In this paper, we investigate the distributed optimization problem for heterogeneous linear multi-agent systems with unknown disturbances. To solve this problem, we propose a distributed controller design framework, w...
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In this paper, we investigate the distributed optimization problem for heterogeneous linear multi-agent systems with unknown disturbances. To solve this problem, we propose a distributed controller design framework, which reduces the controller design for heterogeneous linear multi-agent systems to the stabilizer design for first-order multi-agent systems. By this framework, we propose two kinds of dynamic controllers under the strong convexity of the objective function and the restricted secant inequality condition, respectively. Based on the optimal condition and singular perturbation analysis technique, we prove that the system converges to the optimal state if the disturbances tend to be constant or vary slowly. To further optimize the performance criterion under system stability and input constraint, we provide an optimal gain tuning algorithm such that the system stability, optimality and feasibility are simultaneously achieved. Numerical examples are provided to illustrate the effectiveness of the theoretical results.
It is one of the most essential processes in the industrial cyber-physical system (ICPS) that multiple edge computing nodes (ECNs) collect field sensor information and cooperate for sensing and control. The exchange o...
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It is one of the most essential processes in the industrial cyber-physical system (ICPS) that multiple edge computing nodes (ECNs) collect field sensor information and cooperate for sensing and control. The exchange of sensing information on the edge side is critical for these ECNs that serve as multiple edge estimators and one edge controller. However, the limited transmission resources and the diverse performance demands of ECNs for sensing and control make it challenging to design the edge network topology delicately. For this issue, a novel dynamic observability (DO) condition is proposed to balance sensing-control performance and transmission cost under various demand settings. Based on the quantitative analysis of the relationship between overall transmission cost and each ECN's effective observability, DO gives the criterion for desirable network topologies with spatio-temporal dynamics. Then for the given performance demands, a dynamic observability guaranteed method (DOGM) is proposed to determine the network topology by triggering proper sensing links. In this way, the set of triggered sensing links may vary in a dynamic manner to satisfy the DO condition, and the overall performance of sensing and control is theoretically guaranteed. Finally, the comprehensive advantages of DOGM are demonstrated by the simulation study in the hot rolling laminar cooling process.
Unlike traditional Internet of Things (IoT), Vehicular Ad Hoc networks (VANETs) operate in open environments and transmit information through wireless communication technologies, making VANETs more susceptible to vari...
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