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This paper is intended to solve the fully distributed secure bipartite consensus problem of nonlinear multi-agent systems (MASs) with quantized information under Denial-of-Service (DoS) attacks. The attacks, which constrained on attack frequency and duration are studied. Firstly, we propose a novel secure output feedback control protocol integrated of the logarithmic quantizer and relative output measurements of neighboring agents, which can realize secure control under DoS attacks by choosing the design parameters correctly. Secondly, an adaptive control protocol that includes dynamic coupling strengths into the control law and the state observer function is developed. Contrast to the single adaptive control strategy, two adaptive couplings constructed in sensor-to-observer, and controller-to-actuator channels, respectively, which can alleviate the burden of the limited bandwidth and energy consumption more effectively. Furthermore, this control strategy with dynamic coupling gains is fully distributed, under which agents are not required to know a priori knowledge of any global information and the quantizer only needs to quantize the output state error information of agents. Then, theoretical guarantees on the effectiveness of the proposed controllers in steering the system to a secure bipartite (bounded) consensus under quantized output measurements and intermittent DoS attacks are derived. Finally, the numerical simulation inspired by a real-world physical network system is developed to verify the usefulness of the presented controllers.

This paper considers the leader-following bipartite consensus for a class of nonlinear multi-agent systems (MASs) subject to exogenous disturbances under directed fixed and switching topologies, respectively. Firstly, two new output feedback control protocols involving signs of link weights are introduced based on relative output measurements of neighboring agents. In order to estimate the disturbances produced by an exogenous system, a disturbance observer-based approach is developed. Then, sufficient conditions for leader-following bipartite consensus with directed fixed topologies are derived. Furthermore, by assuming that each switching topology contains a directed spanning tree, it is proved that the leader-following bipartite consensus can be realized with the designed output feedback control protocol if the dwell time is larger than a non-negative threshold. Finally, numerical simulations inspired by a real-world DC motors are provided to illustrate the effectiveness of the proposed controllers.

The kappa statistic is a widely used as a measure for quantifying agreement between two nominal classifications. The statistic has been extended to the case of two normalized fuzzy classifications. In this paper we define category kappas for quantifying agreement on a particular category of two normalized fuzzy classifications. The overall fuzzy kappa is a weighted average of the proposed category kappas. Since the value of the overall kappa lies between the minimum and maximum values of the category kappas, the overall kappa, in a way, summarizes the agreement reflected in the category kappas. The overall kappa meaningfully reflects the degree of agreement between the fuzzy classifications if the category kappas are approximately equal. If this is not the case, it is more informative to report the category kappas. HighlightsFuzzy kappas for quantifying agreement on a particular category are defined.The fuzzy kappa of Dou et al. is a weighted average of the proposed category kappas.With two categories the category kappas and overall kappa coincide.Adding all other membership functions presents an alternative definition.