Pneumatic actuator is widely used in the automation industry and in the field of automatic control due to its advantages such as high power to weight ratio, costeffective and uses air as a clean medium to drive it. However, pneumatic actuator also has some drawback in control due to the nonlinear factors such as air compressibility and friction. Therefore, the purpose of this research is to design a controller that will control the position of the cylinder pneumatic stroke. Fuzzy Logic Control is proposed because of its simplicity in terms of less mathematical equation and also its performance in controlling the nonlinearities. Three different types of Fuzzy Logic controller were designed and compared to observe the performance of the controller in controlling the pneumatic actuator. An optimization method of the Particle Swarm Optimization (PSO) algorithm is used in tuning the fuzzy control parameter. PSO is used to find the best value of the parameter involved in the controller design. Both controllers and optimization method are designed using MATLAB/Simulink platform from position transfer function obtained by System Identification (SI) technique. Then, the simulation results are analyzed and validated with real-time experiment using the Data Acquisition (DAQ) card. The experiment has been done to the pneumatic actuator with different loads and positions target. A Pneumatic Ball and Beam System (PABBS) is proposed as the application of the position controller. The mathematical model of the system is developed and tested with simulation and experiments for its fast response and stability in controlling the ball movement. Results show that Proportional-Derivative Fuzzy Logic Controller (PD-Fuzzy) offers better control compared to other controllers in terms of stability and robustness for the pneumatic actuator and cascaded PD-Fuzzy controller gives better control compared with position and rate feedback controller for the PABBS application.
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