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2.8 Conclusion

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Resembling the fractional-order dynamics of gas flow, the pneumatic system also has similar dynamics. Based on the analysis from the literature survey, it has been found that the fractional-order controllers provide enhanced control for the systems that possess fractional-order dynamics. Hence, in this work, FOPID controllers are used to control pneumatic position servo system. One of the challenging issues while applying FOPID controller is the tuning of parameters. In this paper, MMGA method based on Pareto rank is proposed for tuning FOPID parameters. It is evident from the results that FOPID is exceeding IPID in terms of greater accuracy and less energy consumption. It is worthwhile to point out that the dynamic behavior of FOPID controllers are superior to PID controllers. The efficacy of the proposed method is also exhibited by comparing its performance with six methods proposed in the literature. The pneumatic position control system using FOPID gives the best performance than IPID controller. GA is used to find the optimized values of FOPID controller. This paper discussed about the implementation of optimized FOPID controller using GA to find the maximum fitness solution. Simulation results in MATLAB and hardware results from PIC microcontroller validated the proposed algorithm thereby showing the superior performance of FOPID over IPID controller in a pneumatic position servo system.

Smart Systems for Industrial Applications

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