State Estimation for Complex Networks with Randomly Varying Topologies and DoS Attacks Under Binary Encoding Scheme

In this paper, based on using binary encoding scheme, the state estimation issue is tackled for complex networks suffering from nonlinearities, stochastic inner coupling, randomly varying topologies and randomly occurring denial-of-service (DoS) attack. The binary encoding scheme is selected to manage the network communication between the sensor to the estimator. The measurement output is quantized to be encoded into a binary bit string (BBS), the random binary bit flipping is taken into account during the network transmission process caused by channel noise, and the received BBS is decoded by the estimator. The Gaussian-distributed random variables are adopted to reflect the possible stochastic variation of inner coupling strength inside each network node in practice. Three sets of Bernoulli-distributed random variables are put into use to depict the random occurrence of varying topology structures, binary bit flipping and DoS attacks during the network transmission, respectively. Based on the statistical properties analysis of the decoded signal, a equivalent stochastic noise is formulated to reflect the influence of random bit errors. This paper targets the state estimator design in such a situation so that the estimation error system achieves the exponential ultimate boundedness in mean square. Through stochastic analysis and inequality operation, a sufficient condition is brought forward for the presence of the satisfactory exponentially ultimately bounded estimator. The estimator gains are yielded readily through solving the matrix inequalities. Ultimately, a numerical simulation example is carried on to validate the usefulness of the estimation method put forth in this paper.