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On reproducing existing controllers as Model Predictive controllers

机译:在将现有控制器复制为模型预测控制器时

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The ability to take constraints explicitly into account in the optimisation problem formulation has made Model Predictive Control (MPC) a popular control strategy. However, finding the weights in the optimisation criterion is often non-trivial and requires a fair bit of trial-and-error. Conventional controllers such as PID, on the other hand, are relatively easy to tune, and they often achieve satisfactory performance when there are no constraints. In this paper, we present three approaches for designing an MPC such that it reproduces the conventional controller when there are no constraints. The first approach is from the existing literature where a full order observer is used in the reverse engineering. The second and third approach used a reduced order observer and state augmentation respectively are proposed. The obtained controller can also serve as an initial MPC which can be further fine tuned, and constraints can later be added to evaluate any potential benefit of using MPC compared to the original controller.
机译:在优化问题表述中明确考虑约束的能力使模型预测控制(MPC)成为一种流行的控制策略。但是,在优化标准中找到权重通常并非易事,并且需要反复试验。另一方面,传统的控制器(例如PID)相对容易调整,并且在没有限制的情况下通常可以达到令人满意的性能。在本文中,我们提出了三种设计MPC的方法,以便在没有约束的情况下可以重现常规控制器。第一种方法来自现有文献,其中在逆向工程中使用了全阶观测器。提出了分别使用降阶观测器和状态增强的第二种方法和第三种方法。所获得的控制器还可以用作初始MPC,可以对其进行进一步的微调,并且可以在以后添加约束以评估与原始控制器相比使用MPC的任何潜在好处。

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