A design method of model reference adaptive consensus control of multi-agent systems composed of unknown linear processes is presented in this paper. The proposed control scheme is constructed via a backstepping procedure and state variable filters together with a restricted information network structure among agents. It is shown that the resulting control system is robust to uncertain system parameters and that the desirable consensus tracking is achieved asymptotically or approximately via the adaptation mechanism.