Optimization of adaptive control of a robotic manipulator with 8 degrees of freedom

This study presents an adaptive control system for an eight-degree-of-freedom robotic manipulator, aimed at resolving persistent challenges in controlling high-degree-of-freedom systems, such as computational complexity, parameter convergence, and ensuring stability under dynamic uncertainties. The controller is designed based on a Lyapunov approach, enabling real-time estimation of the system’s unknown parameters and ensuring accurate tracking of a desired trajectory. Numerical experiments conducted in the MATLAB environment demonstrate the superiority of the proposed adaptive controller over benchmark methods. The results show a 97 % improvement in Root Mean Square Error compared to Model Predictive Control (MPC) and a 95.5 % improvement compared to the Kalman filter-based method, along with a significant reduction in settling time, rise time, and steady-state error. The obtained data convincingly confirms that the proposed adaptive control method is a robust and highly effective solution for optimizing complex robotic systems with a high number of degrees of freedom.
EDN: BHABQM, https://elibrary/bhabqm

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