Authors
1 Control and Systems Engineering Department, University of Technology, Baghdad-Iraq
2 Computer Engineering Department, University of Technology, Baghdad, Iraq
3 Mechanical Engineering Department, University of Technology, Baghdad-Iraq
Abstract
This paper proposes a predictive nonlinear PID neural voltagetracking controller design for Proton Exchange Membrane Fuel Cell (PEMFC)
Model with an on-line auto-tuning intelligent algorithm. The purpose of the
proposed robust feedback nonlinear PID neural predictive voltage controller is
to find the optimal value of the hydrogen partial pressure action in order to
control the stack terminal voltage of the (PEMFC) model for one-step-ahead
prediction. The Chaotic Particle Swarm Optimization (CPSO) is utilized as a
stable and intelligent robust on-line auto-tuning algorithm to obtain the nearoptimal weights for the proposed controller so as to improve the performance
index of the system as well as to minimize the energy consumption. The
Simulation results demonstrated the effectiveness of the proposed controller
compared with the linear PID neural controller
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