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Additional info for Applied control theory
3 Control by empirical relations This type of approach is particularly appropriate where a continuous (as opposed to batch) process is to be maintained in a constant state despite the presence of disturbances. The various measurements that are available are weighted and combined together in a semi-scientific way to produce one or more variables that are then used to drive the process control system. While no process model is needed (and that is one of the advantages of the approach) the semi-scientific combination often makes some basic assumptions connected with mass, energy or chemical balance in the process.
Lack of suitable primary measurements has, from the outset, limited the scope of process control systems. Measurement of primary variables in large-scale industry is very costly and any investment made will be contingent on an expected payback. Economic calculations can only be made in an overall systems context since it will be in improved system performance that any payback will materialise. Conventional measurement topics are not covered here but a number of comprehensive handbooks and specialist monographs are listed in the bibliography.
Time-varying elements. (g) Stochastic features. It is important to understand the simpler aspects before embarking on timeconsuming complex investigations. (a) Dead-time Td, at least where it is constant, can be determined from a straightforward step test conducted on the (open-loop) process. Let a process that consists only of dead-time Td be put in series with a manipulable gain k in closed-loop. At r * some gain k the system will execute steady sinusoidal oscillations with frequency co*.