Cloud-based Distributed Consensus Control For Networked Multi-Agent Systems

With the rapid advancement of computer and communication technologies,the integration of multi-agent systems with cutting-edge Internet technologies such as 5G Io T and cloud computing has resulted in the emergence of a new cloud-based networked multi-agent system paradigm.This paradigm offers numerous benefits such as enhanced data processing capabilities,reduced system deployment costs,and improved system scalability.However,the introduction of cloud networking has posed several challenges to networked multi-agent systems,including limitations imposed by communication links(uploading and downloading data)and the variable nature of communication topology.These challenges have created new difficulties in achieving distributed consensus control in networked multi-agent systems.Therefore,developing effective distributed consensus control strategies within cloud-based frameworks is a pressing issue that requires urgent attention in this field.This thesis addresses the issue of distributed consensus control for cloud-based multi-agent systems,with a particular focus on the impact of multiple heterogeneous networks,such as network-induced delays,topology switching,communication quantization,and unobservable state information.Therefore,a series of novel theories and methods for distributed collaborative control is proposed to tackle these challenges.The main contributions of this work can be summarized as follows:(1)To address the issue of network-induced heterogeneous time-varying communication delays,a cloud-based networked distributed consensus control method for multi-agent systems is proposed.Firstly,a networked multi-agent system model under the cloud framework is established,with the introduction of an asynchronous delay handling mechanism under fixed topology.Based on this model,sufficient conditions for ensuring the stability of the closed-loop system are obtained using Lyapunov analysis methods,and a cloud-based controller design method is proposed.Secondly,under topology switching,the switching system analysis methods are used to obtain sufficient conditions for ensuring the exponential stability of the closed-loop system.The average residence time of topology switching needs to satisfy corresponding conditions,and the system parameters need to satisfy a set of linear matrix inequality(LMI)conditions.Under these conditions,a cloud-based controller gain matrix design method for the switching topology is obtained.Finally,the effectiveness of the proposed methods is verified through numerical simulations.(2)To address the issue of unobservable system states,a cloud-based distributed consensus control method for networked multi-agent systems is proposed.Under the cloud framework,both a Luenberger observer and a distributed cloud observer are designed,and it is theoretically proved that these two observers can effectively estimate the system state.Then,a cloud-based observer-based distributed consensus control strategy is developed based on this.Sufficient conditions for ensuring system consensus are derived using Lyapunov analysis methods and linear matrix inequality methods,and the design methods for both the observer gain matrix and the cloud controller gain matrix are obtained.The effectiveness of the proposed methods is verified through numerical simulations,and the two design methods are compared.(3)To address the issue of communication delays and state quantization,a cloud-based networked distributed consensus control method for multi-agent systems is proposed.Firstly,under the influence of heterogeneous communication delays and quantization,a cloud-based distributed consensus protocol is designed.Secondly,using Lyapunov analysis methods,the stability of the closed-loop system is analyzed,and sufficient conditions for the stability of the closed-loop error system are derived.This condition characterizes the impact of heterogeneous communication delays and quantization on the system.Under this stability condition,the cloud controller gain design method is obtained.Finally,the effectiveness of the proposed method is verified through numerical simulations.