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Data-Driven Modeling and Control of a Two-Link Flexible Manipulator (TLFM)

Two-link flexible manipulators (TLFMs) are used in different application domains, and their merits include lightweight, low energy consumption, high operational speed, transportability, maneuverability, and low cost. Despite the merits of TLFMs, the flexibility of the links introduces modeling and c...

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Bibliographic Details
Main Author: Ayankoso, Samuel
Format: Thesis
Published: AUC Knowledge Fountain 2021
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Summary:Two-link flexible manipulators (TLFMs) are used in different application domains, and their merits include lightweight, low energy consumption, high operational speed, transportability, maneuverability, and low cost. Despite the merits of TLFMs, the flexibility of the links introduces modeling and control problems. The existing mathematical modeling techniques of a TLFM, such as the assumed mode method (AMM), finite element method (FEM) and finite difference method (FDM are mathematically complex and do not accurately match the physical system dynamics. Lumped parameter method (LPM) model is a simplified model, but it is also inaccurate. Moreover, different forms of control problems are applicable to TLFM; these include link position control, deflection suppression, trajectory tracking control and force control. This thesis focuses on investigating and formulating the existing LPM and AMM models of a TLFM and the development of linear and nonlinear data-driven models. Then, four controllers are used, namely proportional-integral-derivative (PID) control, linear quadratic regulator (LQR) control, fuzzy logic control (FLC) and adaptive sliding mode control (ASMC), to handle the position control and deflection suppression of the links. The controllers are simulated with different TLFM models, and they are also implemented experimentally on Quanser TLFM. The relative performance of the control techniques in both position control and deflection reduction are analyzed through a comparative study. Besides, the controllers are tested in terms of polynomial trajectory tracking and robustness to the disturbances added to the system.