执行器故障多率采样间歇过程的鲁棒耗散迭代学习容错控制

Robust dissipative iterative learning fault-tolerant control for multi-rate sampling batch process with actuator failure

针对一类具有干扰和执行器故障的多率采样间歇过程,提出一种具有鲁棒耗散性能的迭代学习容错控制算法.通过提升技术将多采样率过程用慢速率采样的状态空间模型来描述,并基于二维系统理论,把迭代学习控制过程转化为等价2D Roesser故障系统,再沿时间和迭代方向设计具有耗散性能的反馈容错控制器,并以线性矩阵不等式形式给出容错控制器存在的充分条件,同时确保多率采样间歇过程在正常和故障条件下的耗散性能.注塑过程的注射速度控制仿真验证了方法的有效性和可行性.

For a class of multi-rate sampling linear batch process with disturbances and actuator faults,this paper presents an iterative learning fault-tolerant control algorithm with robust dissipative performances.The multi-rate sampling process is described by a state-space model with low sampling rate by using the lifting technology and based on the twodimensional（2D） system theory.The iterative learning control process is transformed to an equivalent 2D Roesser system with structure-form faults;and then,the feedback fault-tolerant controller with dissipative performances is designed along the time and the trial directions.The sufficient conditions for the existence of the controller are given in terms of linear matrix inequalities（LMIs）.Therefore,it can ensure the dissipative performances in normal and fault conditions for multirate sampling batch process.The injection velocity control simulations on the injection molding process demonstrate the feasibility and effectiveness of the proposed method.