arXiv subjects

Jilie Zhang

Publications and source records attributed to Jilie Zhang.

5 recordsLinked to original sources

arXiv2026

A Fresh Look on Network Synchronization

This paper gives a fresh look at network synchronization. Here we no longer analyze it from the view of mathematics, such as graph theory, while we probe into one from control theory. First, we analyze the synchronization region using the inner coupling matrix, giving up the routine method of studying the network structure. The motivation comes from the inner coupling matrix that is not subject to any restrictions like network structure, such as distance and communication strength among nodes. It can be configured at will to meet the synchronization performance if only the states of the local dynamic are measurable or observable and the communication topology is connected. Thus, it is very useful for future practical engineering design. In addition, we have an amazing finding that the network synchronization and multi-agent system consensus problems are equivalence essentially. Afterwards a unified viewpoint, that is, the essence of multi-agent consensus control is the same as that of network synchronization, is present. Here, the equivalence relation is clearly proven and proposed. Therefore, we can synthesize the inner coupling matrix for network systems or the controller gain for multi-agent systems for each other. Finally, we also present a kind of method for addressing the nonlinear complex network system. Then the effectiveness of method is verified by taking the network of the three-oscillator universal probe as an example.

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arXiv2022

Platooning of Connected Vehicles with Directed Graph: $H_\infty$ Robustness Analysis and Synthesis

This paper revisits the robustness analysis and distributed ${ H}_\infty$ controller design for the platooning of connected vehicles. Recently, the relevant result subjected to the undirected topology has been studied, in the light of the symmetry of Laplace matrix. It is well known that the same problem is more challenging for the \emph{directed} topology, since the Laplace matrix ceases to be symmetric. In this paper, the problem is solved by introducing more weighting parameters and setting suitable values for them. Then we show that the introduced weighting parameters lead to a positive effect on robustness, and solve the problem of feedback high gain. Finally, two numerical simulations and a practical simulation based on Next Generation Simulation (NGSIM) dataset are used to illustrate the effectiveness of our method.

math.OC↗

arXiv2021

Coupling effect and pole assignment in trajectory regulation of multi-agent systems

This paper revisits a well studied leader-following consensus problem of linear multi-agent systems, while aiming at follower nodes' transient performance. Conventionally, when not all follower nodes have access to the leader's state information, distributed observers are designed to estimate the leader's state, and the observers are coupled via communication network. Then each follower node only needs to track its observer's state independently, without interacting with its neighbors. This paper deliberately introduces certain coupling effect among follower nodes, such that the follower nodes tend to converge to each other cooperatively on the way they converge to the leader. Moreover, by suitably designing the control law, the poles of follower nodes can be assigned as desired, and thus transient tracking performance can also be adjusted.

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arXiv2019

Data-Based Optimal Control of Multi-Agent Systems: A Reinforcement Learning Design Approach

This paper studies optimal consensus tracking problem of heterogeneous linear multi-agent systems. By introducing tracking error dynamics, the optimal tracking problem is reformulated as finding a Nash-equilibrium solution of a multi-player games, which can be done by solving associated coupled Hamilton-Jacobi (HJ) equations. A data-based error estimator is designed to obtain the data-based control for the multi-agent systems. Using the quadratic functional to approximate the every agent's value function, we can obtain the optimal cooperative control by input-output (I/O) $Q$-learning algorithm with value iteration technique in the least-square sense. The control law solves the optimal consensus problem for multi-agent systems with measured input-output information, and does not rely on the model of multi-agent systems. A numerical example is provided to illustrate the effectiveness of the proposed algorithm.

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arXiv2017

Leader-Based Optimal Coordination Control for the Consensus Problem of Multiagent Differential Games via Fuzzy Adaptive Dynamic Programming

In this paper, a new on-line scheme is presented to design the optimal coordination control for the consensus problem of multi-agent differential games by fuzzy adaptive dynamic programming (FADP), which brings together game theory, generalized fuzzy hyperbolic model (GFHM) and adaptive dynamic programming. In general, the optimal coordination control for multi-agent differential games is the solution of the coupled Hamilton-Jacobi (HJ) equations. Here, for the first time, GFHMs are used to approximate the solution (value functions) of the coupled HJ equations, based on policy iteration (PI) algorithm. Namely, for each agent, GFHM is used to capture the mapping between the local consensus error and local value function. Since our scheme uses the single-network rchitecture for each agent (which eliminates the action network model compared with dual-network architecture), it is a more reasonable architecture for multi-agent systems. Furthermore, the approximation solution is utilized to obtain the optimal coordination controls. Finally, we give the stability analysis for our scheme, and prove the weight estimation error and the local consensus error are uniformly ultimately bounded. Further, the control node trajectory is proven to be cooperative uniformly ultimately bounded.

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