6.1 Conclusion
This thesis has demonstrated the self-learning fuzzy control(SLFC) system for forward type and flyback type DC-DC conveters, where the new type control algorithm SLFC has been developed in which the rule bases do not need to be prior defined. The SLFC design method can automatically generate the rule bases to achieve better performance. In the rule modifier, the modification value is obtained from fuzzy inference of modification rules so that the learning algorithm can proceed reasonably and quickly. Experimental results have been provided to demonstrate the robust control performance of the proposed control systems under the occurrence of uncertainties.
6.2 Future Work
In the future, we can apply other intelligent control strategy to implement the DC-DC converters on the FPGA board. Such as, sliding-mode self-learning control and other adaptive fuzzy control, etc. In this thesis, the FPGA implementation of the proposed control method is more complicated than PI control and fuzzy control. So what we have to do is to reduce the chip area of the FPGA processor. So the SLFC control algorithm needs to be simplified in order to make the SLFC more efficient and low cost.
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Appendix I