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

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Abstract

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 has been of high importance in practice for 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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APA

Khleaf, H. K., Nahar, A. K., & Jabbar, A. S. (2019). Intelligent control of DC-DC converter based on PID-neural network. International Journal of Power Electronics and Drive Systems, 10(4), 2254–2262. https://doi.org/10.11591/ijpeds.v10.i4.pp2254-2262

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