未知参数非线性系统的自适应广义预测控制  

Adaptive Generalized Predictive Control of Nonlinear Systems with Unknown Parameters

作　　者：兰旭颖[1] 林锦国[1] 

机构地区：[1]南京工业大学自动化与电气工程学院,江苏南京210009

出　　处：《计算机仿真》2011年第10期138-140,145,共4页Computer Simulation

基　　金：国家863计划基金资助项目(2009AA04Z161)

摘　　要：研究非线性系统的稳定性和跟踪优化问题,针对未知参数非线性系统的参数辨识和输出跟踪问题,给出参数自适应广义预测控制方法,为使辨识模型能实时反映被控对象特性以及输出对设定值的跟踪有较高精度。提出将非线性系统转化为受控自回归滑动平均模型,根据输入输出数据辨识模型参数。采用广义预测控制滚动优化的策略得出最优控制律,将最优控制律作用于对象实现非线性系统的优化控制以及系统输出对设定值的跟踪控制。明显克服了自适应控制对模型精度要求高的缺陷且具有在线辨识,滚动优化的特点。最后,通过仿真实例验证了方法的有效性。An adaptive generalized predictive control was formulated to solve the problems that an unknown parameter nonlinear system is hard to be identified and track the setting trajectory.It achieves that identification model reflects the controlled object properties in real-time and the outputs have a high precision tracking.A nonlinear model was replaced by a controlled auto-regressive integrated moving average model.According to the input and output data,the identification model parameters can be obtained.The optimized control law can be gained through the receding horizon optimization tactics,the optimized control and tracking control of the nonlinear system were realized by using the optimized control law.Further,the effectiveness of this proposed method was confirmed by the simulation.

关 键 词：非线性系统 参数辨识 自适应广义预测控制 

分 类 号：TP273[自动化与计算机技术—检测技术与自动化装置]