Abstract

In this work we focus on the synergy between modeling with RNNs, and nonlinear controller design for decoupling control. The thesis of the paper is that recurrent neural networks (RNNs) can be conveniently used in an integrated black-box modeling and controller design methodology for decoupling control of multivariable nonlinear systems. A simulation example on a multivariable continuous-stirred-tank-reactor (CSTR) is provided to elucidate related issues. The effects of modeling uncertainty and state reconstruction on decoupling performance are specifically discussed.

Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call