An LMI-based approach to the design of super-twisting observers with application to a lipase production process from olive oil by Candida rugosa

This paper presents a systematic methodology for designing super-twisting observers. Thanks to a state transformation, the estimation error dynamics can be cast in a Linear Parameter Varying (LPV) framework and a design procedure based on LMIs can be developed ensuring practical stability and finite time convergence. This approach is applied to the design of 3 super-twisting observers for estimating the reaction rates in a lipase production process from olive oil by Candida rugosa. The estimated rates can be used in an asymptotic observer to reconstruct the component concentrations.