In order to solve the problem that it is difficult to accurately model the complex fluid domain in the negative pressure chamber of the robot in the process of wall climbing, and thus cannot quickly and steadily adsorb, a double closed-loop control strategy based on parameter identification and particle swarm optimization is proposed in this paper to improve the speed and stability of the adsorption response of the robot in the process of wall climbing. Firstly, a vacuum negative pressure wall climbing robot with a spring pressure regulating structure is developed, and the critical conditions of the robot’s instability are solved by mechanical analysis. Then, the rigid-flexible coupling model of the whole machine was established based on mass, spring and Maxwell viscoelastic elements. The model parameters of the adsorption system were identified by vacuum adsorption test. Compared with the experimental data, the accuracy of the model was more than 80%. On this basis, PID controller is used to adjust the adsorption response speed of the robot, a double closed-loop stable adsorption control strategy is designed, and the control parameters of the adsorption system are adjusted by using the dynamic weight standard particle swarm optimization algorithm. Finally, simulation and prototype tests show that, the proposed control strategy can shorten the static and dynamic response time of the adsorption system by about 3.5 s and 1.4 s, the flow response time by about 1.15s, the maneuvering performance of the whole system is improved by about 26%, and the parameter overshoot and steady-state error are lower, which provides a theoretical reference for the stability control and engineering application of the wall-climbing robot.