Extremum seeking control and gradient estimation based on the Super-Twisting algorithm. (September 2021) - Torres-Zúñiga, Ixbalank; López-Caamal, Fernando; Hernández-Escoto, Héctor; Alcaraz-González, Víctor
Abstract: 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. Graphical abstract: Highlights: An extremum seeking control strategy of a continuous-time dynamical system with a single input and a single output is proposed. A gradient-based optimization algorithm is considered. The input–output gradient is estimated via a differentiator. The Super-Twisting algorithm is used both, as optimization algorithm and as differentiator. Feasibility of the proposed extremum seeking strategy is demonstrated by two simulation examples.