In this paper, it is shown that dynamic optimization problems of first-order systems can be transformed into a static parametric programming problem, where the state plays the role of the parameter. Thus, an optimal feedback law is obtained. This concept is applied to the diesinking Electrical Discharge Machining, a highly time varying industrial process which necessitates adaptation of machini...

Parametric programming provides solution of an optimization problem as a function of the parameters in a computationally efficient manner, without exhaustively enumerating the entire space of parameters. In a model based predictive control framework, parametric programming can be used to obtain optimal control variables as an explicit function of the state variables. The main advantage of this ...

The abstraction gap between algorithms and procedures causes numerous duplicate eeorts in implementing the same algorithms as well as apparent under-use of many eecient algorithms. A solution to this problem is to realize algorithmic abstraction at the programming language level in addition to data abstraction. In this paper, we rst discuss the two conditions for a programming language to suppo...

For controllable timed automata, a general parametric optimization framework based on automatatheory is proposed. The framework is general enough to incorporate both the parametric analysis problem and the controller synthesis problem of computer systems. We propose an algorithm for the construction of the characterization of the parameter constraints and controller synthesis, which in turn yie...