K.N. Toosi University of Technology International Journal of Robotics, Theory and Applications 2008-7144 9 1 2023 05 01 Model-Free Joint Space Controller for Fully-Constrained Cable-Driven Parallel Robots: a Bio-Inspired Algorithm 11 19 178828 EN Mohammad Bajelani Advanced Robotics and Automated Systems (ARAS), Faculty of Electrical Engineering K. N. Toosi University of Technology, Tehran, Iran. 0000-0002-0414-2677 S. Ahmad Khalilpour Advanced Robotics and Automated Systems (ARAS), Faculty of Electrical Engineering K. N. Toosi University of Technology, Tehran, Iran. M. Isaac Hosseini Advanced Robotics and Automated Systems (ARAS), Faculty of Electrical Engineering K. N. Toosi University of Technology, Tehran, Iran. Hamid D. Taghirad Advanced Robotics and Automated Systems (ARAS), Faculty of Electrical Engineering K. N. Toosi University of Technology, Tehran, Iran. 0000-0002-0615-6730 Philippe Cardou Department of Mechanical Engineering, Robotics Laboratory, Laval University Journal Article 2022 06 20 Due to the complex model of cables, non-linearity, and uncertainties that exist in Cable-Driven Parallel Robots (CDPRs), this paper proposes a bio-inspired intelligent approach to overcome these challenges. This method, Brain Emotional Learning (BEL), mimics the emotional aspect of the mammal brain. Because of its easy-to-implement mathematical model, the Brain Emotional Learning-Based Intelligent Controller (BELBIC) brings fast adaptation, robustness, and low computational cost. The core idea of this paper is to define new saturated learning functions that eliminate the necessity of calculating the Jacobian matrix and forward kinematics in the control loop while still ensuring positive tensions. To evaluate the effectiveness of the proposed method, an experimental study was conducted using a plotter CDPR. The experimental results indicate that BELBIC can be adopted as a new approach in the trajectory tracking problem in the context of CDPRs, as it provides an acceptable tracking error (less than 10 degrees) without using the Jacobian matrix in the feedback loop. https://ijr.kntu.ac.ir/article_178828_40430f9cb39b93ef6f499080c8a3d829.pdf