Mu, Baojie (The University of Texas at Dallas), Li, Yaoyu (University of Texas at Dallas), Seem, John E. (Johnson Controls Inc.)

Comparison of Several Self-Optimizing Control Methods for Efficient Operation for a Chilled Water Plant

Scheduled for presentation during the Contributed session "Flow and Thermal Systems" (WeAT4), Wednesday, October 23, 2013, 11:55−12:15, Paul Brest West

6th Annual Dynamic Systems and Control Conference, October 21-23, 2020, Stanford University, Munger Center, Palo Alto, CA

This information is tentative and subject to change. Compiled on April 24, 2024

Abstract

Self-optimizing control methods have received significant attention recently, due to the merit of nearly model-free capability of real-time optimization. Of particular interest in our study are two classes of self-optimizing control strategies, i.e. the Extremum Seeking Control (ESC) and Simultaneous Perturbation Stochastic Approximation (SPSA). Six algorithms, including dither ESC, adaptive dither ESC, switching ESC, one-measurement SPSA, and adaptive one-measurement SPSA are compared based on simulation study with a Modelcia based virtual plant of chiller-tower plant. The integral performance indices are evaluated to incorporate both transient and steady-state characteristics. Some design procedures are summarized for these self-optimizing control algorithms.