Skip to main content
Article thumbnail
Location of Repository

Hybrid Modeling Based Adaptive Neural Controller

By Alois Mészáros and Sebastião Feyo De Azevedo


Abstract — In this paper, a new control technique for nonlinear control based on hybrid modeling is proposed. The control system utilizes the well-known gradient descent, but the learning rate is adapted in each iteration step in order to accelerate the speed of convergence. It is shown that the selection of the learning rate results in stable training in the sense of Lyapunov. Advantages of this technique are illustrated by simulations where a continuous flow stirred biochemical reactor is chosen as a case study

Topics: PID controller
Year: 2009
OAI identifier: oai:CiteSeerX.psu:
Provided by: CiteSeerX
Download PDF:
Sorry, we are unable to provide the full text but you may find it at the following location(s):
  • (external link)
  • (external link)
  • Suggested articles

    To submit an update or takedown request for this paper, please submit an Update/Correction/Removal Request.