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A tube feedback iterative learning control for batch processes

机译：用于批处理的管反馈迭代学习控制

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Optimization-based iterative learning control (OILC) has been widely applied to batch processes due to its fast convergence, good control performance and ability to handle constraints. However, how to guarantee constraint satisfaction and convergence of tracking error in the presence of unknown system nonlinearity remains open in the framework of OILC. It is important to address this issue since unknown nonlinearity is common in practice and detrimental to good control performance. In this paper, we propose a tube feedback OILC to investigate the applicability of linear-model based control strategy on batch processes with an unknown nonlinear term. First, a state feedback control law is designed to stabilize the system. The stabilized system is then decomposed into two subsystems: repeatable and unrepeatable subsystems; Second, an invariant set of states corresponding to the unrepeatable subsystem is computed, based on which an OILC is further developed for the repeatable subsystem to improve the control performance. Meanwhile, the feedback controller steers the states within a tube around the trajectory of OILC. In this way, convergence and constraint satisfaction are ensured simultaneously. Compared with the currently existing methods, the proposed method has the following advantages: (1) generality covering both stable and unstable systems; (2) low computation complexity; and (3) rigorous stability. The simulation results on injection molding velocity control demonstrate that the proposed method has superior performance.
机译：基于优化的迭代学习控制（OILC）由于其快速收敛，良好的控制性能和处理约束的能力而被广泛应用于批处理过程。但是，在系统未知的情况下，如何保证约束满足和跟踪误差的收敛性在OILC框架中仍然是未知的。解决这个问题很重要，因为未知的非线性在实践中很常见，并且不利于良好的控制性能。在本文中，我们提出了一种管反馈OILC，以研究基于线性模型的控制策略在具有未知非线性项的批生产过程中的适用性。首先，设计状态反馈控制律以稳定系统。然后将稳定的系统分解为两个子系统：可重复和不可重复的子系统;其次，计算对应于不可重复子系统的不变状态集，基于此状态可进一步开发用于可重复子系统的OILC，以提高控制性能。同时，反馈控制器控制OILC轨迹在管内的状态。这样，可以同时确保收敛和约束满足。与现有方法相比，该方法具有以下优点：（1）涵盖了稳定系统和不稳定系统的一般性; （2）计算复杂度低; （3）严格的稳定性。注塑速度控制的仿真结果表明，该方法具有优越的性能。

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