Adaptive distributed observer-based predictive formation tracking control for autonomous underwater vehicles

Numerous existing autonomous underwater vehicles (AUVs) formation control works have focused on the observation of external time-varying disturbances in trajectory tracking control. However, external time-varying disturbance outliers cannot be ignored due to the complex marine environment. It is rarely considered in pre-vious research. In this paper, a double-layer distributed formation prediction control scheme is designed, including an upper-level adaptive distributed observer and a lower-level predictive controller. Firstly, the ve-locity is observed and regarded as an unknown variable by the expectation maximization algorithm. The gain in the observer will be optimized by adaptive cubature Kalman to improve the anti-disturbance performance of the adaptive distributed observer. Then, the constraints of internal safety distance and input saturation are fully considered. The distributed cooperative cost function is constructed based on the virtual trajectory, which is further introduced into local rolling domain optimization to realize formation predictive control. The bound-edness of innovation and Lyapunov stability are utilized to prove the reliability of the control system. Some comparative simulation experiments are designed to demonstrate the effectiveness and robustness of the pro-posed method.