Neural Adaptive Nonlinear MIMO Control for Bipedal Walking Robot Locomotion in Hazardous and Complex Task Applications

Bekhiti, Belkacem; Iqbal, Jamshed; Hariche, Kamel; Fragulis, George

Abstract

This paper introduces a robust neural adaptive MIMO control strategy to improve the stability and adaptability of bipedal locomotion amid uncertainties and external disturbances. The control combines nonlinear dynamic inversion, finite-time convergence, and radial basis function (RBF) neural networks for fast, accurate trajectory tracking. The main novelty of the presented control strategy lies in unifying instantaneous feedback, real-time learning, and dynamic adaptation within a multivariable feedback framework, delivering superior robustness, precision, and real-time performance under extreme conditions. The control scheme is implemented on a 5-DOF underactuated RABBIT robot using a dSPACE DS1103 platform with a sampling rate of ∆t=1.5 ms (667 Hz). The experimental results show excellent performance with the following: The robot achieved stable cyclic gaits while keeping the tracking error within e=±0.04 rad under nominal conditions. Under severe uncertainties of trunk mass variations ∆mtrunk=+100%, limb inertia changes ∆Ilimb=±30%, and actuator torque saturation at τ=±150 Nm, the robot maintains stable limit cycles with smooth control. The performance of the proposed controller is compared with classical nonlinear decoupling, non-adaptive finite-time, neural-fuzzy learning, and deep learning controls. The results demonstrate that the proposed method outperforms the four benchmark strategies, achieving the lowest errors and fastest convergence with the following: IAE=1.36, ITAE=2.43, ISE=0.68, tss=1.24 s, and Mp=2.21%. These results demonstrate evidence of high stability, rapid convergence, and robustness to disturbances and foot-slip.

Citation

Bekhiti, . B., Iqbal, J., Hariche, K., & Fragulis, G. (2025). Neural Adaptive Nonlinear MIMO Control for Bipedal Walking Robot Locomotion in Hazardous and Complex Task Applications. Robotics, 14(6), Article 84. https://doi.org/10.3390/robotics14060084

• Journal Article Type: Article
• Acceptance Date: Jun 12, 2025
• Online Publication Date: Jun 17, 2025
• Publication Date: Jun 1, 2025
• Deposit Date: Jun 17, 2025
• Publicly Available Date: Jun 17, 2025
• Journal: Robotics
• Electronic ISSN: 2218-6581
• Publisher: MDPI
• Peer Reviewed: Peer Reviewed
• Volume: 14
• Issue: 6
• Article Number: 84
• DOI: https://doi.org/10.3390/robotics14060084
• Keywords: neural adaptive control; MIMO control; RABBIT robot; robust tracking; bipedal walking robot
• Public URL: https://hull-repository.worktribe.com/output/5240120