Modelling and control strategies development of GAREX

Modelling and control strategies development of GAREX

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This chapter focuses on a multi-input-multi-output (MIMO) sliding mode (SM) controller which is aimed to simultaneously control the angular trajectory and compliance of the GAit Rehabilitation Exoskeleton (GAREX). The MIMO controller is developed based on the complete model of GAREX system which consists of four sub-system models. They are flow dynamics of the valves, pressure and force dynamics of the antagonistic pneumatic artificial muscles, as well as the load dynamics of the exoskeleton. Experiments with and without healthy subjects are conducted a GAREX to validate the developed SM controllers. The experimental results indicate good multivariable tracking performance of this controller.

Chapter Contents:

  • 9.1 Introduction
  • 9.2 System modelling
  • 9.2.1 Valve flow dynamics
  • 9.2.2 Pneumatic muscle pressure dynamics
  • 9.2.3 Pneumatic muscle force dynamics model
  • 9.2.4 Load dynamics of the mechanism
  • 9.3 Multi-input-multi-output sliding mode control for GAREX
  • 9.4 Experimental validation
  • 9.4.1 Experiments with the knee joint mechanism
  • 9.5 Pilot study of gait training with GAREX
  • 9.5.1 Generating reference gait trajectory
  • 9.5.2 Treadmill-based gait experiment with healthy subject
  • 9.6 Summary
  • Appendix A The mechanism dynamics calculation
  • References

Inspec keywords: MIMO systems; gait analysis; medical robotics; trajectory control; patient rehabilitation; compliance control; variable structure systems; multivariable control systems; pneumatic actuators

Other keywords: antagonistic pneumatic artificial muscles; angular trajectory control; GAREX; valve flow dynamics; load dynamics; multivariable tracking performance; MIMO controller; multiinput-multioutput sliding mode controller; force dynamics; control strategy development; compliance control; gait rehabilitation exoskeleton

Subjects: Patient care and treatment; Physics of body movements; Spatial variables control; Mechanical variables control; Robotics; Biological and medical control systems; Patient care and treatment; Multivariable control systems

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