This paper mainly considers the optimal measurement feedback control and stabilization for networked control systems (NCSs) with packet losses. The problems are involved with fundamental difficulties of separation principle and optimal estimation (conditional expectation) for multiplicative noise stochastic systems. First, the optimal estimator (conditional expectation) for NCSs with packet losses is derived and the optimal measurement feedback controller is obtained by using the maximum principle. The sufficient and necessary solvability condition of finite horizon measurement feedback control problem is first presented. Moreover, the asymptotic stability of the optimal estimator is studied. Finally, for the infinite horizon case, based on the introduction of a new Lyapunov function, which is defined with the optimal cost function, it is shown that the system is stabilizable in the mean square sense if and only if an algebraic Riccati equation admits a unique positive definite solution.

This paper investigates the stabilization and control problems for linear continuous-time mean-field systems (MFS). Under standard assumptions, necessary and sufficient conditions to stabilize the mean-field systems in the mean square sense are explored for the first time. It is shown that, under the assumption of exact detectability (exact observability), the mean-field system is stabilizable if and only if a coupled algebraic Riccati equation (ARE) admits a unique positive semi-definite solution (positive definite solution), which coincides with the classical stabilization results for standard deterministic systems and stochastic systems.One of the key techniques in the paper is the obtained solution to the forward and backward stochastic differential equation (FBSDE) associated with the maximum principle for an optimal control problem. Actually, with the analytical FBSDE solution, a necessary and sufficient solvability condition of the optimal control, under mild conditions, is derived. Accordingly, the stabilization condition is presented by defining an Lyaponuv functional via the solution to the FBSDE and the optimal cost function.It is worth of pointing out that the presented results are different from the previous works [1] for stabilization and also different from the works [2], [3], [4] on optimal control.

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This paper studies the bipartite consensus problem of multi-agent systems with intermittent interaction under signed directed graph. It is assumed that each agent receives its states information relative to its neighbors at the sampling time and updates the control input by using the states information, and the period of each agent updates control input is equal to a positive integer multiple of its sampling period. Cooperation and competition between agents are represented by positive and negative weights of edge respectively in the signed topology. The sufficient condition for achieving bipartite consensus is obtained by Shure-Cohen stability criterion, which reveals the relationship among sampling period, update control input period and controller gain of system. Finally, simulation tests show the bipartite consensus performances of agents under intermittent protocol and signed topology.INDEX TERMS Multi-agent systems, intermittent interaction, bipartite consensus, positive and negative weights, Shure-Cohen stability criterion.

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