Abstract
In this paper, an intelligent temperature control strategy is proposed for thermoelectric cooling systems. The Lyapunov-based control method allows a dynamic updating law to be employed in the fuzzy logic system to improve the system performance in the presence of unmodeled dynamics. A new smooth function is also integrated into the control loop to limit input voltage, effectively addressing potential energy waste issue. Furthermore, the controller design challenges posed by even-power input are resolved using the adaptive fuzzy control method and Lagrange’s mean value theorem. Performance analysis indicates that the control function and state signals of the refrigeration system are bounded under our proposed method. Compared with the traditional intelligent control strategy, we only need to design a dynamic update law, which effectively reduces the complexity of the algorithm and is favorable for implementation. Finally, simulation and experimental results demonstrate the effectiveness of the method proposed in this paper. Compared to the traditional PID method, our control method reduces the maximum error by 29.4% and the setting time by 35.7% in the experiment.
Published Version
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