A variable-batch-length iterative learning optimization control method for a mobile robot, relating to the field of mobile robot optimization control. The control method comprises: converting a repeatedly running mobile robot system into an input and output matrix model of time series on the basis of a boosting technology, and establishing a variable batch length problem as a batch length random change model by means of a random variable; for a batch length variation occurring in the system, designing an iterative learning optimization control algorithm by using an optimization idea, and obtaining a feedforward form of the iterative learning optimization control algorithm under the batch length variation on the basis of a performance index function; and proving, on the basis of a successive projection framework, the convergence of the iterative learning optimization control algorithm designed in the presence or absence of input constraints in mathematical expectation sense. The tracking control problem of the mobile robot system under a variable batch length is solved, and input constraints are considered, thereby achieving high-precision tracking of a desired trajectory.
VARIABLE-BATCH-LENGTH ITERATIVE LEARNING OPTIMIZATION CONTROL METHOD FOR MOBILE ROBOT