Conflict Constrained Control for Switched Multiagent Systems With Nonaffine Nonlinear Faults and Uncertainties

This article investigates a conflict-constrained control method for switched multiagent systems with nonaffine nonlinear faults. Existing studies on state constraints often assume that the reference signal always stays within the constraint set. However, in practice, constraints may be dynamically detected during system operation and conflict with predefined reference signals, causing brief violations of the constraint boundaries. When the reference signal cannot remain within the prescribed range, many backstepping control methods based on BLF and nonlinear transformations become ineffective. To address this, a new SRS is constructed by using a virtual circle approach, and a conflict-constrained control method is proposed. By combining a common Lyapunov function and the radial basis function neural network, the effects of switching behavior and nonaffine nonlinear faults can be effectively compensated. A shift function is also introduced in the coordinate transformation to further relax constraints on initial values. The proposed method is validated through multiple simulation experiments.