Title : Feasible Performance Evaluations of Digitally-Controlled Auxiliary Resonant Commutation Snubber-Assisted Three Phase Vo



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7.1Comparison of BFOA and ABCA

Figure 24 shows the time taken by the BFOA tuned controller and the ABCA tuned controller for meeting the stopping criteria. The performance parameters of the PID controller, BFOA tuned PID controller and the ABCA tuned PID controller are tabulated in Table 2.



Fig. 24 stopping criteria

It is obvious that the PID controller parameters when tuned with the ABC algorithm produce an output with very negligible overshoot and lesser settling time. Thus ABC tuning produces better controller performance than the BFO tuning of the PID controlled Buck converter. Also, ABC tuning takes less computation time to reach the optimal solution when compared with BFO tuning which is shown in Figure 18.
8. Conclusion

In this paper, the performance of traditional linear PID controller which is optimized using two nature inspired algorithms: Bacterial Foraging Optimization Algorithm (BFOA) and Artificial Bee Colony Algorithm (ABCA) have been evaluated and compared with that of the highly non linear PID based Sliding Mode Controller. These controllers have been designed for a dc-dc Buck Converter. The results show that the ABCA converges at a faster rate than that of the BFOA. Moreover, the BFOA tuned PID controller and ABCA tuned PID controller outperforms that of the PID based sliding mode controller. Hence it can be concluded that while tuning the conventional, simple, most popular PID controlled Buck converter using ABC algorithm, its performance gets upgraded than that of the robust but complicated sliding mode controller.



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