Bat Optimization of Hybrid Neural Network-FOPID Controllers for Robust Robot Manipulator Control

Bashra Kadhim Oleiwi ¹ Mohamed Mohamed ¹ Ahmad Taher Azar ^2,3,4* Saim Ahmed ^2,3 Ibrahim A Hameed ^5*

• ¹ University of Technology, Iraq, Baghdad, Baghdad, Iraq
• ² College of Computer and Information Sciences, Prince Sultan University, Riyadh, Saudi Arabia
• ³ Automated Systems and Soft Computing Lab (ASSCL), Prince Sultan University, Riyadh, Saudi Arabia
• ⁴ Faculty of Computer and Artificial Intelligence, Benha University, Benha, Egypt
• ⁵ Norwegian University of Life Sciences, As, Akershus, Norway

The position and trajectory tracking control of rigid links robot manipulator suffers from problems such as poor accuracy, unstable performance, and response caused by unidentified loads and outside disturbances. In this paper, three control structures have been proposed to control a multi-input, multi-output coupled, a nonlinear three-link Rigid Robot Manipulator (3-LRRM) system and effectively solve the signal chattering in the control signal. In this paper, to overcome these problems, three hybrid control structures based on combinations between the benefits of Fractional Order Proportional, Integral, and Derivative operations (FOPID) and the benefits of neural networks are proposed for a 3-LRRM. The first hybrid control scheme is a neural-network (NN) like Fractional-Order Proportional Integral plus NN like Fractional Order Proportional Derivative controller (NN-FOPIPD), the second control scheme is NN plus FOPID Controller (NN+FOPID). In contrast, the third control scheme is Elman NN like FOPID controller (ELNN-FOPID). Bat Optimization Algorithm (BOA) is applied to find the best parameter values of the proposed control scheme by minimizing the performance index of the Integral Time Square Error (ITSE). MATLAB software is used to carry out the simulation results. Using the simulation tests, the performance of the suggested controllers is compared without retraining the controller parameters. The robustness of the designed control schemes' performance is assessed utilizing uncertainties in system parameters, outside disturbances, and initial position changes. The results show how beneficial and successful the suggested NN-FOPIPD control strategy was, where the NN-FOPIPD structure demonstrated the best performance among the suggested controllers.