Current control theory and practice presumes that the controller is
supplied a target (reference or setpoint) for the system variable to be controlled. In contrast, many industrial manufacturing plants are
required to produce their products to specifications. Such specifications most often consist of some nominal product quality (e.g., coating
thickness, boiling point, etc.), as well as upper and / or lower acceptable limits for the product quality variables. In essence, the
operating objectives of many manufacturing processes are to produce product with some desirable product quality distribution.
Our work has
focused on development of control techniques that can shape the product quality distribution to meet customer requirements, while simultaneously
minimizing the cost of control. Our research has been a very interesting blend of stochastic and nonlinear control theory, functional analysis,
probability theory, with some ideas drawn from optimization and parameter estimation. Current work in the mathematics of finance has
provided valuable insight.
