DESIGN OF SAMPLED DATA CONTROLLERS

The performance of modern optimal algorithms for sampled data controllers is analyzed and compared to classical controller design. It is shown that their performance is very sensitive to the structure of the disturbance used in the design procedure, but quite insensitive to the parameters of the noise model. For most processes stability constraints are overriding. The paper also shows that optimal algorithms require a different type of stability analysis, as they are very sensitive to small deviations between the real process model and the model used for design. Conventional stability margins are meaningless here. A design strategy utilizing optimal control theory is proposed that results in properly working and stable controllers, with a performance that is overall better than that of PID controllers. Emphasis is given to strategies for operator control but the results should be of more general applicability. © 1979, American Chemical Society. All rights reserved.