Wajdi T. Joudah Al-Rubaye; Ah med Al-Araji1; Hayder A. Dhahad
Volume 20, Issue 3 , July 2020, , Page 50-64
Abstract
This paper proposes an off-line adaptive digital Proportional Integral Derivative (PID) control algorithm based on Field Programmable Gate Array (FPGA) for Proton Exchange Membrane Fuel Cell (PEMFC) Model. The aim of this research is to obtain the best hydrogen partial pressure (PH2) value using FPGA ...
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This paper proposes an off-line adaptive digital Proportional Integral Derivative (PID) control algorithm based on Field Programmable Gate Array (FPGA) for Proton Exchange Membrane Fuel Cell (PEMFC) Model. The aim of this research is to obtain the best hydrogen partial pressure (PH2) value using FPGA emulator to design and implement a digital PID controller that track the fuel cell output voltage during a variable load current applied. The off-line Particle Swarm Optimization (PSO) algorithm is used for finding and tuning the optimal value of the digital PID controller parameters that improve the dynamic behavior of the closed loop digital control fuel cell system and to achieve the stability of the desired output voltage of fuel cell. The numerical simulation results (MATLAB) package and FPGA emulator experimental work show the performance of the proposed FPGA-PID controller in terms of voltage error reduction and generating optimal value of the (PH2) control action without oscillation in the output and no saturation state when these results are compared with other control methodology.
Essra A. Jaber; Ahmed S. Al-Araji; Hayder A. Dhahad
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 theproposed robust feedback nonlinear PID neural predictive voltage controller isto find the optimal ...
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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 theproposed robust feedback nonlinear PID neural predictive voltage controller isto find the optimal value of the hydrogen partial pressure action in order tocontrol the stack terminal voltage of the (PEMFC) model for one-step-aheadprediction. The Chaotic Particle Swarm Optimization (CPSO) is utilized as astable and intelligent robust on-line auto-tuning algorithm to obtain the nearoptimal weights for the proposed controller so as to improve the performanceindex of the system as well as to minimize the energy consumption. TheSimulation results demonstrated the effectiveness of the proposed controllercompared with the linear PID neural controller