Adaptive consensus algorithms for state variables of leaderless multi-agent systems

In this paper, we propose consensus algorithms to achieve an agreement of the state values of all agents for multi-agent systems consisting of dynamical systems with unknown parameters. By adjusting feedback gains online, the stability of multi-agent system is guaranteed against uncertainties of parameters. We assume that there is neither leader nor virtual leader providing the target of state values for all agents. Then, a common target for all agents is decided by a distributed approach. By the control inputs, the state values of all agents converge to the common target, and consensus is achieved.