ran Li

Distributed cooperative tracking control for heavy haul trains with event-triggered strategy

A cooperative control with distributed event-triggered strategy for heavy haul trains is proposed to track the desired velocity with minimum in-train forces under the consideration of operation efficiency and resource utilization. Event-triggered sampling mechanism is employed in determining the time instants for state sampling and transmission among locomotives to reduce system operation and resource consumption. A theorem for the triggering condition is developed to achieve the cooperative tracking under event triggering mechanism by exploiting the M-matrix, algebraic graph theory and the Lyapunov method. It is rigorously proved that the closed-loop system is uniformly asymptotically cooperative stable under proposed strategy. Simulations demonstrate the feasibility and effectiveness of the proposed strategy.

An Event-Triggered Consensus Control with Sampled-Data Mechanism for Multi-agent Systems

Abstract In this paper, an event-triggered control strategy with sampled-data mechanism is proposed to address the consensus problem for multi-agent system. The states of each agent are obtained periodically instead of continuous detection by using sampling technology. Rather than traditional Lyapunov technique, the system stability is analyzed by introducing a disagreement vector whose convergence is proved by contraction mapping, and a necessary condition about the upper bound of sampling period is derived under which systems could achieve consensus. Simulations results are presented to show the effectiveness of proposed event-triggered control strategy with sampled data mechanism compared to the basic one.

Decentralized event-triggered cooperative control for multi-agent systems with uncertain dynamics using local estimators☆

Abstract This paper presents a decentralized event triggered cooperative control design for uncertain multi-agent systems under limited communication resources. A local estimator is employed by each agent to generate self-state estimates. The estimated states are directly used in the consensus control design, and the estimator parameters are used in the event condition design. Once an event is triggered, the local estimator is repeatedly reset to its corresponding real state values, such that it can stabilize the uncertain dynamical systems without knowing the exact system model parameters. A theorem for this triggering condition is developed to provide stable thresholds that are robust to model uncertainties and guarantee the asymptotical stability by exploiting the M-matrix, algebraic graph theory and the Lyapunov method. It is rigorously proved that the overall system will achieve the consensus and has no zeno behavior under the introduced triggering condition. Simulation results are provided to show the effectiveness of the proposed decentralized event-triggered cooperative control strategy.

An explicit predictive current-sharing control for parallel charging systems with nonlinear dynamics

In order to balance the output current of each charger related with energy storage type light rail vehicles, an explicit predictive current-sharing control is proposed in this paper. The dynamics of the parallel charging system with non-identical node is formulated as a multi-input and multi-output state space model, which is a second-order nonlinear system. As the duty ratio input of each charger is bounded and the current should evolve within the range of constraint, the current-sharing control design can be converted into a model predictive optimization problem. The cost function related with this nonlinear optimization problem includes three terms named the output current tracking error energy, the control input changing error energy and the output current cooperative interaction energy. By adopting the proposed predictive current-sharing control, the output current of each charger can track the reference current in a finite time while the duty ratio of each charger can satisfy the boundedness constraint and the current can also satisfy the peak value constraint at the same time. Simulation results verify that the proposed current-sharing approach is effective.

Periodic Event-Triggered Condition Design for the Consensus of Multiagent Systems with Communication Delays

This paper focuses on the periodic event-triggered consensus problem for multiagent systems under undirected graph. In the periodic event-triggered control, the event condition is tested only periodically to decide when to exert the control behaviors and when to broadcast the sampling data. Two sets of event-triggered strategies combining with sampled-data control are designed based on an exponential decay function and a quadratic Lyapunov function, respectively. Some useful theorems for these two periodic event-triggered strategies about the choice of period are derived to guarantee the asymptotical stability of the closed-loop multiagent systems. In addition, this paper gives a sufficient condition about the bounds of communication delay for the multiagent systems. It is rigorously proved that the overall system will achieve the consensus under the proposed strategy if the period and time delay satisfy the theorems. Finally, we extend these solutions to general linear dynamical systems. Simulation results are presented to show the effectiveness.