A New Simple-to-Configure Self-Perturbing Multivariable Extremum-Seeking Controller

TL;DR

This paper introduces a simple, easy-to-configure stochastic relay-based extremum-seeking controller for MISO systems, effective for static and dynamic optimization with minimal parameters.

Contribution

The work develops a new extremum-seeking algorithm that is significantly easier to configure than existing methods, requiring only one parameter per input channel.

Findings

Successful simulation of static system optimization.

Effective dynamic system optimization demonstrated.

Simplified configuration process validated.

Abstract

This paper presents a new stochastic relay-based extremum-seeking controller (ESC) for multi-input-single-output (MISO) systems. The goal of this work was to create an algorithm that is much simpler to configure than alternative approaches making deployment to real-world problems easier. A solution is developed first for a static map and then adapted for a general class of dynamic systems. The number of configurable parameters is one per input channel for the static case and only one additional parameter is needed for the dynamic version. The problem of gradient identification is solved via the use of stochastic relay gains and a simple stability proof for the static case is presented. Simulation tests demonstrate the performance of the strategy for optimizing both static and dynamic systems.