Many of the practical problems in achieving high performance feedback control for challenging applications have been addressed by modifications to the basic PID control law. These modifications include set-point filters that allow both load rejection and set-point following objectives to be satisfied simultaneously and the use of low pass filters to improve stability, particularly when derivative action is employed.
The drawback of course is that these modifications introduce more tuning parameters that have to be adjusted in order to achieve the desired performance. Non linear optimization techniques allow the control engineer to tune this extended set of parameters taking into account practical considerations such as model estimation uncertainty, interactive control loops, actuator wear etc.
This paper will consider the performance of various optimally tuned feedback control strategies to a simulated refining process with interactive control variables. A multivariable controller will be used as a benchmark reference. The impact of model error and process constraints will also be considered. We will demonstrate how control performance can be improved by the correct use of the tuning parameters that are available in most commercial distributed control systems, allowing significant benefits to be achieved for a relatively modest investment.
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