Brain Emotional Learning based Intelligent Controller for a Cable-Driven Parallel Robot

Concerning the lack of knowledge about non- linearity and uncertainties existing in the cable-driven robot models, an intelligent controller is proposed in this paper to overcome the lack of knowledge. Brain Emotional Learning is one of the bio-inspired algorithms which mimics the emotional part of the mammals’ brain. Not only does the Brain Emotional Learning Based Intelligent Controller (BELBIC) enable us to reach quick adaptation and robustness, but the computations are also very efficient. By defining the BELBIC learning functions with saturation functions, it is shown that the need to calculate the Jacobian matrix and forward kinematics in the feedback loop is eliminated, while guaranteeing positive tensions to the robot. The performance of the proposed method is examined by experiments, and results show that BELBIC can perform well in terms of tracking error.