Temperature Control in Water-Gas Shift Reaction with Adaptive Dynamic Programming

作者: Yuzhu Huang , Derong Liu , Qinglai Wei

DOI: 10.1007/978-3-642-31362-2_53

关键词:

摘要: In this paper, a neural network (NN)-based adaptive dynamic programming (ADP) algorithm is employed to solve the optimal temperature control problem in water-gas shift (WGS) process. Since WGS process has characteristics of nonlinearity, multi-input, time-delay and strong coupling, it very difficult establish precise model achieve using traditional methods. We develop an NN conversion furnace data gathered from process, then controller based on dual heuristic (DHP) optimize WGS. Simulation results demonstrate effectiveness neuro-controller.

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