Integral Tracking for Management of Uncertain Populations
Richard Rebarber (Mathematics, University of Nebraska)
(November 12, 2013 10:20 AM - 11:15 AM)
Regulation or management to a constant set–point is fundamental across science and engineering. In conservation management or pest control, population managers aim to regulate the population to a desired density. In order to be useful in applications, set–point regulation should be robust to parametric uncertainty and measurement errors. We address how set–point regulation can be achieved in a robust way. We describe the control theory concept of Integral Control. Integral control is a simple yet powerful technique developed by control engineers, which is ubiquitous in engineering but has not yet (to our knowledge) received attention in population dynamics. One striking feature of integral controllers is that they can be implemented on the basis of both minimal knowledge of the system to be managed or regulated, and in the presence of considerable system uncertainty. This that makes them appealing for population management/conservation, where uncertainty and incomplete measurements are expected. In this talk we discuss the theory of integral controllers and give hypothetical examples.