A miniature pneumatic bending rubber actuator controlled by using the PSO-SVR-based motion estimation method with the generalized Gaussian Kernel

Kou Fujita, Mingcong Deng, Shuichi Wakimoto

Research output: Contribution to journalArticle

6 Citations (Scopus)

Abstract

Soft actuators have been employed in various fields recently. A miniature pneumatic bending rubber actuator is one of the soft actuators. This actuator will be used for medical and biological fields. Its flexibility and high safety are suitable for fragile objects. However, its modeling is difficult due to its nonlinearity. There are no suitable sensors to measure the output of this actuator. In this paper, the particle swarm optimization-support vector regression (PSO-SVR)-based estimation method with the generalized Gaussian kernel is proposed. An experimental result with the operator-based robust nonlinear control system is employed to verify the effectiveness of the proposed method.

Original languageEnglish
Article number6
JournalActuators
Volume6
Issue number1
DOIs
Publication statusPublished - Mar 1 2017

Fingerprint

Gaussian Kernel
Support Vector Regression
Rubber
Motion Estimation
Motion estimation
Pneumatics
Particle swarm optimization (PSO)
Particle Swarm Optimization
Actuator
Actuators
Nonlinear control systems
Nonlinear Control Systems
Robust Control
Safety
Flexibility
Nonlinearity
Verify
Sensor
Output
Sensors

Keywords

  • Nonlinear control
  • Operator theory
  • Particle swarm optimization
  • Soft actuator
  • Support vector machine
  • Support vector regression

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Control and Optimization

Cite this

A miniature pneumatic bending rubber actuator controlled by using the PSO-SVR-based motion estimation method with the generalized Gaussian Kernel. / Fujita, Kou; Deng, Mingcong; Wakimoto, Shuichi.

In: Actuators, Vol. 6, No. 1, 6, 01.03.2017.

Research output: Contribution to journalArticle

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