Research Of Control Strategy In Power Transmission Line De-icing Robot

In connection with the particular working environment of power transmission line de-icing robot, designing the work of the robot to impact de-icing, a method that the S-shape curve is applied in the trajectory planning of transmission line de-icing robot is proposed in this paper. The method makes full use of advantages of S-shape curve and improves the traditional complex S-shape curve algorithms. A new trajectory planning algorithm presented in the paper, which gives the corresponding mathematical description, uses not only four backward acceleration and deceleration sections but two forward acceleration sections. The simulation results show that the new adopted algorithm is of great flexibility and practical engineering value.Using Iterative Learning Control as the control strategy of the de-icing robot, to achieve the full trace in the process of de-icing, the paper designs the fuzzy PID learning control system by using fuzzy control technology and the iterative learning control. The system uses fuzzy tuning elements to do real time tuning empirical parameters of traditional PID iterative learning control system, which solves the problem of bad real time capability and low convergence speed of the traditional PID iterative learning control system. The result of the simulation shows that this method has excellent control effect.Facing the problem of bigger steady-state error by using the traditional fuzzy controller, the paper introduces variable universe fuzzy control. The characteristics of the variable universe fuzzy control system are carefully studied, and the variable universe fuzzy PID iterative learning control algorithm is designed. Finally the system is put into the de-icing robot trajectory tracking . Through analysis on comparing with the traditional iterative learning control system PID tracking, the result of the simulation shows that the method is efficiency and superiority.