Rudder Roll Damping Autopilot Using Dual Extended Kalman Filter–Trained Neural Networks for Ships in Waves

The roll motions of ships advancing in heavy seas have severe impacts on the safety of crews,vessels,and cargoes;thus,it must be damped.This study presents the design of a rudder roll damping autopilot by utilizing the dual extended Kalman filter(DEKF)trained radial basis function neural networks(RBFNN)for the surface vessels.The autopilot system constitutes the roll reduction controller and the yaw motion controller implemented in parallel.After analyzing the advantages of the DEKF-trained RBFNN control method theoretically,the ship’s nonlinear model with environmental disturbances was employed to verify the performance of the proposed stabilization system.Different sailing scenarios were conducted to investigate the motion responses of the ship in waves.The results demonstrate that the DEKF RBFNN based control system is efficient and practical in reducing roll motions and following the path for the ship sailing in waves only through rudder actions.

A cascade model of information processing and encoding for retinal prosthesis

Retinal prosthesis offers a potential treatment for individuals suffering from photoreceptor degeneration diseases.Establishing biological retinal models and simulating how the biological retina convert incoming light signal into spike trains that can be properly decoded by the brain is a key issue.Some retinal models have been presented,ranking from structural models inspired by the layered architecture to functional models originated from a set of specific physiological phenomena.However,Most of these focus on stimulus image compression,edge detection and reconstruction,but do not generate spike trains corresponding to visual image.In this study,based on stateof-the-art retinal physiological mechanism,including effective visual information extraction,static nonlinear rectification of biological systems and neurons Poisson coding,a cascade model of the retina including the out plexiform layer for information processing and the inner plexiform layer for information encoding was brought forward,which integrates both anatomic connections and functional computations of retina.Using MATLAB software,spike trains corresponding to stimulus image were numerically computed by four steps：linear spatiotemporal filtering,static nonlinear rectification,radial sampling and then Poisson spike generation.The simulated results suggested that such a cascade model could recreate visual information processing and encoding functionalities of the retina,which is helpful in developing artificial retina for the retinally blind.