This paper addresses the finite-time three-dimensional path-following control problem for underactuated autonomous airship with error constraints and uncertainties. First, a five degrees-of-freedom path-following error model in the Serret-Frenet coordinate frame is established. By applying the finite-time stability theory, a virtual guidance-based finite-time adaptive neural backstepping path-following control approach is proposed. Barrier Lyapunov functions (BLFs) are introduced to deal with attitude error constraints. Neural networks (NNs) are presented to compensate for the uncertainties. To prevent the “explosion of complexity” in the design of the backstepping method, a finite-time convergent differentiator (FTCD) is introduced to estimate the time derivatives of virtual control signals. Stability analysis showed that all closed-loop signals are uniformly ultimately bounded, the constrained requirements on the airship attitude errors are never violated, and the path-following errors converge to a small neighborhood of the origin in a finite time. At last, simulation studies are provided to demonstrate the effectiveness of the proposed control approach.
Three-dimensional path following control based net cage inspection bionic robotic fish
