Research On Motion Control Of Remote Operated Vehicle Based On Fuzzy PID Control

As well as we know, Twenty-first Century is an era that belongs to the ocean. Ocean space has become an important field of military and economic competition all over the world. The major countries all attach importance to marine research and grow with each passing day. High-tech automation equipment in the large depth of underwater has become the primary choice for marine exploration and rescue. Along with the arrival of the upsurge, Remotely Operated Vehicle referred to as ROV, has made considerable development. Compared with autonomous underwater vehicle, the ROV gets the power and control instructions provided by umbilical cord from the surface of the cable, which is characterized by a light, simple, reliable with strong operational capability and relatively simple technical complexity.As typical dual-use equipment, ROV not only can be used for the exploration and development of marine resources, but also plays an irreplaceable role in the modern naval construction. It has become an indispensable platform used for underwater exploration and operation. As a rescue force, we shoulder the underwater rescue and salvage mission. Wide operating range and depth and engineering workof high demand are consistent with the features and intention. Including China the major powers are developping various ROV, to complete mine clearance, mine detection, investigation, detection, salvage and other tasks. This topic will use ROV(“YQ2B”) as the research object, to study and optimize the law of control.In this paper, the spatial kinematic model of ROV is established. According to the practical needs, the six degree of freedom motion model is simplified. Using the theory of model decoupling, plane hypothesis and model linearization, the parameters of the controller are adjusted by thetwo-dimensional fuzzy logic control based on the classic PID control algorithm. At the same time, the design of PID Fuzzy Logic Controller is accomplished by using the Logic Fuzzy provided by Matlab software. With the help of Matlab/Simulink, the heading and depth control are simulated and the simulation results are compared. The better applicability of fuzzy PID control is verified.