Reducing the computational effort of optimal process controllers for continuous state spaces by using incremental learning and post-decision state formulations

• Published in: Journal of process control Vol. 24; no. 3; pp. 133 - 143
• Main Authors: Senn, Melanie, Link, Norbert, Pollak, Jürgen, Lee, Jay H.
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.03.2014
• Subjects: Approximate Dynamic Programming; Artificial Neural Network; Continuous state space; Dynamic Programming; Optimal control; Continuous state space; Artificial Neural Network; Dynamic Programming; Optimal control; Approximate Dynamic Programming

•We have realized multiple optimal control approaches for continuous state spaces.•Stochastic influences in the state space are taken into account.•We compare the control approaches by their efficiency and computational effort.•The evaluation sample problem allows us to apply all suggested approache...