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- Title
Multiobjective Genetic Algorithm-Based Optimization of PID Controller Parameters for Fuel Cell Voltage and Fuel Utilization.
- Authors
Qin, Yuxiao; Zhao, Guodong; Hua, Qingsong; Sun, Li; Nag, Soumyadeep
- Abstract
Nowadays, given the great deal of fossil fuel consumption and associated environmental pollution, solid oxide fuel cells (SOFCs) have shown their great merits in terms of high energy conversion efficiency and low emissions as a stationary power source. To ensure power quality and efficiency, both the output voltage and fuel utilization of an SOFC should be tightly controlled. However, these two control objectives usually conflict with each other, making the controller design of an SOFC quite challenging and sophisticated. To this end, a multi-objective genetic algorithm (MOGA) was employed to tune the proportional–integral–derivative (PID) controller parameters through the following steps: (1) Identifying the SOFC system through a least squares method; (2) designing the control based on a relative gain array (RGA) analysis; and (3) applying the MOGA to a simulation to search for a set of optimal solutions. By comparing the control performance of the Pareto solutions, satisfactory control parameters were determined. The simulation results demonstrated that the proposed method could reduce the impact of disturbances and regulate output voltage and fuel utilization simultaneously (with strong robustness).
- Subjects
BURNUP (Nuclear chemistry); SOLID oxide fuel cells; PID controllers; FUEL cells; WATER distribution; LEAST squares
- Publication
Sustainability (2071-1050), 2019, Vol 11, Issue 12, p3290
- ISSN
2071-1050
- Publication type
Article
- DOI
10.3390/su11123290