Bipartite tracking consensus for fractional-order nonlinear multiagent systems with sampled-data and input saturation

This study focuses on the sampled-data bipartite tracking consensus (BTC) issue for a type of fractional-order (FO) nonlinear multiagent systems (FOMASs) subject to input saturation. In the network under consideration, agents exhibit both competitive (CM) and cooperative (CO) interactions simultaneously. By employing Lyapunov stability theory, the FO Halanay-type Inequality, and the linear matrix inequality (LMI) approach, several criteria are derived to guarantee that the considered MASs can attain the BTC. Moreover, by utilizing the matrix decomposition (MD) approach, the dimensions of matrix inequalities are significantly reduced, which helps alleviate computational complexity. As a result, the derived results can be effectively applied to large-scale FOMASs. Also, the controller gain matrix is clearly represented based on the solutions of a series of matrix inequalities. Besides, we present a method for estimating the maximum attraction region of BTC. Ultimately, numerical simulation is employed to substantiate our theoretical analysis.