Abstract
In this paper, two algorithms are performed to find an optimum design of a six-degree-of-freedom Stewart platform to provide a desired pure rotational motion required in the robotic rehabilitation of the foot for patients with neuropathy. To accomplish this, first, we present the kinematic and the dynamic analysis of the Stewart platform. The dynamic equations are derived by using a customized Lagrange method. Then, physically meaningful objective variables are defined such as the size of the platform, the length of the six links, the maximum stroke of the six linear actuators, the maximum actuator force, and the reachable workspace. This is followed by using two optimization methods (Genetic Algorithm and Monte-Carlo method) to study the aforementioned objective variables, resulting in the optimal solution for the desired orientation motions. Then, the detailed investigation of the effect of changes in these objective variables on the variation of the platform design variables is studied. Finally, in a numerical example, the advantages and disadvantages of using the Genetic Algorithm and the Monte-Carlo method to find the optimal design variables for a custom cost function with weighted objective variables are revealed.
| Language | English (US) |
|---|---|
| Title of host publication | 2017 American Control Conference, ACC 2017 |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Pages | 5294-5299 |
| Number of pages | 6 |
| ISBN (Electronic) | 9781509059928 |
| DOIs | |
| State | Published - Jun 29 2017 |
| Event | 2017 American Control Conference, ACC 2017 - Seattle, United States Duration: May 24 2017 → May 26 2017 |
Other
| Other | 2017 American Control Conference, ACC 2017 |
|---|---|
| Country | United States |
| City | Seattle |
| Period | 5/24/17 → 5/26/17 |
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ASJC Scopus subject areas
- Electrical and Electronic Engineering
Cite this
An optimal Stewart platform for lower extremity robotic rehabilitation. / Dabiri, Arman; Sabet, Sahand; Poursina, Mohammad; Armstrong, David G.; Nikravesh, Parviz E.
2017 American Control Conference, ACC 2017. Institute of Electrical and Electronics Engineers Inc., 2017. p. 5294-5299 7963777.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - An optimal Stewart platform for lower extremity robotic rehabilitation
AU - Dabiri,Arman
AU - Sabet,Sahand
AU - Poursina,Mohammad
AU - Armstrong,David G.
AU - Nikravesh,Parviz E.
PY - 2017/6/29
Y1 - 2017/6/29
N2 - In this paper, two algorithms are performed to find an optimum design of a six-degree-of-freedom Stewart platform to provide a desired pure rotational motion required in the robotic rehabilitation of the foot for patients with neuropathy. To accomplish this, first, we present the kinematic and the dynamic analysis of the Stewart platform. The dynamic equations are derived by using a customized Lagrange method. Then, physically meaningful objective variables are defined such as the size of the platform, the length of the six links, the maximum stroke of the six linear actuators, the maximum actuator force, and the reachable workspace. This is followed by using two optimization methods (Genetic Algorithm and Monte-Carlo method) to study the aforementioned objective variables, resulting in the optimal solution for the desired orientation motions. Then, the detailed investigation of the effect of changes in these objective variables on the variation of the platform design variables is studied. Finally, in a numerical example, the advantages and disadvantages of using the Genetic Algorithm and the Monte-Carlo method to find the optimal design variables for a custom cost function with weighted objective variables are revealed.
AB - In this paper, two algorithms are performed to find an optimum design of a six-degree-of-freedom Stewart platform to provide a desired pure rotational motion required in the robotic rehabilitation of the foot for patients with neuropathy. To accomplish this, first, we present the kinematic and the dynamic analysis of the Stewart platform. The dynamic equations are derived by using a customized Lagrange method. Then, physically meaningful objective variables are defined such as the size of the platform, the length of the six links, the maximum stroke of the six linear actuators, the maximum actuator force, and the reachable workspace. This is followed by using two optimization methods (Genetic Algorithm and Monte-Carlo method) to study the aforementioned objective variables, resulting in the optimal solution for the desired orientation motions. Then, the detailed investigation of the effect of changes in these objective variables on the variation of the platform design variables is studied. Finally, in a numerical example, the advantages and disadvantages of using the Genetic Algorithm and the Monte-Carlo method to find the optimal design variables for a custom cost function with weighted objective variables are revealed.
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U2 - 10.23919/ACC.2017.7963777
DO - 10.23919/ACC.2017.7963777
M3 - Conference contribution
SP - 5294
EP - 5299
BT - 2017 American Control Conference, ACC 2017
PB - Institute of Electrical and Electronics Engineers Inc.
ER -