Abstract
In this chapter, a comprehensive experimental study is carried out on modeling, identification, and position control of a pneumatic actuator equipped with an electrical proportional directional control valve. The nonlinear state space representation of the pneumatic system is obtained based on dynamic behavior of the cylinder and the air pressure through the proportional valve. The derived dynamic model of the pneumatic system has unknown parameters, including friction force, viscous damping coefficient, and the proportional valve variables. Rather than using simple linear models, the LuGre model is considered for modeling the highly nonlinear behavior of the friction force. In addition, the viscous coefficient is measured during an experimental test which is called the Free-Fall test. Upon performing several step response tests on the pneumatic setup, unknown parameters of the dynamic model are identified by resorting to the Genetic Algorithm (GA). The identified model is validated based on the step response tests, which can demonstrate how much the derived model is accurate. Furthermore, a model-free and a model-based control strategy are designed using the obtained state space equations of the pneumatic system. For this purpose, a Soft Switching Control (SSC) as the model-free and a Backstepping–Sliding Mode Control (BS-SMC) as the model-based control strategies are applied to tracking and position control of the pneumatic actuator. In order to evaluate the tracking performance of the proposed controllers, sinusoidal trajectories with frequencies in the range of 0.1 to 1 Hz are tested as desired trajectories. The controllers' performance are put into contrast to the Root Mean Square Error (RMSE), frequency response (Bandwidth), and Maximum Absolute Error (MAE) criteria. The experimental results reveal that the BS-SMC can make a better performance in position control of the pneumatic actuator regarding the aforementioned criteria.
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