Abstract: An iterative learning-based energy-saving control method for a piezoelectric motor, comprising: setting a sampling period of a piezoelectric motor (101); obtaining an expected output trajectory of the piezoelectric motor, and performing sampling according to the sampling period to obtain a sampled expected output sequence (102); setting an initial control input signal of the piezoelectric motor (103); obtaining an actual control input signal according to a mapping relation of the initial control input signal, and transmitting the actual control input signal to the piezoelectric motor to obtain an actual output position (104); obtaining a mapping relation of the output position of the piezoelectric motor according to the actual output position, and sampling the mapping relation according to the sampling period to obtain a sampled actual output sequence (105); calculating the difference between the sampled expected output sequence and the sampled actual output sequence to obtain a sampling error function sequen

Abstract: The invention relates to a field off artificial intelligence (AI) technologies, and discloses a method and an apparatus for high-order iterative self-learning control for a robotic fish, and a storage medium; the control method performs preferential iterative calculation on control gain elements in the control gain set to obtain a target control gain set; and performs high-order iterative calculation according to the target control gains, the first control input thrust and the first tracking error to obtain a target control input thrust, and then controls a robotic fish to swing according to the target control input thrust to obtain an expected speed. In this way, complete tracking and rapid convergence of a swim speed of a robotic fish in the whole operation space may be achieved.