Adaptive Control Scheme for Large‐Scale Interconnected Systems Described by Hammerstein Models. Issue 3 (12th January 2017)

• Record Type: Journal Article
• Authors: Elloumi, Mourad; Kamoun, Samira
• Is Part Of: Asian journal of control. Volume 19:Issue 3(2017)
• Page Start: 1075
• Page End: 1088
• Publication Date: 2017-01-12
• Subjects: Interconnected large‐scale nonlinear systems -- stochastic time‐varying systems -- discrete Hammerstein models -- adaptive control -- parametric estimation -- interconnected hydraulic process; Automatic control -- Periodicals; Control theory -- Periodicals; 629.805
• DOI: 10.1002/asjc.1443
• Languages: English
• ISSNs: 1561-8625

Abstract

Abstract: This paper proposes an adaptive algorithm for the online control of discrete‐time large‐scale nonlinear systems, which reduces the noise effects acting on the system output (regulation problem) and allows the system output to keep track of a time‐varying trajectory (tracking problem). We consider a large‐scale nonlinear system that can be decomposed into single‐input single‐output (SISO) interconnected nonlinear subsystems with known structure variables (orders, delays) and unknown time‐varying parameters. Each interconnected subsystem is described by block‐oriented models, specifically a discrete‐time Hammerstein model. Parameter adaptation is performed using a recursive parametric estimation algorithm based on the adjustable model method and the least squares techniques. Simulation results of an interconnected petroleum process are provided to demonstrate the effectiveness of the developed control scheme.