Course control method of manta ray-imitated robotic fish based on Q learning and pectoral fin phase difference

The invention relates to a manta ray imitating robotic fish course control method based on Q learning and pectoral fin phase difference, and compared with a traditional control method, the manta ray imitating robotic fish course control method does not need to establish a control object model, acquires experimental data, carries out offline training on a Q table, then transplants the table to a prototype controller, and obtains a control variable in a table look-up mode. And controlling the prototype to move at a fixed depth. Compared with other reinforcement learning control methods, the method is low in hardware resource requirement, small in space requirement, small in power consumption and convenient to implement. The beneficial effects of the invention are that: the hardware requirement for the controller is low, and can be realized by a common single-chip microcomputer, the cost is saved, and the effect of saving space and energy is also achieved. A lot of time cost is saved. The method is simple to imp