Event-triggered adaptive NN prescribed performance control for under-actuated UUVs with constraints

This paper presents an event-triggered adaptive prescribed performance control scheme for under-actuated unmanned underwater vehicles with constraints. To guarantee the prescribed transient and steady-state performance, a novel appointed-time prescribed performance control is developed to transform the constrained tracking errors into unconstrained transformed errors. Neural networks (NNs) are employed to approximate the unmeasured velocities. Subsequently, an event-triggered adaptive NN output-feedback control scheme is established by using first-order filtering and backstepping techniques, where event-triggered mechanism is introduced to reduce transmission burdens. Meanwhile, all the closed-loop control signals are bounded and the Zeno behavior is avoided. Finally, simulation results are provided to verify the effectiveness of the proposed control scheme.