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Extremum seeking control and gradient estimation based on the Super-Twisting algorithm
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DOI：10.1016/j.jprocont.2021.08.004.png)
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Abstract
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This article addresses the problem of extremum seeking of a continuous-time dynamical system with a single input and a single output. A Super-Twisting-based optimization algorithm is proposed to compute the input that leads to the extremum value of an unknown convex objective function. Our optimization algorithm requires the input-output gradient of the system's response at steady state, which we compute throughout a Super-Twisting-based differentiator. Feasibility of the proposed extremum seeking strategy is demonstrated by two simulation examples. The first one is an example of interest in academy. The second one is a novel biohydrogen production process. (C) 2021 Elsevier Ltd. All rights reserved.
Keywords:
Extremum seeking control
Sliding modes
Super-Twisting algorithm
Differentiators
Process control
Microbial electrolysis cell
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