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Modeling of Biological Cells with Applications to the Design of a Nano-Micro Gripper Used in Cell Manipulation

Abbasi, Ali Asghar | 2011

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  1. Type of Document: M.Sc. Thesis
  2. Language: Farsi
  3. Document No: 42051 (08)
  4. University: Sharif University of Technology
  5. Department: Mechanical Engineering
  6. Advisor(s): Ahmadian, Mohammad Taghi; Vossoughi, Golamreza
  7. Abstract:
  8. Grasping and manipulation of biological cells have an extensive applications in genetics ,cell proliferation ,cell injection and etc. In robotic manipulation ,it is often assumed that the objects being handled are rigid and only small deformations occurred during manipulation. this does not apply for the case of biological cells. biological cells are highly deformable structures, and their material properties are not well quantified. Therefore strategies for characterizing and manipulating of such deformable objects needs to develop. Different experimental techniques have recently been used and devised to study biological cells. On the one hand, although this experimental techniques have been significant influence on biological cell studying , but they have problems such as difficult implementation ,poor controllability ,high cost ,etc. On the other hand, in some cases ,it is reported that using different mechanical models for the same type of cells , have led to differing mechanical properties. For example in studying of neutrophils, derived mechanical properties using the Newtonian liquid drop model and the Maxwell model are different. Another methods which usually used in cell indentation experiments are the contact mechanics models including the Hertzian model and Sneddon model. These models cannot be used in the cases that large deformations (such as this study) are considered because large deformation violate the small deformation assumption of the contact mechanics models. Hence, the objectives of this research are modeling of biological cells and presenting a suitable force control for grasping and manipulating of them. Therefore the results of this reports can be summarized to three general parts as follows: first, modeling of biological cells. second, analyzing and extending a previously developed nano-micro gripper and third, designing a suitable force controller for the nano-micro gripper. Three models have been suggested for biological cells modeling. First model is making use of artificial neural networks. Second model is applying Adaptive neural fuzzy inference technique for biological cell modeling and third method is employing inverse finite element method together with Levenberg-Marquardt optimization algorithm. third modeling approach assumes that the constitutive material of cell is homogeneous, isotropic , incompressible and hyper elastic solid. This modeling have been done in finite element software, Abaqus standard. Also its connected optimization algorithm has been implemented in Matlab software. The results of biological cells modeling have been compared with experimental observations which captured from literatures .In analysis and extension part of nano-micro gripper , a nano-micro gripper which previously developed by researchers of Toronto university have been analyzed and extended. The controller design part, also designs a simple and effective PID force control for nano-micro gripper and considers its interaction with biological cell. Results of simulations more evident the effectiveness of implemented models and controller.
  9. Keywords:
  10. Neural Network ; Levenberg-Marquardt Equation ; Adaptive Neuro-Fuzzy Inference System (ANFIS) ; Inverse Finite Element Method ; Biological Cells ; Nano-Micro Grippers

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