Control Pneumatic Soft Bending Actuator with Feedforward Hysteresis Compensation by Pneumatic Physical Reservoir Computing

TL;DR

This paper presents a novel fuzzy pneumatic physical reservoir computing model that effectively compensates for hysteresis in soft pneumatic actuators, improving control accuracy and robustness using physical reservoir computing principles.

Contribution

It introduces the first physical system-based feedforward hysteresis compensation model for soft actuators, leveraging pneumatic physical reservoir computing with fuzzy logic.

Findings

FPRC achieves comparable training performance to ESN.

FPRC exhibits better test accuracy and faster execution.

FPRC demonstrates robustness against environmental disturbances.

Abstract

The nonlinearities of soft robots bring control challenges like hysteresis but also provide them with computational capacities. This paper introduces a fuzzy pneumatic physical reservoir computing (FPRC) model for feedforward hysteresis compensation in motion tracking control of soft actuators. Our method utilizes a pneumatic bending actuator as a physical reservoir with nonlinear computing capacities to control another pneumatic bending actuator. The FPRC model employs a Takagi-Sugeno (T-S) fuzzy logic to process outputs from the physical reservoir. The proposed FPRC model shows equivalent training performance to an Echo State Network (ESN) model, whereas it exhibits better test accuracies with significantly reduced execution time. Experiments validate the FPRC model's effectiveness in controlling the bending motion of a pneumatic soft actuator with open-loop and closed-loop control system setups. The proposed FPRC model's robustness against environmental disturbances has also been experimentally verified. To the authors' knowledge, this is the first implementation of a physical system in the feedforward hysteresis compensation model for controlling soft actuators. This study is expected to advance physical reservoir computing in nonlinear control applications and extend the feedforward hysteresis compensation methods for controlling soft actuators.