基于神经网络模型的直接优化预测控制

针对具有时延的非线性系统提出了一种基于神经网络模型直接优于的预测控制。

DIRECT OPTIMIZING PREDICTIVE CONTROL BASED ON NEURAL NETWORK

This paper addresses a kind of predictive control based on neural network(NN) for nonlinear systems with time-delay. The off-line NN model is obtained by using Hierarchical Genetic Algorithms(HGA) to train a sequence data of input and output . Multi-step output predictions are obtained by mapping recursively NN model .The error rectification term is introduced into a performance function directly for on-line control.And it can overcome the influences of mismatched model and disturbances etc. Simulations show systems have good dynamic responses and robustness.