Globally fuzzy leader-follower consensus of mixed-order nonlinear multi-agent systems with partially unknown direction control

Finite-Time Neuroadaptive Cooperative Control for Nonlinear Multiagent Systems Under Nonaffine Faults and Partially Unknown Control Directions

This article investigates the cooperative control of complex nonlinear multiagent systems (CNMASs), in which the agents suffer from nonaffine faults and the control directions of some agents are unknown. A finite-time adaptive control scheme is presented for the CNMASs. A finite-time command filter is designed to solve the "explosion of complexity" issues, overcome chattering issues, and relax the limitations of the filter input. The impact of filter errors is alleviated by an improved error compensation mechanism. Based on piecewise Nussbaum functions, the partially unknown control direction is addressed. The proposed finite-time cooperative control strategy on the basis of local information can ensure that all signals in the closed-loop system are finite-time bounded, and the absolute value of the cooperative control errors can converge to a given upper bound in a finite time. The rapidity and robustness of the proposed method are verified by two comparative simulation examples. A real multirobot cooperative control experiment is used to verify the effectiveness of the presented method.

Consensus Control of Mixed-Order Nonlinear Multiagent Systems: Framework and Case Study

This article investigates the consensus problem of mixed-order nonlinear multiagent systems (MASs). First, a new research framework of consensus control for MASs with hybrid-order dynamics is established. In this framework, the order of low-order dynamic subsystems is increased to higher-order dynamic subsystems by means of increasing order technology, so that the mixed-order MASs can be changed into the same-order MASs. Thus, the distributed controller of hybrid-order MASs can be designed by using the consensus control method of the same-order MASs. Second, through a case study of a stochastic mixed first- and second-order nonlinear MASs, this article further expounds the design idea of the framework structure and gives the concrete design form of the distributed controller and the stability analysis of the closed-loop system. Finally, simulations are given to verify the effectiveness of the distributed control protocol in this case.

Globally fuzzy consensus of hybrid-order stochastic nonlinear multi-agent systems

This paper studies the globally fuzzy consensus of stochastic nonlinear multi-agent systems (MAS) with hybrid-order dynamics. The followers are modeled as hybrid first- and second-order systems. The leader is presented as second-order system and can transmit his own states to the first- and second-order followers. In view of the local characteristics of communication among agents, the followers can be decomposed into two categories: one is the set of followers who can communicate with the leader, and the other is the set of followers who cannot communicate with the leader. Using the design method of fuzzy feed-forward compensator and Lyapunov stability theory, a new hybrid fuzzy consensus controller is designed for the two kinds of follower sets. Compared with most stochastic MAS, the proposed algorithm not only solves the consensus of hybrid-order stochastic MAS based on fuzzy approximator, but also obtains the results of globally uniform ultimate bounded (GUUD). In the end, the simulation results further verify the validity of the proposed algorithm.

State-based event-triggered consensus strategy for Takagi-Sugeno fuzzy fractional-order multiagent systems with switching topologies

This article addresses the event-triggered consensus problem for Takagi-Sugeno fuzzy fractional-order multiagent systems with switching topologies. First, to effectively avoid the frequent communication among agents, a state-based event-triggered consensus strategy is designed, which uses the local information from neighboring agents at sampling moments. Then, several sufficient conditions, which rely on the fractional derivative number and time delay information, are presented to guarantee the consensus of fractional-order multiagent systems based on Takagi-Sugeno fuzzy model. Moreover, Zeno behaviors are precluded by proving that the interval length of the two consecutive event-triggering moments for each agent is greater than a positive constant. Finally, some numerical examples are presented, which not only demonstrated the rationality of our proposed consensus protocol but also shown that the presented consensus method based on the designed event-triggered control protocol has the advantage for avoiding communication congestion compared to the existing results.