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Fully Characterization of Strictly Positive Real Transfer Function Matrices
Mojtaba Hakimi Moghaddam,Hamid Khaloozadeh 제어로봇시스템학회 2012 제어로봇시스템학회 국제학술대회 논문집 Vol.2012 No.10
Several necessary and sufficient conditions for characterization of strict positive realness property of transfer function matrices have been derived in the literature. However, some of them are inconsistent with definition of strict positive realness and the others have been restricted to proper transfer function matrices. Besides, there is a necessary condition in the previous correct statements which is difficult to check. In this paper, using Markov parameters of linear time invariant multivariable systems, we will remove the aforementioned deficiencies. On the other hand, we will prove new equivalent conditions to characterize strict positive realness such that not only it can be easily checked but also it can be used when the transfer function matrix is improper.
Revision on the Frequency Domain Conditions for Strict Positive Realness
Mojtaba Hakimi Moghaddam,Hamid Khaloozadeh 대한전기학회 2007 International Journal of Control, Automation, and Vol.5 No.1
In this paper, the necessary and sufficient conditions for strict positive realness of the rational transfer functions directly from basic definitions in the frequency domain are studied. A new frequency domain approach is used to check if a rational transfer function is a strictly positive real or not. This approach is based on the Taylor expansion and the Maximum Modulus Principle which are the fundamental tools in the complex functions analysis. Four related common statements in the strict positive realness literature which is appeared in the control theory are discussed. The drawback of these common statements is analyzed through some counter examples. Moreover a new necessary condition for strict positive realness is obtained from high frequency behavior of the Nyquist diagram of the transfer function. Finally a more simplified and completed conditions for strict positive realness of single-input single-output linear time-invariant systems are presented based on the complex functions analysis approach.