# A Novel Method for Designing Motion Profiles Based on a Fuzzy Logic Algorithm Using the Hip Joint Angles of a Lower-Limb Exoskeleton Robot

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## Abstract

**:**

## 1. Introduction

## 2. Methods

#### 2.1. Design of an Exoskeleton Robot with an Electro-Hydarulic Actuator System

#### 2.2. Design of a Real-Time Motion Profile for the Exoskeleton Robot’s Knee Joint Angle

#### 2.3. The Proposed Algorithm with a Controller

## 3. Experiment

## 4. Conclusions

## Author Contributions

## Funding

## Conflicts of Interest

## References

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**Figure 1.**Design of an exoskeleton robot with an electro-hydraulic actuator (EHA) system. DoF: degrees of freedom.

**Figure 5.**Input membership function of the fuzzy set: Hip joint angles. N, negative; ZR, zero; P, positive; PS, positive small; PM, positive medium; and PL, positive large.

**Figure 6.**Simulation results of the proposed algorithm for estimating the knee joint angle: (

**a**) the summed plantar pressure sensors for distinguishing the gait phase, (

**b**) the crisp inputs of the hip joint angles, (

**c**) the comparison of the estimated robot knee and the actual robot knee, and (

**d**) the measurement error between the estimated output and the actual output.

**Figure 8.**System block diagram of the estimated algorithm combined with the EHA [9].

**Figure 9.**Schematic diagram of the experimental set-up for the exoskeleton system. ADC, analog-to-digital converter; CAN, controller area network; LVDT, linear variable differential transformer; MCU, main controller unit; SPI, serial peripheral interface; and MFC, Microsoft foundation class.

**Figure 10.**Experimental results of the proposed algorithm for estimating the knee joint angle: (

**a**) the crisp inputs of the hip joint angles, (

**b**) the plantar pressure sensors for distinguishing the gait phase, (

**c**,

**d**) the fuzzy inputs and outputs, respectively, between 1.7 and 2.7 s, and (

**e**) the results of the knee joint angle ${x}_{r}$ and the estimated knee joint angle ${\widehat{x}}_{r}$.

**Figure 11.**Exoskeleton robot in the walking experiment on level ground: (

**a**) the change of the hip joint angles, (

**b**) the sum of the plantar pressure sensors, (

**c**) the motor speed, (

**d**) the tracking error, and (

**e**) a comparison of the actual and the estimated knee joint angles of the exoskeleton robot.

**Figure 12.**The sit-to-stand movement experiment: (

**a**) the change in the hip joint angles, (

**b**) the motor speed, (

**c**) tracking error, and (

**d**) a comparison of the actual and the estimated knee joint angles of the exoskeleton robot.

Input2 | |||||||
---|---|---|---|---|---|---|---|

RN | RZR | RP | RPS | RPM | RPL | ||

Input1 | LN | VL | L | M | H | VH | NA |

LZR | L | VL | L | M | H | VH | |

LP | M | L | VL | L | M | H | |

LPS | H | M | L | VL | L | M | |

LPM | VH | H | M | L | VL | L | |

LPL | NA | VH | H | M | L | VL |

Input2 | |||||||
---|---|---|---|---|---|---|---|

RN | RZR | RP | RPS | RPM | RPL | ||

Input1 | LN | VH | VH | VH | H | VH | NA |

LZR | VH | VH | H | M | H | VH | |

LP | VH | H | H | M | M | H | |

LPS | H | M | M | M | M | M | |

LPM | VH | H | M | M | M | M | |

LPL | NA | VH | H | M | M | M |

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**MDPI and ACS Style**

Song, B.; Lee, D.; Park, S.Y.; Baek, Y.S.
A Novel Method for Designing Motion Profiles Based on a Fuzzy Logic Algorithm Using the Hip Joint Angles of a Lower-Limb Exoskeleton Robot. *Appl. Sci.* **2020**, *10*, 6852.
https://doi.org/10.3390/app10196852

**AMA Style**

Song B, Lee D, Park SY, Baek YS.
A Novel Method for Designing Motion Profiles Based on a Fuzzy Logic Algorithm Using the Hip Joint Angles of a Lower-Limb Exoskeleton Robot. *Applied Sciences*. 2020; 10(19):6852.
https://doi.org/10.3390/app10196852

**Chicago/Turabian Style**

Song, Buchun, Dongyoung Lee, Sang Yong Park, and Yoon Su Baek.
2020. "A Novel Method for Designing Motion Profiles Based on a Fuzzy Logic Algorithm Using the Hip Joint Angles of a Lower-Limb Exoskeleton Robot" *Applied Sciences* 10, no. 19: 6852.
https://doi.org/10.3390/app10196852