An example of robust internal model control under variable and uncertain delay. (December 2017)

• Record Type: Journal Article
• Authors: Clerget, Charles-Henri; Grimaldi, Jean-Philippe; Chèbre, Mériam; Petit, Nicolas
• Is Part Of: Journal of process control. Volume 60(2017)
• Page Start: 14
• Page End: 23
• Publication Date: 2017-12
• Subjects: Internal model control -- Sampled-data system -- Varying time delays -- Stability analysis; Process control -- Periodicals; Fabrication -- Contrôle -- Périodiques; Process control; Periodicals; Electronic journals; 660.281
• DOI: 10.1016/j.jprocont.2017.04.003
• Languages: English
• ISSNs: 0959-1524

Abstract

Highlights: This paper studies internal model control of a nonlinear static process under model uncertainty. The main novelty of this work lies in the fact that measurements suffer from a variable time delay and that exact measurement dating is not available. We perform an original stability analysis of the problem as a time varying linear system in an appropriate norm. Robust global exponential convergence of the controller is established under meaningful conditions on the model mismatch and the gain of the controller. Abstract: This paper proposes a particular study of the classic internal model control algorithm for a sampled-data system in a generalized context of uncertainty. Besides the usually considered model mismatch, the particularity of the case under consideration is that the measurements available to the control algorithm suffer from large, varying and uncertain delays. The presented study considers a simple SISO nonlinear system. The control algorithm is a sampled nonlinear model-based controller with successive model inversion and bias correction. The main contribution of this article is its proof of global convergence and robustness despite time-varying delays and uncertain measurement dating. In particular, the model error, the varying delays and measurements dating error are treated using monotonicity of the system and a detailed analysis of the closed-loop behaviour of the sampled dynamics, in an appropriate norm.