María Isabel Neria-González

Nonlinear controller design with application to a continuous bioreactor

The goal of this work is to present a mathematical model of a sulfate-reducing bioreactor where a proposed nonlinear controller is applied to regulate the dynamics of the process. The corresponding kinetic model, experimentally corroborated, is extended to simulate continuous operation, and a class of smooth controllers, under the frame of sliding modes, is proposed to control the sulfate concentration into the bioreactor employing the dilution rate as control input, with successes. The proposed controller avoids the named chattering phenomena for its smooth structure, and its performance is compared with a well tuned proportional-integral and high-order sliding-mode controllers in order to analyze their corresponding closed-loop behavior. A sketch of proof of the closed-loop stability is provided.

Finite Time Estimation for Switched Nonlinear Systems: Application to Stirred Tank Bioreactor

Abstract This work presents the design of a class of finite time observer applied to a nonlinear switched system. The proposed observer is applied to a stirred batch anaerobic bioreactor, described by classic mass balances, where a sulfate-reducing process took place and kinetic regimen alteration is induced by a change in the carbon source. The proposed observer has a simple structure and under an adequate choosing of the observer´s gain the proposed methodology cancels the upper bounds of the system under the different kinetic regimens inducing the required finite time convergence. The performance of the proposed observer is showed via numerical simulations and for comparison purposes a sliding-mode observer is also implemented, both of them are conducted and experimentally corroborated. The convergence of the observer is done with a simple analysis of the estimation error dynamic equations for all the corresponding subspaces and is showed that the convergence of the estimator is reached under the required conditions.

Partial Control of a Continuous Bioreactor: Application to an Anaerobic System for Heavy Metal Removal

This work presents a control strategy for a continuous bioreactor for heavy metal removal. For this aim, regulation of the sulfate concentration, which is considered the measured and controlled state variable, allowed diminishing the cadmium concentration in the bioreactor, where the corresponding controller was designed via nonlinear bounded function. Furthermore, a nonlinear controllability analysis was done, which proved the closed-loop instability of the inner or uncontrolled dynamics of the bioreactor. A mathematical model, experimentally corroborated for cadmium removal, was employed as a benchmark for the proposed controller. Numerical experiments clearly illustrated the successful implementation of this methodology; therefore, cadmium removal amounted to more than 99%, when the initial cadmium concentration was up to 170 mg/L in continuous operating mode.

Improvement of Activated Sludge Process Using a Nonlinear PI Controller Design via Adaptive Gain

Abstract The goal of this work was to design an adaptive nonlinear proportional–integral (PI) controller to regulate the dynamics of an aerobic wastewater bioreactor, providing a mathematical sketch of proof of the convergence of the control scheme. Adequate operating regions were determined and the corresponding steady-state points were studied via phase portrait and bifurcation analysis. The proposed controller was applied to a wastewater treatment plant to regulate dissolved oxygen (DO) concentration and, indirectly, the concentration of chemical oxygen demand (COD) in the bioreactor; the recirculation flow rate was considered as the manipulated variable. The implementation was based on the mathematical bioreactor’s model, which was experimentally verified; it describes COD dynamics, DO, biomass, recirculation biomass concentrations, and temperature. The obtained results, via numerical simulations, showed that the proposed control law is able to control DO concentration; this control exhibited better performance in comparison to a linear one.

Estimation of a class of stirred tank bioreactors with discrete-delayed measurements

Abstract This work addresses the problem of designing an on-line discrete-delayed measurement processor to estimate the state of a class of stirred tank bioreactors where the growth of sulfate reducing bacteria takes places. On the basis of the Monod-type model of the reactor, a geometric approach is straightforward applied to systematically construct and tune the data processor. The resulting estimator is tested on a continuous and a batch culture process, showing a robust convergence even in the presence of modeling errors.