A new event-triggered adaptive tracking controller for nonlinear systems with unknown virtual control coefficients

This paper investigates the adaptive event-triggered tracking control problem for nonlinear systems with virtual control coefficients being unknown nonlinear functions. Firstly, different from approximators using fuzzy logics/neural networks or Nussbaum gain technique, a new transformation with less computation is introduced based on a monotone decreasing positive continuous function to handle uncertain virtual control coefficients (UVCCs). Furthermore, a novel event-triggered threshold scheme is firstly developed, which can switch between the fixed and relative threshold strategies smoothly. Finally, an adaptive event-triggered tracking controller is constructed, whose effectiveness is verified by both theoretical analysis and simulations.