ABSTRACT
The chapter is devoted to the design of an intelligent neural network-based control system for underwater robots. A new algorithm for intelligent controller learning is derived using the speed gradient method. The proposed systems provide robot dynamics close to the reference ones. Simulation results of neural network control systems for underwater robot dynamics with parameter and partial structural uncertainty have confirmed the perspectives and effectiveness of the developed approach.
