October 2004

Special Report: Improving Process Control

Model predictive control for nonlinear processes with varying dynamics

A parametric approach produces accurate models

Axelrud, C., Liano, K., Sayyar-Rodsari, B., Pavillion Technologies, Inc.

Model predictive control (MPC) is now a widely accepted control technology in many process industry applications. Successful application of MPC technology to complex nonlinear processes with varying dynamics, however, is a difficult challenge. Meeting this challenge requires high-fidelity process models that are easy to understand, develop and maintain. Also required are computationally efficient control algorithms that are easy to implement. A varying dynamics nonlinear model predictive control (VDNLMPC) algorithm addresses these challenges. Nonlinear model predictive control (NLMPC). Arguably, MPC is one of the most important developments in process control over the past two decades.

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