Fast predictive control algorithm based on an FPAA analog neural network

XU Zuhua; HUANG Yanchun; CHEN Minghao; ZHAO Jun; SHAO Zhijiang

doi:10.16511/j.cnki.qhdxxb.2019.25.004

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Journal of Tsinghua University(Science and Technology) ›› 2019, Vol. 59 ›› Issue (5) : 394-402. DOI: 10.16511/j.cnki.qhdxxb.2019.25.004

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Fast predictive control algorithm based on an FPAA analog neural network

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Abstract

A fast predictive control algorithm was developed for simpler, faster MPC optimization based on an FPAA analog neural network. An FPAA analog circuit provides the quadratic programming using a continuous neural network which avoids the convergence problem of discrete neural networks in a fast, simple and flexible algorithm that uses less computational resources than previous methods. The signal constraint of the FPAA analog circuit is solved by translation and scaling. The software and hardware design of the FPAA analog neural network predictive control is presented and verified in tests that show that the algorithm is effective.

Key words

fast model predictive control / field programmable analog array (FPAA) / analog neural network

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XU Zuhua, HUANG Yanchun, CHEN Minghao, ZHAO Jun, SHAO Zhijiang. Fast predictive control algorithm based on an FPAA analog neural network[J]. Journal of Tsinghua University(Science and Technology). 2019, 59(5): 394-402 https://doi.org/10.16511/j.cnki.qhdxxb.2019.25.004

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