Fuzzy neural network based adaptive iterative learning control scheme for velocity tracking of wheeled mobile robots

Abstract

The velocity tracking problem of wheeled mobile robots (WMRs) which work with repeatable trajectories and different initial errors is discussed in the paper. Three mathematical models of WMR, namely, kinematic model, dynamic model and DC motor driven model, are deduced and the stratagem of fuzzy neural network based adaptive iterative learning control (FNN-AILC), which includes the components of fuzzy neural network, approximation errors and feedback, is presented. The proposed scheme can deal with MIMO system, which is distinguished from previous research work. The simulation is presented and the result verifies the effectiveness of the controller.