Event-Based Asymptotic Tracking Control for Constrained MIMO Nonlinear Systems via a Single-Parameter Adaptation Method

The issue of event-based asymptotic tracking control for constrained multi-input-multi-output (MIMO) nonlinear systems by designing a single-parameter adaptation method is addressed in this work. Different from some works that rely on prior knowledge of the gain function, this work allows for unknown gain functions. This harsh condition is handled by introducing a new affine variable. Meanwhile, to eliminate the step of turning state constraints into new bounds for tracking errors, a new barrier function is provided instead of continuing to use the Log- or Tan-type barrier Lyapunov function (BLF). This imposes constraints on the system states instead of tracking errors, removing the strict feasibility conditions for virtual controllers. To reduce the computational burden, only one adaptive parameter is designed in this work. Then, an event-triggered strategy is integrated into the control scheme to reduce the waste of communication resources. The systems output can asymptotically track the desired trajectory even if the state of the closed-loop system meets the constraints. Simulation results confirm the validity of this scheme.