Extremum seeking‐based observer design for reduced order models of coupled thermal and fluid systems. (20th April 2021)

• Record Type: Journal Article
• Authors: Koga, Shumon; Benosman, Mouhacine; Borggaard, Jeff
• Other Names: Benosman Mouhacine guestEditor.; Krstić Miroslav guestEditor.; Guay Martin guestEditor.; Teel Andrew guestEditor.
• Is Part Of: International journal of adaptive control and signal processing. Volume 35:Number 7(2021)
• Page Start: 1316
• Page End: 1335
• Publication Date: 2021-04-20
• Subjects: Boussinesq equation -- extremum seeking -- input‐state stability -- iterative feedback tuning -- observer design -- thermo‐fluid models; Adaptive control systems -- Periodicals; Adaptive signal processing -- Periodicals; 629.836
• DOI: 10.1002/acs.3252
• Languages: English
• ISSNs: 0890-6327

Abstract

Summary: We present an extremum seeking (ES)‐based robust observer design for thermal‐fluid systems, pursuing an application to efficient energy management in buildings. The model is originally described by Boussinesq equations which is given by a system of two coupled partial differential equations (PDEs) for the velocity field and temperature profile constrained to incompressible flow. Using proper orthogonal decomposition, the PDEs are reduced to a set of nonlinear ordinary differential equations. Given a set of temperature and velocity point measurements, a nonlinear state observer is designed to reconstruct the entire state under the error of initial states, and model parametric uncertainties. We prove that the closed loop system for the observer error state satisfies an estimate of L 2 norm in a sense of locally input‐to‐state stability with respect to parameter uncertainties. Moreover, the uncertain parameters estimate used in the designed observer are optimized through iterations of a data‐driven ES algorithm. Numerical simulation of a two‐dimensional Boussinesq PDE illustrates the performance of the proposed adaptive estimation method.