National Center for International Research on Quality-Targeted Process Optimization and Control, College of Control Science and Engineering, Zhejiang University, Hangzhou 310027, China
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.
徐祖华, 黄彦春, 陈铭豪, 赵均, 邵之江. 基于FPAA模拟神经网络的快速预测控制算法[J]. 清华大学学报（自然科学版）, 2019, 59(5): 394-402.
XU Zuhua, HUANG Yanchun, CHEN Minghao, ZHAO Jun, SHAO Zhijiang. Fast predictive control algorithm based on an FPAA analog neural network. Journal of Tsinghua University(Science and Technology), 2019, 59(5): 394-402.
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2019, Vol. 59 
