-prepared due to their emphasis on complex mathematics or sole focus on continuous processes. Early tuning methods, still taught in the industry, were designed to deliberately make the loop oscillate. The jacket and reactor temperature relationship includes integrating dynamics, making controller tuning less intuitive than for self-regulating (e.g., flow) loops.
Complex control systems have been developed to handle various reactor hardware, specific types of chemical reactions and production constraints . For the fastest possible set-point response, you may want to consider a nonlinear control strategy as described in Ref. 2. However, for reactors controlled by simple cascade strategies (Figure 1), many problems can be prevented by applying the following five steps to each loop:
- Make the process dynamics as linear as possible.
- Minimize dead time.
- Measure the process dynamics.
- Choose the right controller algorithm to compensate for the process dynamics.
- Tune for the speed required, without oscillation.