首页> 外文期刊>International Journal of Robust and Nonlinear Control >Robust design of iterative learning control for a batch process described by 2D Roesser system with packet dropouts and time-varying delays
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Robust design of iterative learning control for a batch process described by 2D Roesser system with packet dropouts and time-varying delays

机译:2D Roesser系统与分组丢失和时变延迟描述的批处理学习控制的稳健设计

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Batch process, working as a best choice for low-volume and high-value products in manufacturing, has been widely used in chemical industries. The actuator faults and time delays often occur in practical production. This paper develops an iterative learning control (ILC) design for a batch process described by two-dimensional (2D) Roesser system with packet dropouts and time-varying delays. The phenomenon of actuator faults is regarded as an arbitrary stochastic sequence satisfying the Bernoulli random binary distribution. Firstly, the ILC design for a batch process is transformed into stability analysis for a 2D stochastic system with time-varying delays. Secondly, for analyzing the stability of 2D stochastic systems, we derive the stability condition in terms of linear matrix inequality. Then, we give a procedure to get the control gain for the ILC design. An injection modeling process as an example with simulations in different cases of data dropout is given to demonstrate the validity of the proposed method. Furthermore, the proposed method has a better result by comparing the existing methods.
机译:批处理,作为制造业低价和高价值产品的最佳选择,已广泛应用于化工工业。执行器故障和时间延迟通常发生在实际生产中。本文开发了一种迭代学习控制(ILC)设计,用于二维(2D)瑞塞系统,具有分组丢失和时变延迟的二维(2D)roesser系统描述的批处理。致动器故障现象被认为是满足Bernoulli随机二元分布的任意随机序列。首先,具有时变延迟的2D随机系统的稳定性分析转变为批处理的ILC设计。其次,为了分析2D随机系统的稳定性,我们在线性矩阵不等式方面获得了稳定性条件。然后,我们给出一个程序来获得ILC设计的控制增益。给出注射建模过程作为不同数据辍学情况下的模拟的示例,以证明所提出的方法的有效性。此外,通过比较现有方法,所提出的方法具有更好的结果。

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