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Research Papers

Design, Modeling, and Control of a Portable Leg Rehabilitation System

[+] Author and Article Information
Khaled M. Goher

Faculty of Environment Society and Design,
Lincoln University,
Lincoln 7647, New Zealand
e-mail: khaled.goher@lincoln.ac.nz

Sulaiman O. Fadlallah

School of Engineering, Computer, and
Mathematical Sciences,
Auckland University of Technology,
Auckland 1142, New Zealand
e-mail: sulaiman.fadlallah@aut.ac.nz

Contributed by the Dynamic Systems Division of ASME for publication in the JOURNAL OF DYNAMIC SYSTEMS, MEASUREMENT, AND CONTROL. Manuscript received August 18, 2016; final manuscript received January 17, 2017; published online May 12, 2017. Assoc. Editor: Dumitru I. Caruntu.

J. Dyn. Sys., Meas., Control 139(7), 071013 (May 12, 2017) (15 pages) Paper No: DS-16-1410; doi: 10.1115/1.4035815 History: Received August 18, 2016; Revised January 17, 2017

In this work, a novel design of a portable leg rehabilitation system (PLRS) is presented. The main purpose of this paper is to provide a portable system, which allows patients with lower-limb disabilities to perform leg and foot rehabilitation exercises anywhere without any embarrassment compared to other devices that lack the portability feature. The model of the system is identified by inverse kinematics and dynamics analysis. In kinematics analysis, the pattern of motion of both leg and foot holders for different modes of operation has been investigated. The system is modeled by applying Lagrangian dynamics approach. The mathematical model derived considers calf and foot masses and moment of inertias as important parameters. Therefore, a gait analysis study is conducted to calculate the required parameters to simulate the model. Proportional derivative (PD) controller and proportional-integral-derivative (PID) controller are applied to the model and compared. The PID controller optimized by hybrid spiral-dynamics bacteria-chemotaxis (HSDBC) algorithm provides the best response with a reasonable settling time and minimum overshot. The robustness of the HSDBC–PID controller is tested by applying disturbance force with various amplitudes. A setup is built for the system experimental validation where the system mathematical model is compare with the estimated model using system identification (SI) toolbox. A significant difference is observed between both models when applying the obtained HSDBC–PID controller for the mathematical model. The results of this experiment are used to update the controller parameters of the HSDBC-optimized PID.

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References

Figures

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Fig. 1

System overall design using solidworks

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Fig. 2

System schematics diagram

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Fig. 3

Modes of operation

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Fig. 4

Knee and ankle joint displacement–torque relation in adams

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Fig. 5

(a) System open-loop response: angular positions with a unit step input and (b) system open-loop response: angular positions for a step input with a gain of 100

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Fig. 6

PLRS schematic description of the control strategy

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Fig. 7

Calf and foot system response using proportional derivative (PD) controller

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Fig. 8

Calf and foot system response using PID controller

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Fig. 9

Hybrid spiral-dynamics bacteria-chemotaxis (HSDBC) optimization algorithm

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Fig. 10

Calf and foot system response comparison (manual tuning versus HSDBC)

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Fig. 11

Characteristics parameters of calf and foot movement

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Fig. 12

Calf and foot control effort comparison

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Fig. 13

Disturbance signals applied on the system

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Fig. 14

Calf and foot system response with external disturbance

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Fig. 15

System identification toolbox graphical user interface (GUI)

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Fig. 17

Designed circuit for motor orientation control

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Fig. 18

Hardware low-pass filter

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Fig. 20

Prototype modes of operation

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Fig. 21

Calf and foot measured outputs

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Fig. 22

System behavior while input variation

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Fig. 23

Calf measured and simulated model output comparison

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Fig. 24

Comparison between mathematical model and actual prototype by applying HSDBC–PID controller for calf

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Fig. 25

Angular calf displacement (math. model HSDBC–PID controller versus updated HSDBC–PID controller)

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Fig. 26

Foot measured and simulated model output comparison

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Fig. 27

Comparison between mathematical model and actual prototype by applying HSDBC–PID controller for foot

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Fig. 28

Angular foot displacement (math. model HSDBC–PID controller versus updated HSDBC–PID controller

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