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针对一类非线性离散动态系统,设计了一个自适应控制方案。为了保证在任意时刻均能为被控的动态系统选择最好的控制器,方案基于输入输出数据为系统定义一个线性预测模型,并在此基础上设计能够保证闭环系统所有信号有界的线性鲁棒自适应控制器,同时定义一个非线性预测模型,再基于径向基神经网络设计一个旨在提高系统控制性能的非线性自适应控制器。通过比较2个控制器预测的系统输出性能,设计合理的开关切换规则。控制方案能将系统稳定性控制和性能优化的控制分离并单独实现,使得系统能在保证稳定性前提下,借助神经网络控制器良好的追踪能力有效提高自适应控制效果。最后通过仿真例子说明了系统稳定和提高输出追踪效果可以同时得到保证。
For a class of nonlinear discrete dynamic systems, an adaptive control scheme is designed. In order to ensure that the best controller can be chosen for the controlled dynamic system at any time, the scheme defines a linear prediction model for the system based on the input and output data. On the basis of this, a linear linear model is designed to ensure that all the signals in the closed-loop system are bounded Rod adaptive controller. At the same time, a nonlinear prediction model is defined. Then a nonlinear adaptive controller based on RBF neural network is designed to improve the system control performance. By comparing the system output performance predicted by the two controllers, a reasonable switching rule is designed. The control scheme can separate the system stability control from the performance optimization control and achieve them separately, which makes the system effectively improve the adaptive control effect with the good tracking ability of the neural network controller while guaranteeing the stability. Finally, the simulation example shows that the system stability and improve the output tracking effect can be guaranteed at the same time.