This paper describes a knowledge-based temporal
representation of state transitions for industrial real-time
systems. To allow expression of uncertainty, we shall define
fluents as disjuncts of positive/negative time-varying
properties. A state of the world is represented as a collection
of fluents, which is usually incomplete in the sense that
neither the positive form nor the negative form of some
properties can be implied from it. The world under consideration
is assumed to persist in a given state until an action(s)
takes place to effect a transition of it into another state,
where actions may either be instantaneous or durative.
High-level causal laws are characterized in terms of relationships
between actions and the involved world states. An effect
completion axiom is imposed on each causal law to guarantee
that all the fluents that can be affected by the performance
of the corresponding action are governed. This completion
requirement is practical for most industrial real-time
applications and in fact provides a simple and effective
treatment to the so-called frame problem.