Position Control Of A Servopneumatic Actuator Using Fuzzy Compensation

Modern servopneumatic positioning technology has made significant inroads in the automated manufacturing environment. The advantages cited by end users include the speed of motion, low cost of installation and maintenance, cleanliness, and the simplicity of operation of these systems relative to other similar hydraulic and electro-mechanical technologies. The robustness of servopneumatic technology solutions is limited by the positioning accuracy of current system controllers. Servopneumatic controllers typically rely on sophisticated control algorithms that accommodate the highly non-linear nature of pneumatic actuator operation. Current positioning accuracy is approximately 1% of the stroke length. System non-linearities include the presence of both static and dynamic actuator friction. Compensating for this stick-slip type of friction which occurs at low velocities is imperative for good positioning accuracy. Taken as a whole, these system characteristics provide an ideal modern laboratory setup for instruction in the use of positioning controllers and the development of supporting control methodologies. The development of several novel undergraduate laboratory modules devoted to the use and understanding of this modern servopneumatic system and implementation of fuzzy based control methods is presented. These modules include an introduction to servopneumatic systems, position control using a standard industry controller, Numerical Control (NC) programming, calibration of proportional flow control valve, results of an implementation of position control using proportional plus integral and derivative (PID) control and alternative control algorithms. The PID control performs much the same function as a feedback controller, but with a more elaborate algorithm for determining its output. It looks at the current value of the error, the integral of the error over a recent time interval, and the current derivative of the error signal to determine not only how much of a correction to apply, but for how long. This three quantities are each multiplied by a "tuning constant" and added together to produce the current controller output Important concepts addressed in the laboratory modules include: 1. Understanding response patterns of the system and development of a friction compensation technique using a fuzzy logic based model of the system. 2. Comparison of the response patterns of the above control systems with respect to positioning accuracy and other parameters.