Adaptive and robust-adaptive control schemes for an anaerobic bioprocess with biogas production

Abstract

This paper presents the design of adaptive and robust-adaptive control strategies for an anaerobic bioprocess with biogas production. The design schemes are developed under the realistic assumption that both bacterial growth rates and influent flow rates are time-varying and uncertain, but some lower and upper bounds of these uncertainties are known. The proposed control structures are achieved by combining a linearizing control law with a state asymptotic observer or an interval observer, and with a parameter estimator used for online estimation of unknown kinetics of the process. Numerical simulations are performed to test the proposed algorithms.

Optimization of Wastewater Anaerobic Digestion Using Mechanistic and Meta-heuristic Methods: Current Limitations and Future Opportunities

“…Flores-Estrella et al [5] 2013 Mass balance model [53] COD Dilution rate Petre and Selisteanu [110] 2013 ADM- [115] 2003 Experimental data VFA Influent flow rate Yordanova [116] 2004 Mass balance model [53] Biogas output flow rate and pH…”

“…Linear control with feedforward/feedback structure Mendez-Acosta et al [117] 2005 Mass balance model [53] COD of output Inlet COD concentration estimators or observers commonly used in biological processes include asymptotic observers [110], disturbance decoupled observer [120], Luenberger observer [58,61], state observer [60], and interval observer [76]. Despite their reported satisfactory results, these observers require the total knowledge of the process variables, which are rarely available in practice.…”

“…Garcia-Dieguez et al [69] implemented multi-objective cascade controller based on VFA concentration in the effluent and methane production rate in an upflow sludge bed filter (USBF) reactor (anaerobic treatment of winery wastewater) There were also several control schemes that performed well in their simulation studies such as the Rincon et al method [60] that can handle the uncertainty in the kinetic function, biomass concentration, biological yield coefficients, kinetic parameters, and the effect of input saturation. Petre and Selisteanu's [110] robust-adaptive control strategy can be combined with a state asymptotic observer or an internal observer and a parameter estimator to estimate unknown kinetics of the process online and withstand disturbances and noisy data acting on the process and more importantly uncertainties in the growth rate and influent substrate concentration [76].…”

Integrating systems analysis and control for implementing process analytical technology in bioprocess development

“…To account for the parametric and state uncertainties of the process, the authors combined a linearizing control law with an internal observer to determine the bounds on unmeasured states. Extensive numerical simulations were performed to validate the controller and its performance was benchmarked against the performance of an exact linearizing controller . Renard et al .…”