Abstract
A multivariable adaptive feedback control for highly uncertain continuous anaerobic digestion processes is proposed to regulate the volatile fatty acids (VFA) concentration, the strong ions concentrations, and the total and intermediate alkalinities. The multivariable control scheme includes a Luenberger observer to estimate both the unmeasured variables (i.e., VFA) and unknown microbial growth kinetics. The control approach is designed using an exponential Lyapunov function to resemble the typical exponential biological growth of the involved microbial consortia. Taking into account physicochemical equilibrium, alkalinities are represented as a function of the state variables. As a result, the control problem becomes a regulation problem on alkalinities, and in turn, a tracking control problem on the state variables, with two manipulated variables—the dilution rate and the feed rate of a strong alkali solution—while the state variables’ set-points are given as a function of pH. The implementation of this multivariable control scheme was experimentally tested and validated in a 0.982 m3 pilot plant treating agro-industrial wastewater and demonstrated to be robust in the face of unknown microbial growth kinetics. Results showed the potential for practical application and optimization of industrial digesters.
Highlights
Anaerobic digestion (AD) is a very complex biological process used for treating agroindustrial wastewaters with a high variety of organic long-chain compounds, such as carbohydrates, lipids, and proteins
The control objectives, i.e., the set-points, were first established based on normal operational conditions stated by the alkalinity criteria (3–4), and formally expressed in the form of state variables based on a physicochemical analysis as in Equations (8) and (9)
A multivariable control approach was proposed to regulate the alkalinities in anaerobic digestion processes and successfully implemented on an anaerobic 0.982 m3 up-flow fixedbed bioreactor for the treatment of agro-industrial wastewater located in Narbonne, France, over 12 days in which several alkalinity set-points were tested
Summary
Anaerobic digestion (AD) is a very complex biological process used for treating agroindustrial wastewaters with a high variety of organic long-chain compounds, such as carbohydrates, lipids, and proteins. Zhang et al [40] modified the ADM1 model by integrating a more detailed physicochemical framework and by introducing inorganic carbon and nitrogen balance terms to resolve the discrepancies between the carbon and nitrogen contents, while Shi et al [41] improved the ADM1 model using a variable stoichiometric approach based on the high hydrogen partial pressures and pH These improvements provide useful information, the high dimension of the modified ADM1 makes it very difficult to implement in process control structures [42]. The ratio VFA/Z has been regulated by using a model predictive control (MPC) approach in order to achieve an optimal OS on the basis of a modified AM2 model [56] The aim in this contribution is to design, develop, and implement a multivariable adaptive feedback controller to regulate the VFA concentration and total and intermediate alkalinities to guarantee the operational stability of the AD process. It is shown that the proposed robust MIMO control scheme is robust in the face of parameter uncertainty, unknown kinetics, and pH variations, as well as in measuring disturbances
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