Highly accurate trajectory tracking control for Automatic Guided Vehicle using fuzzy PID

Automatic Guided Vehicle (AGV) with high tracking accuracy plays an important role in unmanned factories and intelligent manufacturing, and has a broad development prospect. In order to improve the accuracy of AGV trajectory tracking, a two-input single-output fuzzy adaptive parallel proportional-integral-derivatives (PIDs) trajectory tracking control algorithm is proposed in this paper. A mathematical model of lateral distance error and navigation angle error of AGV is constructed and used as control inputs. A weighted summation method is proposed to merge the outputs of parallel PIDs into a single-output to adjust the speed of AGV driving wheels. In the simulation experiments, the AGV tracks linear and circular reference trajectories, respectively. Simulation results have demonstrated that the effectiveness and superiority of the proposed algorithm for AGV trajectory tracking.