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MODEL PREDICTIVE CONTROL OF LINEAR SYSTEMS SUBJECT TO ACTUATOR DEGRADATION

机译:执行机构退化对线性系统的模型预测控制

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The degradation of physical components in engineering systems is generally unavoidable, in view of factors such as wear due to usage, aging of the materials and hostile environmental conditions. In particular, the degradation of actuators in a closed-loop control system can lead to poor performance and, in extreme cases, loss of controllability. In this context, it may be interesting to design controllers that can exploit the available knowledge on the degradation dynamics to maintain adequate performance and extend the useful life of the actuators. The present work is concerned with cases in which the degradation rate depends on the exerted control effort. It is shown that the loss of actuator effectiveness can be taken into account by using an augmented design model of the bilinear type. A model predictive controller (MPC) can then be implemented by using suitable optimization algorithms that can handle quadratic costs subject to bilinear constraints. A simulated example is presented to illustrate some of the salient advantages of the proposed method. The results obtained by using the proposed MPC are compared to those of a standard MPC formulation, as well as an MPC with model parameters updated at each sample time according to the degradation state of the actuator.
机译:考虑到诸如由于使用引起的磨损,材料的老化以及恶劣的环境条件等因素,工程系统中物理组件的退化通常是不可避免的。特别是,闭环控制系统中执行器的性能下降会导致性能下降,在极端情况下会导致可控性下降。在这种情况下,设计控制器可能会很有趣,这些控制器可以利用有关降级动力学的可用知识来维持足够的性能并延长执行器的使用寿命。当前的工作涉及退化率取决于所施加的控制努力的情况。结果表明,可以通过使用双线性类型的扩展设计模型来考虑执行器效率的损失。然后,可以使用适合的优化算法来实现模型预测控制器(MPC),该算法可以处理受双线性约束的二次成本。给出了一个仿真示例,以说明该方法的一些显着优势。将使用建议的MPC所得的结果与标准MPC配方的结果以及根据致动器的退化状态在每个采样时间更新模型参数的MPC进行比较。

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