论文标题
简化双尤拉方法的闭环标识
On simplification of Dual-Youla approach for closed-loop identification
论文作者
论文摘要
众所周知，闭环识别的双YouLa方法具有几个实际上重要的优点。也就是说，它提供了准确的植物模型，无论噪声模型如何，并且可以固有地使用副本分解来处理不稳定的植物。另外，该方法在经验上是强大的，而对于控制器知识的不确定性。但是，使用副分解可能会导致对工业应用的障碍。本文展示了如何得出该方法的简化版本，该方法可以在没有副本分解的情况下识别植物本身，同时享受双Youla方法的所有优点。事实证明，这种简化的版本与最近由作者提出的稳定预测错误方法相同。给出详细的仿真结果以证明上述优点。
The dual Youla method for closed loop identification is known to have several practically important merits. Namely, it provides an accurate plant model irrespective of noise models, and fits inherently to handle unstable plants by using coprime factorization. In addition, the method is empirically robust against the uncertainty of the controller knowledge. However, use of coprime factorization may cause a big barrier against industrial applications. This paper shows how to derive a simplified version of the method which identifies the plant itself without coprime factorization, while enjoying all the merits of the dual Youla method. This simplified version turns out to be identical to the stabilized prediction error method which was proposed by the authors recently. Detailed simulation results are given to demonstrate the above merits.
