Asymptotically stable adaptive consensus control of multi-agent systems based on H∞ control criterion

Design methodologies of asymptotically stable adaptive H∞ consensus control of multi-agent systems composed of the first-order and the second-order regression models are presented in this paper. The proposed control schemes are derived as solutions of certain H∞ control problems, where estimation errors of tuning parameters and imperfect knowledge of the leader are regarded as external disturbances to the process. It is shown that the resulting control systems are robust to uncertain system parameters and that the desirable consensus tracking is achieved asymptotically via adaptation schemes and L2-gain design parameters together with an introduction of the generating model of the leader.