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本文提出一种以小脑模型 (CMAC)网络为多步预测模型的非线性预测控制算法 ,并将启发式遗传算法引入到滚动优化中 ,以提高优化过程的收敛速度和求解精度。仿真结果表明该算法是有效可行的
In this paper, we propose a nonlinear predictive control algorithm based on the cerebellar model (CMAC) network as a multi-step predictive model. The heuristic genetic algorithm is introduced into the rolling optimization to improve the convergence speed and accuracy of the optimization process. Simulation results show that the algorithm is effective and feasible