| The icing disasters of transmission line such as line trip, break line, pole collapse, insulator flashover and communication interruption have resulted in huge economic lose of nation. The traditional manual deicing is not only inefficient but also threatens to the safety of electrical workers. Therefore, it has immediate practical significance and important value in development of transmission line deicing robot instead of traditional manual deicing. Moreover, the precise and stable trajectory tracking is the guarantee of deicing robot walking, crossing obstacles and deicing on the electric-power line autonomously. According to the special task and complicated work environment of deicing robot, a series of methods for trajectory tracking control are put forward in this thesis.Firstly, much research is done on modeling for deicing robot based on the structure of its motion control system and analysis of the trajectory tracking. Due to the specialty of robot structure and work environment, there is the nonlinear and strong coupling not only between the robot arm and transmission but also between the robot arm and the body positions. Therefore, the modeling problem of the deicing robot is divided into the kinematic, dynamic and the hybrid model. This is convenient to obtain the velocity and acceleration of robot and robot trajectory tracking control.After the accurate modeling of the deicing robot, several methods in trajectory tracking control are studied, such as the PID tracking control, adaptive tracking control, the PID tracking control based on BP neural network, the adaptive tracking control based on BP neural network, the PID tracking control based on particle swarm optimization neural network and the adaptive tracking control based on particle swarm optimization neural network. Finally, simulation experiments show the effectiveness of established deicing robot hybrid model and above-mentioned trajectory tracking control methods. |
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