In this work, a new development of predictive voltage-tracking control algorithm for Proton Exchange Membrane Fuel Cell (PEMFCs) model, using a neural network technique based online auto-tuning intelligent algorithm was proposed. The aim of proposed robust feedback nonlinear neural predictive voltage controller is to find precisely and quickly the optimal hydrogen partial pressure action to control the stack terminal voltage of the (PEMFC) model for N-step ahead prediction. The Chaotic Particle Swarm Optimization (CPSO) implemented as a stable and robust on-line auto-tune algorithm to find the optimal weights for the proposed predictive neural network controller to improve system performance in terms of fast-tracking desired voltage and less energy consumption through investigating and comparing under random current variations with the minimum number of fitness evaluation less than 20 iterations.
This paper presents the enhancement of the output performance of a non-linear fuel cell (FC) system using a new design that comprises an adaptive SIMO-PID neural controller with different types of online swarm optimization algorithms. The work focuses on improving the use of single-input multi-output (SIMO) PID neural networks to control the non-linear FC system. The goal of the proposed adaptive SIMO-PID neural voltage-tracking controller is to rapidly and precisely identify the optimal hydrogen flow rate and oxygen flow rate control actions that are used to control the (FC) stack terminal output voltage. Three swarm optimization algorithms are used to find and tune the weights of the SIMO-PID neural controller: the Firefly algorithm, chaotic particle swarm optimization algorithm, and proposed hybrid Firefly-chaotic particle swarm optimization (F-CPSO) algorithm. Numerical simulation results show that the proposed controller using the (F-CPSO) algorithm is more accurate than with the FA or CPSO; the proposed SIMO-PID neural controller parameters are obtained more rapidly there is a high reduction in the number of function evolutions. Furthermore, the proposed controller’s ability with the F-CPSO algorithm to generate a smooth flow rate control response for the non-linear (PEMFC) system without voltage oscillation in the output is determined by investigations under load variations.
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