Adaptive Neural Control for Nonlinear MIMO Function Constraint Systems

Dear Editor, In this letter, a novel adaptive control design problem for uncertain nonlinear multi-input-multi-output (MIMO) systems with time-varying full state constraints is proposed, where the considered consist of various subsystems, and states each subsystem are interconnected tightly. It universally acknowledged that in existing researches constraints, system constraint bounds always constants or functions. Different from previous methods, boundary letter regarded as special function not only time but variables. order to handle tangent type barrier Lyapunov functions (tan-TVBLFs) introduced. By combining neural networks (NNs) backstepping technique, an intelligent controller developed. Meanwhile, we introduce even guarantee feasibility NN approximation unknown over practical compact sets. The mentioned strategy certified through simulation results.