基于改进的等价动态线性化模型的自校正控制
Self-Tuning Control based on Modified Equivalent-Dynamic-Linearization Model
AI总结：
提出基于引入时延和干扰的改进EDLM的自校正控制器，分四种情况应用，通过分析闭环极点实现设计与稳定性分析，并解决MFAC中参数λ的定量选择问题。
摘要：
当前的无模型自适应控制（MFAC）方法是基于等价动态线性化模型（EDLM）设计的，忽略了实际中的时间延迟和干扰。通过与当前关于MFAC的工作进行比较：i）提出了一类基于通过引入时间延迟和干扰而改进的新EDLM的自校正控制器，以便更客观地反映真实系统。此后，我们将所提出的控制器分为四种情况，以便于应用；ii）通过分析闭环极点的功能，可以实现系统的控制器设计和稳定性分析。此外，通过分析系统的零极点配置和静态误差，首次完成了当前MFAC中如何按数量选择参数λ的问题，而这在以前的收缩映射方法中几乎无法实现；iii）对所提出方法的研究集中于线性模型，以便于掌握其工作行为；最后，使用两个例子证明了所提出方法的有效性，并指出了当前MFAC理论中的不足之处。
英文摘要：
The current model-free adaptive control (MFAC) method is designed on the basis of the equivalent-dynamic-linearization model (EDLM) with neglect of the time delay and disturbance in practical. By comparisons with the current works about MFAC, i) a class of self-tuning controller is proposed based a new EDLM modified by the introduction of time delay and disturbance so as to reflect the real system more objectively. Thereafter, we classify the proposed controller into four cases to enable easier applications; ii) the controller design and stability analysis of system are achievable by analyzing the function of the closed-loop poles. In addition, the issue of how to choose the parameter λin current MFAC by quantity is firstly finished by the analysis of zeros-poles placement and static error of system, whereas this can hardly be realized by the previous contraction mapping method; iii) the study on the proposed method is focused on linear model for easily mastering its working behavior; At last, two examples are used to demonstrate the effectiveness of the proposed method and to point out the deficiencies in the current MFAC theory.
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