Adaptive Neural Network Control with Control Allocation for A Manned Submersible in Deep Sea

摘要

This paper thoroughly studies a control system with control allocation for a manned submersible in deep sea being developed in China.The proposed control system consists of a neural-network-based direct adaptive controller and a dynamic control allocation module.A control energy cost function is used as the optimization criteria of the control allocation module,and weighted pseudo-inverse is used to find the solution of the control allocation problem.In the presence of bounded unknown disturbance and neural networks approximation error,stability of the closed-loop control system of manned submersible is proved with Lyaponov theory.The feasibility and validity of the proposed control system is further verified through experiments conducted on a semi-physical simulation platform for the manned submersible in deep sea.