Consensus-Based Adaptive Control for Systems with Different Tracking Tasks

This paper focuses on applying the existing consensus idea to adaptive control design. A novel adaptive control approach, called consensus-based adaptive control (CBAC), is proposed for parametric large-scale systems. It is assumed that in each subsystems the unknown parameter vectors are same, but the tracking tasks are different. Each subsystems can use communication networks to exchange their learning information instead of their states. Two cases of communication topologies are investigated in this paper. It is proved in each case that the estimate of unknown parameters in all subsystems can converge to a common constant vector and all subsystems can asymptotically achieve the tracking tasks. A simulation example is provided to illustrate the effectiveness of the control scheme proposed in this paper.