Adaptive Guaranteed-Performance Consensus Control for Multiagent Systems With an Adjustable Convergence Speed
For researchers in multi-agent systems, this work provides a method to adjust convergence speed adaptively while maintaining guaranteed performance, though it is an incremental improvement over existing adaptive consensus protocols.
This paper proposes a novel adaptive guaranteed-performance consensus protocol for multi-agent systems that allows adjustable convergence speed by changing the adaptive control gain, without increasing communication burden. Sufficient conditions for guaranteed-performance consensus are derived, and the lower bound of the convergence coefficient is shown to be linearly adjustable.
Adaptive guaranteed-performance consensus control problems for multi-agent systems are investigated, where the adjustable convergence speed is discussed. This paper firstly proposes a novel adaptive guaranteed-performance consensus protocol, where the communication weights can be adaptively regulated. By the state space decomposition method and the stability theory, sufficient conditions for guaranteed-performance consensus are obtained, as well as the guaranteed-performance cost. Moreover, since the convergence speed is usually adjusted by changing the algebraic connectivity in existing works, which increases the communication burden and the load of the controller, and the system topology is always given in practical applications, the lower bound of the convergence coefficient for multi-agent systems with the adaptive guaranteed-performance consensus protocol is deduced, which is linearly adjustable approximately by changing the adaptive control gain. Finally, simulation examples are introduced to demonstrate theoretical results.