Trajectory Bounds of Input-to-State Stability for Nonlinear Model Predictive Control∗. Issue 8 (2015)

• Record Type: Journal Article
• Authors: Griffith, Devin W.; Biegler, Lorenz T.
• Is Part Of: IFAC-PapersOnLine. Volume 48:Issue 8(2015)
• Page Start: 1027
• Page End: 1032
• Publication Date: 2015
• Subjects: optimal control -- nonlinear programming -- model-based control -- robust stability -- multivariable feedback control -- predictive control; Automatic control -- Periodicals; 629.805
• DOI: 10.1016/j.ifacol.2015.09.103
• Languages: English
• ISSNs: 2405-8963

Abstract

Abstract: Model predictive control (MPC) is an optimization-based tool that is widely used in the chemical industry, and nonlinear MPC (NMPC) expands the technology to handle more detailed models that are accurate across a wider range of state values. Many works in the literature have studied NMPC using Input-to-State Stability (ISS). The purpose of this work is to provide a method for calculating state trajectory bounds for NMPC using ISS theory. These predictive bounds are derived in terms of parameters that may be found from a series of open loop calculations in the general nonlinear case. Results are shown for a scalar linear system and a nonlinear CSTR, and the challenges involved with higher dimensional problems are discussed.