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Song Fang

Publications and source records attributed to Song Fang.

23 records · Page 2Linked to original sources

Two-Way Coding in Control Systems Under Injection Attacks: From Attack Detection to Attack Correction

In this paper, we introduce the method of two-way coding, a concept originating in communication theory characterizing coding schemes for two-way channels, into (networked) feedback control systems under injection attacks. We first show that the presence of two-way coding can distort the perspective of the attacker on the control system. In general, the distorted viewpoint on the attacker side as a consequence of two-way coding will facilitate detecting the attacks, or restricting what the attacker can do, or even correcting the attack effect. In the particular case of zero-dynamics attacks, if the attacks are to be designed according to the original plant, then they will be easily detected; while if the attacks are designed with respect to the equivalent plant as viewed by the attacker, then under the additional assumption that the plant is stabilizable by static output feedback, the attack effect may be corrected in steady state.

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A Frequency-Domain Characterization of Optimal Error Covariance for the Kalman-Bucy Filter

In this paper, we discover that the trace of the division of the optimal output estimation error covariance over the noise covariance attained by the Kalman-Bucy filter can be explicitly expressed in terms of the plant dynamics and noise statistics in a frequency-domain integral characterization. Towards this end, we examine the algebraic Riccati equation associated with Kalman-Bucy filtering using analytic function theory and relate it to the Bode integral. Our approach features an alternative, frequency-domain framework for analyzing algebraic Riccati equations and reduces to various existing related results.

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Three laws of feedback systems: entropy rate never decreases, generalized Bode integral, absolute lower bound in variance minimization, Gaussianity-whiteness measure (joint Shannon-Wiener entropy), Gaussianing-whitening control, and beyond

This paper aims at obtaining universal laws and absolute lower bounds of feedback systems using information theory. The feedback system setup is that with causal plants and causal controllers. Three laws (entropy rate never decreases, generalized Bode integral, and absolute lower bound in variance minimization) are obtained, which are in entropy domain, frequency domain, and time domain, respectively. Those laws characterize the fundamental limitations of such systems imposed by the feedback mechanism. Two new notions, negentropy rate and Gaussianity-whiteness measure (joint Shannon-Wiener entropy), are proposed to facilitate the analysis. Topics such as whiteness-Gaussianity-variance decomposition, Gaussianing-whitening control (the maximum Gaussianity-whiteness measure principle), whitening control (spectrum/spectral flattening control), generalized Bode plot, and so on are also discussed. The special case of linear time-invariant feedback systems is considered in the end.

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Limitations of state estimation: absolute lower bound of minimum variance estimation/filtering, Gaussianity-whiteness measure (joint Shannon-Wiener entropy), and Gaussianing-whitening filter (maximum Gaussianity-whiteness measure principle)

This paper aims at obtaining performance limitations of state estimation in terms of variance minimization (minimum variance estimation and filtering) using information theory. Two new notions, negentropy rate and Gaussianity-whiteness measure (joint Shannon-Wiener entropy), are proposed to facilitate the analysis. Topics such as Gaussianing-whitening filter (the maximum Gaussianity-whiteness measure principle) are also discussed.

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Three Laws of Multivariable Feedback Systems, Extended Spectral Flatness (Extended Wiener Entropy), 'Uncertainty Principles' in Variance Minimization, and Performance Limitations in Minimum Variance Estimation/Filtering

In this paper, three laws are obtained for multiple-input multiple-output feedback systems, which are in entropy domain, frequency domain, and time domain, respectively. The system setup is that with causal plants and causal controllers. Those laws characterize the performance limitations of such systems imposed by the feedback mechanism. Some new notions are proposed to facilitate the analysis: negentropy rate, extended spectral flatness (extended Wiener entropy), Gaussianity-whiteness measure (joint Shannon-Wiener entropy), etc. Two approaches are adopted: the integrated approach and the divided approach. And 'uncertainty principles' are found in minimum variance control. Besides, performance limitations in minimum variance estimation and filtering are obtained. In the end, the special case of linear time-invariant feedback systems is discussed.

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