@incollection{GaidaWolfB{\"a}cketal.2014,
  author    = {Gaida, Daniel and Wolf, Christian and B{\"a}ck, Thomas and Bongards, Michael},
  title     = {Multi-objective nonlinear model predictive substrate feed control of a biogas plant},
  booktitle = {Kompendium der Forschungsgemeinschaft :metabolon 2012-2014},
  institution = {Fakult{\"a}t 10 / :metabolon Institut},
  year      = {2014},
  abstract  = {In this paper a closed-loop substrate feed control for agricultural biogas plants is proposed. In this case, multi-objective nonlinear model predictive control is used to control composition and amount of substrate feed to optimise the economic feasibility of a biogas plant whilst assuring process stability. The control algorithm relies on a detailed biogas plant simulation model using the Anaerobic Digestion Model No. 1. The optimal control problem is solved using the state-of-the-art multi-objective optimization method SMS-EGO. Control performance is evaluated by means of a set point tracking problem in a noisy environment. Results show, that the proposed control scheme is able to keep the produced electrical energy close to a set point with an RMSE of 0.9 \%, thus maintaining optimal biogas plant operation.},
  subject      = {Biogas},
  language  = {en}
}