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Position Control of a Pneumatic Drive Using a Fuzzy Controller with an Analytic Activation Function.

Željko Šitum¹, Danko Ćorić²

¹Department of Robotics and Production System Automation, Faculty of Mechanical Engineering and Naval Architecture, University of Zagreb, I. Lučića 5, 10000 Zagreb, Croatia.

Sensors (Basel, Switzerland)

|February 15, 2022

Summary

This study introduces an analytic fuzzy logic controller for pneumatic servo drives, simplifying rule-based systems and improving control performance. The novel approach eliminates rule base complexity, enhancing efficiency in pneumatic system applications.

Keywords:

activation function fuzzy logic position control servo pneumatic drive

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Area of Science:

Engineering
Control Systems
Artificial Intelligence

Background:

Pneumatic servo drives are crucial in automation but challenging to control precisely.
Conventional fuzzy logic controllers face scalability issues with increasing input variables.
Proportional valves introduce non-linearities in pneumatic systems.

Purpose of the Study:

To develop a novel fuzzy logic controller (FLC) for precise position control of pneumatic servo drives.
To overcome the exponential growth of rules in traditional FLCs by using an analytic function for defuzzification.
To adapt the controller synthesis to the specific flow rate characteristics of proportional valves.

Main Methods:

Application of a fuzzy logic controller with an analytic activation function for defuzzification.
Fuzzification of input signals using Gaussian-shaped fuzzy sets with adjustable parameters.
Replacement of the conventional 2-D fuzzy rule base with a 1-D analytic function for controller output calculation.
Controller synthesis tailored to the proportional valve's flow rate characteristics.

Main Results:

Successfully eliminated the problem of exponential rule growth inherent in conventional fuzzy logic control.
Developed a simplified 1-D defuzzification approach based on an analytic function.
Demonstrated effective position control of a servo pneumatic drive.
Validated the control algorithms through computer simulations and real-world testing on a pneumatic rodless cylindrical drive.

Conclusions:

The proposed analytic fuzzy logic controller offers a more efficient and scalable alternative for pneumatic servo drive control.
The method simplifies controller design by replacing rule bases with analytic functions.
The controller effectively manages the complexities of pneumatic systems, verified by simulation and experimental results.