Abstract
Cable-Driven Parallel Robot has many advantages. However, the problems of cable collision between each other and environment, the lack of proper structure and non-positive cable tension prevent the spread of them. In this work, a neural network (NN) model of under constrained cable robots is presented with external forces applied to the end-effector (EE) for computing the position of it. As in under-constrained robot’s kinematics and statics are innately coupled together, and they contemporaneously should be considered the forward kinematic problem of the robot change to an optimization problem. This approach does not require pre-knowledge of the uncertainties upper bounds and linear regression form of kinematic and dynamic models. Moreover, to ensure that all cables remain in tension, proposed control algorithm benefit the internal force concept in its structure. The main contribution of this paper has three goals. First, a method is used toward kinematic problem of the under constrained cable robot modeling using four bar linkage kinematic concept, which could be used in online control approaches for real-time purposes. Second, in order to track the position of end-effector, an online PD controller is designed by the three error criteria methods such as IAE, ISE and ITSE. Finally, as the third contribution, NN control approach is applied in order to validate the model. A model is created based on the robot’s geometry and dynamic to solve the forward kinematics problem. So, the forward kinematic problem is solved offline and used online. Moreover, an analysis of workspace is performed which discovers that the solution of the forward kinematic problem of the under-constrained cable robots is unique in this case. In addition, a modified local linear model tree algorithm for nonlinear system modelling are proposed. The results show the effectiveness of the proposed approach in modeling the under constrained cable robot.
Highlights
The first generation of current industrial robots is formed by connecting rigid arms with multiple joints in succession
In order to find the end-effector position of under constrained robots at any moment and the use of it in the control algorithms, a method based on neural network algorithms was proposed
This paper has introduced a new algorithm for position control of end-effector, it is a PD-type controller
Summary
The first generation of current industrial robots is formed by connecting rigid arms with multiple joints in succession. Yeol et al [8] proposed a method to solve the forward kinematics of an under constrained cable driven robot This solution is obtained by finding all balancing situations, similar to rigid four-bar robots. To find the position of the robot, the robot forward kinematic become optimized a question of balance, which aims to minimize the potential energy of end-effector (find the lowest height of the center of mass of the end-effector with the specified cable lengths) and the balance of forces at any moment This can be conducted using optimization methods such as genetic algorithms or the consideration of changes to variables using convex optimization of analysis and so on. In order to ensure this method, the information of trained neural network is used in a control algorithm to control robot position and result is given for a 4 cable driven spatial robot
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