Hybrid Intelligent Inverse Optimal Control for Methane Production in an Anaerobic Process

Chemical and biochemical engineering quarterly

S. Carlos-Hernandez¹  K. J. Gurubel¹  E. N. Sanchez¹  F. Ornelas-Tellez¹ 

关键词: Anaerobic process;    methane production;    hybrid intelligent control;    neural observer;    inverse optimal neural control;    Takagi-Sugeno supervisor;   

DOI  :  

来源: Croatian Society of Chemical Engineers

【 摘 要 】

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 methane production reference trajectory; this control law is based on speed-gradient inverse optimal neural control, b) a nonlinear discrete-time recurrent high-order neural observer is used to estimate biomass concentration, substrate degradation and inorganic carbon, and c) a Takagi-Sugeno supervisor, which detects the process state, selects and applies the most adequate control action, allowing a smooth switching between open loop and closed loop. The applicability of the proposed scheme is illustrated via simulations considering a completely stirred tank reactor.

【 授权许可】

Unknown