论文标题
非线性在线参数标识的模型参考自适应系统方法
A model reference adaptive system approach for nonlinear online parameter identification
论文作者
论文摘要
例如，在模型预测控制中，动态系统通常包含未知参数，必须在系统操作期间确定。因此，需要在线或即时参数识别方法。在线方法的挑战是，随着实验数据的可用，必须连续估计参数。在时间相关的部分微分方程的背景下，现有技术排除了系统非线性取决于参数的情况。基于模型参考自适应系统方法，我们提出了一种在线参数识别方法，用于非线性无限二维进化系统。
Dynamical systems, for instance in model predictive control, often contain unknown parameters, which must be determined during system operation. Online or on-the-fly parameter identification methods are therefore necessary. The challenge of online methods is that one must continuously estimate parameters as experimental data becomes available. The existing techniques in the context of time-dependent partial differential equations exclude the case where the system depends nonlinearly on the parameters.Based on a model reference adaptive system approach, we present an online parameter identification method for nonlinear infinite-dimensional evolutionary system.
