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Model-Based Nonlinear Feedback Controllers for Pressure Control of Soft Pneumatic Actuators Using On/Off Valves
Matheus S Xavier1, Andrew J Fleming1, Yuen K Yong1
1Precision Mechatronics Lab, The University of Newcastle, Callaghan, NSW, Australia.
Frontiers in Robotics and AI
|April 4, 2022
Summary
This study compares three nonlinear feedback controllers for soft actuators. The proposed controllers effectively track pressure, demonstrating improved performance over open-loop systems.
Area of Science:
- Robotics
- Control Systems Engineering
- Soft Actuator Technology
Background:
- Soft actuators require precise low-level control for effective operation.
- Pneumatic systems with solenoid valves present challenges in achieving accurate pressure regulation.
- Open-loop systems exhibit significant limitations in performance and robustness.
Purpose of the Study:
- To apply and compare three nonlinear feedback control strategies for soft actuators.
- To evaluate the effectiveness of State-Dependent Riccati Equation control, sliding mode control, and feedback linearization.
- To enhance controller robustness against model uncertainties and improve pressure tracking.
Main Methods:
- Development of a mathematical model for the pneumatic soft actuator system.
- Utilizing Simscape Fluids for system modeling and control strategy evaluation.
- Implementation of integral action for sliding mode and feedback linearization controllers.
- Design of a feedforward component integrated with a PI controller with anti-windup.
Main Results:
- The developed mathematical model accurately represents the pneumatic system dynamics.
- Simulation and experimental results confirm the effectiveness of the proposed nonlinear controllers.
- All considered controllers demonstrated successful pressure tracking capabilities.
- Augmenting sliding mode and feedback linearization with integral action improved robustness.
Conclusions:
- Nonlinear feedback controllers offer superior performance for low-level control of soft actuators compared to open-loop systems.
- The State-Dependent Riccati Equation control, sliding mode control, and feedback linearization are viable strategies for pneumatic soft actuator control.
- Integral action enhances the robustness of sliding mode and feedback linearization controllers against model uncertainties.
- The integrated feedforward-PI controller provides effective pressure tracking for soft actuators.
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