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A Comparative Study of Adaptive Sliding Mode Control for Biodynamic Vibration Suppression in a 5-DOF Artificial Human Arm | ||
| Kerbala Journal for Engineering Sciences (KJES) | ||
| Volume 6, Issue 1, March 2026, Pages 89-107 PDF (1.72 M) | ||
| Document Type: Research Article | ||
| DOI: 10.63463/kjes1225 | ||
| Authors | ||
| Oula M. H. Fatla* ; Muhammed Abdelhameed | ||
| Department of Mechanical Engineering, College of Engineering, Gulf University, Sanad 26489, Kingdom of Bahrain. | ||
| Abstract | ||
| The present work presents the dynamic modeling and nonlinear control of a 5-DOF artificial human arm, which can efficiently replicate human upper limb movements. A control-oriented 5-DOF rigid-body dynamic model was formulated by employing the Euler-Lagrange equation, which considers inertia, centrifugal, and gravitational forces. A total of four control approaches, namely Proportional-Derivative Control (PD), Computed Torque Control (CTC), Linear Quadratic Regulator (LQR), and Adaptive Sliding Mode Control (ASMC), were proposed and analyzed for their trajectory tracking abilities. Lyapunov stability theory was used to validate the convergence of the ASMC and CTC control approaches, whereas the optimal control gains were calculated for the LQR control approach by linearizing the state-space model. The simulation outcomes demonstrated that the ASMC control approach provides the highest level of trajectory tracking accuracy with an RMS error of 0.012 rad, compared to other control approaches such as CTC (0.041 rad), LQR (0.056 rad), and PD control (0.084 rad). The ASMC control strategy was found to have the fastest settling time of 0.78 s and the smallest overshoot of 2.1%, which confirms its robustness against parametric uncertainties. However, it is achieved at the expense of an increased control effort, with an average torque norm of 15.5 Nm, whereas the PD method requires the least control energy (6.2 Nm) but has poor accuracy. These results have demonstrated the effectiveness of nonlinear robust control, especially ASMC, in improving the tracking capability of bio-inspired robotic manipulators. | ||
| Keywords | ||
| Adaptive Sliding Mode Control; Biodynamic Vibration; Robust Control; Disturbance | ||
| References | ||
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