Publications

This paper investigates sensor scheduling for state estimation of complex networks over shared transmission channels. For a complex network of dynamical systems, referred to as nodes, a sensor network is adopted to measure and estimate the system states in a distributed way, where a sensor is used to measure a node. The estimates are transmitted from sensors to the associated nodes, in the presence of one-step time delay and subject to packet loss. Due to limited transmission capability, only a portion of sensors are allowed to send information at each time step. The goal of this paper is to seek an optimal sensor scheduling policy minimizing the overall estimation errors. Under a distributed state estimation framework, this problem is reformulated as a Markov decision process, where the one-stage reward for each node is strongly coupled. The feasibility of the problem reformulation is ensured. In addition, an easy-to-check condition is established to guarantee the existence of an optimal deterministic and stationary policy. Moreover, it is found that the optimal policies have a threshold, which can be used to reduce the computational complexity in obtaining these policies. Finally, the effectiveness of the theoretical results is illustrated by several simulation examples.

This paper investigates the observer-based event-triggered adaptive sliding mode control (SMC) problem of the semi-Markovian jumping multi-agent systems (S-MJMASs) with completely unknown and uncertain bounded transfer probabilities (TPs). As impacted by the limited bandwidth of the communication network between individual agents and the unmeasurable state information of the systems, an innovative observer based distributed event-triggered adaptive mechanism (ETAM) is proposed, in which the global information of the network is not used and the triggering threshold is dynamically regulated by the adaptive law to reduce excessive network communication. Additionally, since delays exist between the event trigger and the zero-order holder (ZOH) during data transmission in network communication systems, as well as the semi-Markovian jumping parameters, the uncertainty of systems is increased. In this paper, a novel integral sliding surface is constructed and its reachability and continuity in stochastic senses are guaranteed to withstand interferences. With the help of a stochastic semi-Markovian Lyapunov functional and numerous linear matrix inequalities (LMIs) approaches, certain adequate conditions are achieved to ensure that all agents in S-MJMASs can track the leader. Finally, certain numerical simulations are used to demonstrate the efficiency of the suggested theoretical conclusions.

No abstract is provided for this article.

In this paper, a novel coded modulation scheme named Trellis-Coded Differential Chaotic Modulation (TC-DCM) is proposed, which combines trellis codes with M-ary Differential Chaotic Shift Keying (M-DCSK). The new scheme not only reduces the multipath interference efficiently due to its inherent spreading property, but also avoids the use of Channel State Information (CSI), exact synchronization, despreading and the Rake receiver, making the corresponding receiver design simpler and more suitable for band-limited communication systems under severe multipath propagation conditions. Analytical Bit-Error-Rate (BER) bounds are derived and verified over Additive White Gaussian Noise (AWGN) channels. Both analytical performances and simulation results show that the proposed scheme with different states and different coding rates can obtain significant coding gains, compared to the corresponding uncoded schemes with the same bandwidth over AWGN channels. In addition, it is found from simulations that over multipath Rayleigh fading channels without CSI, the proposed TC-DCM system outperforms the Trellis-Coded Modulation Direct-Sequence Spread-Spectrum (TCM DS/SS) system with the same bandwidth efficiency.

This article is concerned with the stability problem for a class of Lipschitz-type nonlinear systems in networked environments, which are suffered from random and impulsive deception attacks. The attack is modeled as a randomly destabilizing impulsive sequence, whose impulsive instants and impulsive gains are both random with only the expectations available. Almost sure stability is ensured based on Doob's Martingale Convergence Theorem. Sufficient conditions are derived for the solution of the nonlinear system to be almost surely stable. An example is given to verify the effectiveness of the theoretical results. It is shown that the random attack will be able to destroy the stability, therefore, a large feedback gain may be necessary.

No abstract is provided for this article.

This paper studies the distributed consensus problem for networked general linear systems in the presence of different quantizers. The distinct features of this work are three-fold. First, both uniform and logarithmic quantization effects are analyzed. A unified control method (involving a distributed controller, a distributed event-detector, time-varying gains and constant parameters) is developed based on the relative quantized state information, which is applicable to practical scenarios where uniform and logarithmic quantization phenomena appear separately or alternately. Second, the updates of the relative information involved in the controller and the communication between adjacent agents are executed only at certain discrete event instants, significantly reducing the information update burden and data transmission load. Moreover, an internal variable, which is adjustable in accordance with the update law, is introduced in the event-detector to enhance the dynamic characteristics of the triggering performance with a lower triggering frequency. Simultaneously, the undesired Zeno behavior can be ruled out. Third, time-varying coupling gain (regulated by an adaptive rule) and triggering gain (relevant to the coupling gain) instead of constant ones are designed for the controller and the event-detector, respectively. Besides, other constant parameters can be easily tuned. These settings enable the developed control method to feature more flexibility and to be implemented in a fully distributed manner, requiring no global information. Finally, simulation examples are presented to illustrate the applicability of the theoretical results.

In this paper, a new memcapacitor model and its corresponding circuit emulator are proposed, based on which, a chaotic oscillator is designed and the system dynamic characteristics are investigated, both analytically and experimentally. Extreme multistability and coexisting attractors are observed in this complex system. The basins of attraction, multistability, bifurcations, Lyapunov exponents, and initial-condition-triggered similar bifurcation are analyzed. Finally, the memcapacitor-based chaotic oscillator is realized via circuit implementation with experimental results presented.

Recently, we looked more closely into the Rabinovich–Fabrikant system, after a decade of study [Danca & Chen, 2004], discovering some new characteristics such as cycling chaos, transient chaos, chaotic hidden attractors and a new kind of saddle-like attractor. In addition to extensive and accurate numerical analysis, on the assumptive existence of heteroclinic orbits, we provide a few of their approximations.