ABSTRACT
Modern control theory provides the tools for developing normative models of "optimal control" that provide an important basis against which to measure human tracking performance. There are three sets of constraints that must be explicitly addressed when approaching an optimal control problem: the dynamic constraints of the process being controlled, the physical constraints, and the value constraints or performance criteria. Modern control theory provides the tools to express the control problem mathematically and in some cases to analytically solve for the "optimal" control solution. A key to the mathematics of modern control theory is the representation of the dynamics of a process in terms of state variables. The optimal control model provides a unique perspective on the modeling process because it supports both a wholistic view that supports appreciation of the global situational constraints that bound performance and it also supports a decomposition or reduction of the system into simpler information-processing components.
