Preliminar Ideas on a Real-Time Optimization Strategy Based on the Super-Twisting Algorithm

Resumen: Real-time optimization is a control method that aims for operating a process in optimal conditions along its operation. Within this class of methods, Extremum Seeking Control is a model-free real-time optimization strategy, which uses only output measurements to compute the optimal controlled input of a process with a convex input-output map. However, its convergence time is long. In this article, a real-time optimization strategy based on the super-twisting algorithm is introduced. As shown by our simulations results, its convergence time may be shorter with respect to the gradient-based optimization algorithm used by classical extremum seeking control. The feasibility of the real-time optimization strategy proposed is demonstrated in simulations for a biohydrogen production process.

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Ixbalank Torres, Alejandro Vargas, Fernando López-Caamal & H+ector Hernández-Escoto. Preliminar Ideas on a Real-Time Optimization Strategy Based on the Super-Twisting Algorithm. Memorias del Congreso Nacional de Control Automático, pp. 353-358, 2018.

Palabras clave

Real-time optimization, gradient-based optimization, super-twisting algorithm, biohydrogen production

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