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.
- Dynamic Systems and Control Division
Comparison of Several Self-Optimizing Control Methods for Efficient Operation for a Chilled Water Plant
Mu, B, Li, Y, & Seem, JE. "Comparison of Several Self-Optimizing Control Methods for Efficient Operation for a Chilled Water Plant." Proceedings of the ASME 2013 Dynamic Systems and Control Conference. Volume 2: Control, Monitoring, and Energy Harvesting of Vibratory Systems; Cooperative and Networked Control; Delay Systems; Dynamical Modeling and Diagnostics in Biomedical Systems; Estimation and Id of Energy Systems; Fault Detection; Flow and Thermal Systems; Haptics and Hand Motion; Human Assistive Systems and Wearable Robots; Instrumentation and Characterization in Bio-Systems; Intelligent Transportation Systems; Linear Systems and Robust Control; Marine Vehicles; Nonholonomic Systems. Palo Alto, California, USA. October 21–23, 2013. V002T25A006. ASME. https://doi.org/10.1115/DSCC2013-4097
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