Abstract In this paper, a genetic-fuzzy control scheme is applied to an active free piston Stirling engine (AFPSE) to achieve a hybrid intelligent converter that is robust to parameter changes.… Click to show full abstract
Abstract In this paper, a genetic-fuzzy control scheme is applied to an active free piston Stirling engine (AFPSE) to achieve a hybrid intelligent converter that is robust to parameter changes. Indeed, the open-loop AFPSE possesses an optimum performance at a distinct operating frequency. However, the optimal frequency of the open-loop engine system is affected by several parameters such as sink and source temperatures, power piston mass, and stiffness of the power piston’s spring. Consequently, there remain some rooms for an intelligent control unit in the open-loop AFPSE such that a maximum power is acquired under different uncertainties and parameter changes. First, a brief description of the mathematical equations governing the open-loop AFPSE is given. Then, an intelligent fuzzy control unit is proposed to control the engine and a genetic algorithm (GA) is used to achieve an optimal fuzzy controller. Accordingly, the output power of the engine is considered as the cost function of GA in the control design problem. Finally, the simulation and practical results reveal the feasibility of design and the benefits of the proposed novel intelligent AFPSE (IAFPSE). Moreover, based on the obtained practical outcomes, it is found that the IAFPSE is robust against the changes of power piston mass ranging from 0.6 kg to 1 kg over which the operating frequency is intelligently tuned from 5.4 Hz to 4.3 Hz respectively.
               
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