Original scientific paper
Hybrid Intelligent Inverse Optimal Control forMethane Production in an Anaerobic Process
K.J. Gurubel
; CINVESTAV, Unidad Guadalajara, Departamento de Control Automático, Av. del bosque 1145, colonia el bajío, Zapopan, Jal., México 45019.
F. Ornelas-Tellez
; División de Estudios de Posgrado, Facultad de Ingeniería Eléctrica, UMSNH, F.J. Mujica SN, Ciudad Universitaria, Morelia, Mich., México 58030
E.N. Sanchez
; CINVESTAV, Unidad Guadalajara, Departamento de Control Automático, Av. del bosque 1145, colonia el bajío, Zapopan, Jal., México 45019.
S. Carlos-Hernandez
; Cinvestav, Unidad Saltillo, Grupo de Investigación en Recursos Naturales y Energéticos, Carretera Saltillo-Monterrey Km. 13.5, Ramos Arizpe, Coahuila, México 25900.
Abstract
Anaerobic processes are very attractive because of their waste treatment properties and their capacity for transforming waste materials in order to generate methane, which can be used as a renewable energy source. A hybrid intelligent control strategy for an anaerobic process is proposed in this work; the structure of this strategy is as follows: a) a control law calculates dilution rate and bicarbonate addition in order to track a methaneproduction reference trajectory; this control law is based on speed-gradient inverse optimalneural control, b) a nonlinear discrete-time recurrent high-order neural observer isused to estimate biomass concentration, substrate degradation and inorganic carbon, and
c) a Takagi-Sugeno supervisor, which detects the process state, selects and applies themost adequate control action, allowing a smooth switching between open loop and closed loop. The applicability of the proposed scheme is illustrated via simulations consideringa completely stirred tank reactor.
Keywords
Anaerobic process; methane production; hybrid intelligent control; neural observer; inverseoptimal neural control; Takagi-Sugeno supervisor
Hrčak ID:
104821
URI
Publication date:
1.7.2013.
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