Adaptive Gains Sliding Mode Observer for the Estimation of Unknown Dynamics in a Heavy Metal Bioremediation Process

Water contamination by heavy metals from indus-trial sources affects public health and harms flora and fauna. Bioreactors using microalgae can remove these metals, but their sensors are often expensive and invasive. To address this, observation algorithms based on sliding modes are proposed to estimate unknown parameters and external disturbances, like changes in the dilution factor due to input regulation issues. Adaptive gains were added to these algorithms. The study evaluates and compares their performance to analyze their advantages and disadvantages.