This paper describes distributed adaptive methods for solving the trajectory distortion control problem of intelligent lawnmowers. The strategy we have chosen is to use the association of motor current changes with changes in the movement patterns of the trajectory to try to modify the relationship between the fuzzy controller and the Proportional Integral Derivative(PID)controller based on traditional fuzzy PID control theory in order to Design a new low-cost control scheme that uses the differences between current detection and linearized models as data feedback, interpolates these linear models with the Takagi-Sugeno(T-S)fuzzy method\cite{1985Fuzzy} to approximate the entire non-linear model, and then the concept of parallel distributed compensation(PDC)synthesizes a state feedback controller. A linear quadratic regulator(LQR)is used to stabilize the system and achieve the desired response. A PID fuzzy control method is then used to form the control of the intelligent lawnmower motor.This strategy uses data feedback obtained by monitoring the left and right motor current fluctuations, and it can be seen from the practical results that the proposed method is effective in obtaining an ideal linear path with good tracking behavior in various situations.And this paper uses the current monitoring changes control method to determine whether the bias voltage tested and confirmed that the method can achieve stable path control.