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.

This content is only available via PDF.
You do not currently have access to this content.