Distributed Group Coordination of Multiagent Systems in Cloud Computing Systems Using a Model-Free Adaptive Predictive Control Strategy
ABSTARCT :
This article studies the group coordinated control problem for distributed nonlinear multiagent systems (MASs) with unknown dynamics. Cloud computing systems are employed to divide agents into groups and establish networked distributed multigroup-agent systems (ND-MGASs). To achieve the coordination of all agents and actively compensate for communication network delays, a novel networked model-free adaptive predictive control (NMFAPC) strategy combining networked predictive control theory with model-free adaptive control method is proposed. In the NMFAPC strategy, each nonlinear agent is described as a time-varying data model, which only relies on the system measurement data for adaptive learning. To analyze the system performance, a simultaneous analysis method for stability and consensus of ND-MGASs is presented. Finally, the effectiveness and practicability of the proposed NMFAPC strategy are verified by numerical simulations and experimental examples. The achievement also provides a solution for the coordination of large-scale nonlinear MASs.
EXISTING SYSTEM :
? In particular, we study the rendezvous and the formation control problems over dynamic interaction graphs, and by adding appropriate weights to the edges in the graphs, we guarantee that the graphs stay connected.
? The remaining agents then track the leader, while obeying some coordination rules to keep the formation.
? In contrast, the other approach to formation control is the leaderless approach.
? In this paper, we will focus on providing solutions to the coordination problem that preserve connectedness in the presence of limited sensing and communication ranges. In particular, the rendezvous and formation control problems are investigated.
DISADVANTAGE :
? The operation of MAS relies on the communication links, which inevitably causes delay-introduced stability problems.
? Moreover, combining MAS with the graph theory and dynamic consensus control to solve the problems of the hierarchical coordination control in MG and MGC is a promising approach.
? Due to the access of the DG system, the study of the switching characteristics for the communication topologies in MAS is a critical problem to be solved.
? The primary control loop mainly adopts droop control, in order to regulate the local power, voltage, and current, and avoid the voltage and frequency instability, and solve the problems of power sharing among the multiple DGs.
PROPOSED SYSTEM :
• In and, a dynamic extension of the static graph theory is proposed as a framework to address network problems with time-varying topologies.
• We will show some simulation results that illustrate the proposed coordination control strategies for different problems.
• The third simulation highlights the proposed formation control strategy, and is implemented based on the formation control law in.
• Analogous to the treatment of the rendezvous problem, we first propose a solution to the formation control problem, and then show that this solution does, in fact, preserve connectedness as well as guarantee convergence in the sense of F1 and F2 above.
ADVANTAGE :
? The performance of high intelligence, strong scalability, high redundancy and reliability adjustment of the voltage, frequency, and power in MG cannot be realized by classical hierarchical control strategy
? Distributed multiagent control method has been widely used to establish optimal model to enhance reliability and energy management, optimization, and improve the performance of ancillary services.
? Compared with the centralized control, these strategies have higher ability to tolerate the communication errors, and better plug-and-play performance, and can be easily extended to more DG units, which makes the system more scalable.
? There are three kinds of fixed communication delays, one is the sending and processing delay, which depends on software and hardware performance of source equipment.
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