Dynamic load carrying capacity of mobile-base flexible-link manipulators: feedback linearization control approach

Korayem, M. H.; Firouzy, Sina; Heidari, Amir

doi:10.1109/robio.2007.4522506

Cited by 13 publications

(5 citation statements)

References 4 publications

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“…Mobile manipulators have gained extensive attention during the last decades due to their improved maneuverability and reduced power consumption over their rigid counterparts [1]. Interaction with environment is a main application for the mobile manipulators.…”

Section: Introductionmentioning

confidence: 99%

A Case Study: Modeling of A Passive Flexible Link on A Floating Platform for Intervention Tasks

Wang

Liu

2018

2018 13th World Congress on Intelligent Control and Automation (WCICA)

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Section: Introductionmentioning

confidence: 99%

A Case Study: Modeling of A Passive Flexible Link on A Floating Platform for Intervention Tasks

Wang

Liu

2018

2018 13th World Congress on Intelligent Control and Automation (WCICA)

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“…In this study, the maximum load neighbourhood robot configurations have been investigated, and some techniques to increase the carrying capacity of the cooperative system have been developed. In order to apply this algorithm, two important factors should be considered: first, the maximum torques that can be generated by motors and, second, the maximum acceptable bounds of errors within which the endeffector is permitted to move (Korayem et al, 2007). The required constraints can be easily satisfied by the aid of our proposed iterative algorithm in this paper.…”

Section: Introductionmentioning

confidence: 99%

Robust optimal motion planning approach to cooperative grasping and transporting using multiple UAVs based on SDRE

Babaie

Ehyaie

2016

Transactions of the Institute of Measurement and Control

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In this paper, we consider the problem of controlling a team of Quadrotors that cooperatively grasp and transport a common payload in three dimensions in the presence of external disturbances and parametric uncertainties such as wind field effects. The main contribution of this work is to propose a cooperative control algorithm based on a decentralized strategy. This algorithm consists of two main parts: first calculating the control vectors for each Quadrotor using Moore-Penrose theory and second combining these control vectors with individual control vectors, which are obtained from a closed-loop non-linear robust optimal controller. In this regard, a robust optimal sliding mode controller (ROSMC), which incorporates the statedependent Riccati equation (SDRE) method with sliding mode control (SMC) technique, is designed. It also has the capability of maximum dynamic load carrying capacity (DLCC) to increase the carrying capacity and the efficiency of the group of Quadrotors. The proposed method inherits the advantages of both approaches including robustness against model uncertainties and high flexibility in designing the control parameters to provide an optimal solution for the non-linear dynamic of the system. The control algorithm is based on the Lyapunov technique, which is able to provide the stability of the end-effecter during tracking of the desired trajectory with acceptable precision. Finally, the simulation results demonstrate the effectiveness of the control strategy for the cooperative Quadrotors to grasp and transport a common payload in various manoeuvres.

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“…In ref. [18], the DLCC of a flexible planar mobile manipulator has been calculated using FL method. Korayem et al 19 have used a controller that is divided into two parts: partial FL and SMC.…”

Section: Introductionmentioning

confidence: 99%

Maximum load of flexible joint manipulators using nonlinear controllers

et al. 2015

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SUMMARYThe main innovation of this paper is determining the dynamic load carrying capacity (DLCC) of a flexible joint manipulator (FJM) using a closed form nonlinear optimal control approach. The proposed method is compared with two closed loop nonlinear methods that are usually applied to robotic systems. As a new idea, DLCC of the manipulator is considered as a criterion to compare how well controllers perform point to point mission for the FJMs. The proposed method is compared with feedback linearization (FL) and robust sliding mode control (SMC) methods to show better performance of proposed nonlinear optimal control approach. An optimal controller is designed by solving a nonlinear partial differential equation named the Hamilton–Jacobi–Bellman (HJB) equation. This equation is complicated to solve exactly for complex dynamics so it is solved numerically using an iterative approximation combined with the Galerkin method. In the FL method, angular position, velocity, acceleration and jerk of links are considered as new states to linearize the dynamic equations. In the case of SMC, the dynamic equations of manipulator are changed to the standard form then the Slotine method is used to design the sliding mode controller. Two simulations are performed for a planar and a spatial Puma manipulator and performances of controllers are compared. Finally an experimental test is done on 6R manipulator and the Stereo vision method is used to determine the position and orientation of the end-effector.

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Dynamic load carrying capacity of mobile-base flexible-link manipulators: feedback linearization control approach

Cited by 13 publications

References 4 publications

A Case Study: Modeling of A Passive Flexible Link on A Floating Platform for Intervention Tasks

A Case Study: Modeling of A Passive Flexible Link on A Floating Platform for Intervention Tasks

Robust optimal motion planning approach to cooperative grasping and transporting using multiple UAVs based on SDRE

Maximum load of flexible joint manipulators using nonlinear controllers

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