Entropy Control in Cyber Physical Systems : How to Feed Maxwell ’ s Demon ?

The control of entropy in cyber physical system (CPS) is studied in order to better operate the physical dynamics of CPS. The controller is then regarded as the Maxwell’s demon that can decrease the system entropy. Due to the second law of thermodynamics, the controller needs external information communicated from sensors since the system entropy cannot be spontaneously decreased. For a finite state physical system in CPS, upper and lower bounds for the communication requirement have been derived. In particular, it is proved that more than H0 − H1 bits are needed for the controller to reduce the entropy from H0 to H1. The proposed bounds and algorithms are then demonstrated numerically in the context of smart grids.

[1]  Anant Sahai,et al.  The Necessity and Sufficiency of Anytime Capacity for Stabilization of a Linear System Over a Noisy Communication Link—Part I: Scalar Systems , 2006, IEEE Transactions on Information Theory.

[2]  Seth Lloyd,et al.  Information-theoretic approach to the study of control systems , 2001, physics/0104007.

[3]  Anthony J. G. Hey,et al.  Feynman Lectures on Computation , 1996 .

[4]  P. Graefe Linear stochastic systems , 1966 .

[5]  L. Brillouin,et al.  The Negentropy Principle of Information , 1953 .

[6]  A.G. Phadke,et al.  Power system frequency monitoring network (FNET) implementation , 2005, IEEE Transactions on Power Systems.

[7]  W. H. Zurek,et al.  Thermodynamic cost of computation, algorithmic complexity and the information metric , 1989, Nature.

[8]  Neri Merhav,et al.  Relations between entropy and error probability , 1994, IEEE Trans. Inf. Theory.

[9]  R. Landauer,et al.  Irreversibility and heat generation in the computing process , 1961, IBM J. Res. Dev..

[10]  Kwee-Yan Teh,et al.  An Optimal Control Approach to Minimizing Entropy Generation in an Adiabatic Internal Combustion Engine , 2006, Proceedings of the 45th IEEE Conference on Decision and Control.

[11]  Babu Narayanan,et al.  POWER SYSTEM STABILITY AND CONTROL , 2015 .

[12]  Thomas M. Cover,et al.  Elements of Information Theory , 2005 .

[13]  Shizume Heat generation required by information erasure. , 1995, Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics.

[14]  Robin J. Evans,et al.  Topological feedback entropy and Nonlinear stabilization , 2004, IEEE Transactions on Automatic Control.

[15]  H. Witsenhausen On the structure of real-time source coders , 1979, The Bell System Technical Journal.

[16]  Masahito Ueda,et al.  Nonequilibrium thermodynamics of feedback control. , 2011, Physical review. E, Statistical, nonlinear, and soft matter physics.

[17]  O. Penrose Foundations of Statistical Mechanics: A Deductive Treatment , 2005 .

[18]  E. Schrödinger What is life? : the physical aspect of the living cell , 1944 .

[19]  Philip Ball The unavoidable cost of computation revealed , 2012, Nature.

[20]  Munther A. Dahleh,et al.  Feedback Control in the Presence of Noisy Channels: “Bode-Like” Fundamental Limitations of Performance , 2008, IEEE Transactions on Automatic Control.

[21]  Sekhar Tatikonda,et al.  Stochastic linear control over a communication channel , 2004, IEEE Transactions on Automatic Control.