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Robust analytical proportional‐integral‐derivative tuning rules for regulation of air pressure in supply manifold of proton exchange membrane fuel cell

K. Ghousiya Begum, Balasubramanian Ganesan

2020Asia-Pacific Journal of Chemical Engineering11 citationsDOI

Abstract

Abstract The core aim of this manuscript is to recommend analytical tuning rules to regulate and control the air supply pressure moving from the supply manifold (SM) to the electrode (cathode) of proton exchange membrane fuel cell (PEMFC). This is done to have an optimal oxygen excess ratio in the fuel cell for enhanced energy generation. The higher order dynamics of PEMFC is approximated to be non‐integer first‐order stable plus time delay model. A simple proportional ‐integral/proportional‐integral‐derivative (PI/PID) control scheme is designed for a specific maximum sensitivity ( Ms ) using analytical tuning rules. This, in turn, enhances its dynamic performance by regulating the SM pressure. The proposed integer order PI/PID control technique is compared with the other fractional order IMC‐PI control techniques that are recently published. The simulation results obtained prove that the proposed tuning rules provide a good response compared with fractional order controllers and thereby maintaining the SM pressure. The robustness of the novel controller is analyzed by introducing perturbations and noise to the dynamic model. The tuning rules proposed are applicable for two maximum sensitivity values of 1.4 and 2 as a measure of robustness. To measure system performance, few time domain metrics and integral absolute error ( IAE) , integral square error ( ISE) , and TV metrics are used. For both the Ms values, the proposed techniques provide stable and improved responses.

Topics & Concepts

PID controllerRobustness (evolution)Control theory (sociology)Proton exchange membrane fuel cellSensitivity (control systems)Computer scienceMathematicsChemistryMembraneEngineeringControl engineeringElectronic engineeringTemperature controlControl (management)Artificial intelligenceBiochemistryGeneFuel Cells and Related MaterialsAdvanced Control Systems DesignAdvanced Battery Technologies Research
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