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This article is concerned with the differentially private consensus control (DPCC) problem for linear discrete-time multiagent systems (MASs) under dynamic encoding–decoding schemes (EDSs), where the agents' initial states are the sensitive data to be protected from potential eavesdroppers. The EDS is deployed on each agent to compress the data before transmission so as to better utilize the limited network bandwidth. Differential privacy, as a performance metric, is introduced to evaluate the level of privacy, and an EDS-based DPCC scheme is proposed to ensure the ultimate mean-square consensus with preserved differential privacy. A set of criteria is first established for the EDS-embedded DPCC problem in terms of the performance of consensus, the size of transmitted data, and the level of privacy. Subsequently, the codesign issue is discussed for the EDS, the differentially private mechanism, and the consensus controller. Finally, the effectiveness of the developed algorithm is illustrated via numerical simulations.

In this article, we investigate the distributed cooperative optimization problem for heterogeneous uncertain high-order nonlinear multi-agent systems with an intermittent communication network, where each agent can only share information with its neighbors in some disjoint time intervals. To address this problem, the design process consists of constructing a distributed optimization algorithm and designing a decentralized tracking controller. To design a distributed optimization algorithm, virtual signals are constructed for all agents to minimize the cost function under the influence of the intermittent communication network. Based on the optimal virtual signals, local references with the existence of high-order derivatives are constructed by using the Hermite interpolation method. Then, a decentralized adaptive controller is designed for each local agent by following the recursive backstepping design procedure. It is theoretically shown that the distributed cooperative optimization problem is solved with the proposed method. Finally, a simulation example is introduced to verify the efficiency of the proposed method.

This technical note deals with the design of mode-dependent H\infty filters for a class of discrete-time switched systems with nonlinearities. In this class of systems, when the system mode changes, the filter designed for the specific subsystem also switches accordingly. The main contribution is on the use of the information of the sojourn probability—the probability of the switched system staying in each subsystem—to build new kind of switched system model when this additional information is available. Sojourn probabilities are easier to obtain than the transition probabilities commonly used in Markovian jump systems. Applying the Lyapunov functional method, the bounded real lemma (BRL) for the resulting filtering error system is obtained in Theorem 1. The filter parameters are designed in Theorem 2 by solving a set of linear matrix inequalities. Finally, two illustrative examples are given to demonstrate the effectiveness and potential of the proposed approach. [ABSTRACT FROM AUTHOR]

In a recent paper refid="ref1"/, a decentralized delay-dependent controller was proposed for a class of interconnected continuous-systems with convex-bounded parametric uncertainties and time-varying delays. Unfortunately, there exist some fundamental mistakes which render the results of refid="ref1"/ questionable. [ABSTRACT FROM AUTHOR]