In order to solve the problem of cleaning and testing the glass curtain wall of high-rise buildings, a multi legged vacuum adsorption wall climbing robot is explored. In order to realize the smooth operation of the wall climbing robot, the main thing is to improve the control accuracy of the motor speed. The fuzzy PID algorithm is used for control, and on this basis, the particle swarm algorithm is used for further iterative optimization. Through the iterative optimization ability of particle swarm optimization algorithm, the scale factors of three PID parameters in fuzzy PID control are determined in real time, and a control system with good performance is obtained. The results show that when the scale factors CKP, CKI and CKD are 0.1, 8.23 and 0 respectively, the stability of the system reaches the optimum. Compared with fuzzy PID control, the response speed of the system further optimized by particle swarm optimization algorithm is improved by 0.024 s, and there is also no overshoot, which can meet the requirements of the system.