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1- Phd Student, Robotic Research Laboratory, Center of Excellence in Experimental Solid Mechanics and Dynamics, School of Mechanical Engineering, Iran University of Science and Technology, Tehran, Iran
2- Prof. Robotic Research Laboratory, Center of Excellence in Experimental Solid Mechanics and Dynamics, School of Mechanical Engineering, Iran University of Science and Technology, Tehran, Iran
3- Associate prof. Mechanical Engineering Department, Faculty of Engineering, Kharazmi University, Tehran, Iran , Tourajizadeh@khu.ac.ir
Abstract:   (92 Views)
The purpose of this paper is to optimal control a dual-stage cable robot in a predefined path and to determine the maximum load-carrying capacity of this robot as a tower crane. Also, to increase the workspace of the robot two stages are employed. Today, cable robots are extensively used in load handling. Positive cable tension and collision-free cable control are the most important challenges of this type of robot. The high ratio of transposable loads to weight makes these robots very attractive for use as tower cranes. Dynamic Load Carrying Capacity (DLCC) is the maximum load that can be carried along a predefined path without violating the actuators and allowable accuracy constraints. State-Dependent Riccati Equation (SDRE) is employed to control the end-effector within the path to achieve the maximum DLCC. This approach is chosen since it can optimize the required motors' torque which consequently leads us to the maximum DLCC. In addition, the constraint of cables’ collision together is also checked along the predetermined path using the non-interference algorithm. The correctness of modeling is verified by comparing the results with previous research and the efficiency of the proposed optimal controlling strategy toward increasing the DLCC is investigated by conducting some comparative simulations. It is shown that the proposed cable robot by the aid of the designed optimal controller can move the maximum load successfully along any desired path using the least amount of motors' torque.
 
     
Type of Study: Research | Subject: Optimization Techniques
Received: 2024/12/23 | Accepted: 2025/01/27

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