A great number of pipelines in China are in unsatisfactory condition and faced with problems of corrosion and cracking, but there are very few approaches for underwater pipeline detection. Pipeline detection autonomous underwater vehicle (PDAUV) is hereby designed to solve these problems when working with advanced optical, acoustical and electrical sensors for underwater pipeline detection. PDAUV is a test bed that not only examines the logical rationality of the program, effectiveness of the hardware architecture, accuracy of the software interface protocol as well as the reliability and stability of the control system but also verifies the effectiveness of the control system in tank experiments and sea trials. The motion control system of PDAUV, including both the hardware and software architectures, is introduced in this work. The software module and information flow of the motion control system of PDAUV and a novel neural network-based control (NNC) are also covered. Besides, a real-time identification method based on neural network is used to realize system identification. The tank experiments and sea trials are carried out to verify the feasibility and capability of PDAUV control system to complete underwater pipeline detection task.