Modelling And Control of Cable Driven Robotic Arm Using Maplesim

Abstract

Cable-driven robotic arms (CDRA) are robots with novel structures, wherein flexible cables are used to drive rigid links identified to move the end effector according to a desired trajectory. Due to the complex and nonlinear characteristics of this type of robotic arm, it is challenging to derive the model, which requires critical analysis to be conducted. This paper presents the design, modeling, and Model Predictive Control (MPC) of a special 2D CDRA with four rigid links. Maplesim is employed as a tool to design and simulate the proposed robotic arm. First, the prototype model is constructed in Maplesim and simulated using random input signals, and the input and output data sets are collected. A data-driven scheme based on neural networks is used to learn the unknown kinematics of the CDRA and to solve the kinematic control issue. The Matlab-Simulink platform is used for this purpose, and the black box model is obtained using the neural network fitting tool. MPC is then used for the end effector trajectory tracking control and to validate the modeling processes. Furthermore, comparative simulations using two scenarios are applied to the controlled system to verify the effectiveness of the proposed modeling and control method with the aid of Mean Squared Error (MSE) as an optimality index. The result verified that CDRA is capable of following reference trajectories accurately with MSE of 10e-5 and 4.99e-5 for rhombus and circular trajectories respectively.