Intelligent control of DC-DC converter based on PID-neural network

Hussain K. khleaf, Ali kareem Nahar, Ansam Subhi Jabbar


This paper introduced a “PID-NN” based on Particle Swarm Optimization control that was applied to a boost converter operating in large-signal domains. Simulation results have shown that the proposed “PID-NN controller” could enhance the (boost converter) startup response with the use of fewer on-off switch operations compared to the Conventional “PID controllers”. This result is of high importance in practice since reducing the number of on-off switches can effectively decrease the transient disturbances and losses due to switching. Simulations also prove that the proposed “PID-NN controller” is capable of efficiently improving rejecting potential disturbances that could happen in the input voltage. Moreover, it has been noticed that the output voltage is more efficiently controlled when applying “PID-NN controller”. The results of the simulation show the efficiency of the suggested algorithm compared with other well-known learning methods.

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Copyright (c) 2019 Hussain K. khleaf, Ali kareem Nahar, Ansam Subhi Jabbar

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