Thomas A. Badgwell

TL;DR: An overview of commercially available model predictive control (MPC) technology, both linear and nonlinear, based primarily on data provided by MPC vendors, is provided in this article, where a brief history of industrial MPC technology is presented first, followed by results of our vendor survey of MPC control and identification technology.

TL;DR: In this article, the authors provide an overview of nonlinear model predictive control (NMPC) applications in industry, focusing primarily on recent applications reported by NMPC vendors, and present five industrial NMPC implementations with reference to modeling, control, optimization and implementation issues.

TL;DR: This work states that nonlinear model predictive control, i.e. MPC based on a nonlinear plant description, has only emerged in the past decade and the number of reported industrial applications is still fairly low.

TL;DR: In this article, a general disturbance model that accommodates unmeasured disturbances entering through the process input, state, or output is presented, and conditions for which offset-free control is possible are stated for the combined estimator, steady-state target calculation, and dynamic controller.

TL;DR: In this paper, a method and apparatus for steady-state target calculation that explicitly accounts for model uncertainty is presented, and a nominal estimate of the system parameters G is made, and the steady state targets are selected such that when G = G, the system is driven to an operational steady state in which the objective function is extremized.