基于三次样条滚动优化多步预测算法的网络学习控制

Networked Learning Control Based on Multi-step Prediction Algorithm of Cubic Spline Rolling Optimization

对于网络延时给基于网络学习的控制带来的不利影响,提出了基于三次样条滚动优化多步预测模型和神经网络在线调节的复合控制,并对令牌网上的复杂、时变、非线性及有外部干扰的被控对象进行了跟踪控制仿真.仿真结果表明:采用本文的复合控制策略,能够较好地克服网络延时对复杂对象控制所产生的不利影响,具有很好的快速性和跟踪精度.

For the adverse effect caused by network delay on networked-learning-based control, a composite control is proposed based on multi-step prediction model of cubic spline rolling optimization and on-line adjustment of neural network. Tracking control simulation is performed on the complex, time-varying and nonlinear controlled object with external disturbances in Token network. Simulation results show that the adverse effect caused hy network delay on the controlled complex object can be overcome, and rapidity and high-precision tracking can bc achieved by applying the composite control strategy.