<p>To enhance the trajectory tracking performance of a cooperative robotic manipulator based on harmonic drive under high-speed variable load conditions, a novel adaptive nonsingular fast terminal sliding mode (ANFTSM) trajectory tracking control method with model feedforward compensation is proposed. Firstly, a new model feedforward compensation method is introduced to enable real-time estimation and compensation of disturbances, which consists of load torque estimation compensation based on an improved harmonic drive compliance model and friction compensation based on a hybrid friction model. Secondly, a novel ANFTSM surface is proposed to accelerate the convergence speed. Then, the model feedforward compensation is combined with the ANFTSM control, which effectively reduces the dependency on the upper bound of uncertainty disturbances and minimizes chattering, and the algorithm is proved to be able to converge in finite time by Lyapunov stability theory. Finally, comparative experiments under various operating conditions validate that the proposed algorithm significantly improves the trajectory tracking accuracy of the robotic manipulator under high-speed variable load conditions, while also exhibiting better robustness to changes in operating conditions.</p>

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Adaptive nonsingular fast terminal sliding mode trajectory tracking control for robotic manipulators with model feedforward compensation

  • Shunjing Hu,
  • Yi Wan,
  • Xichang Liang

摘要

To enhance the trajectory tracking performance of a cooperative robotic manipulator based on harmonic drive under high-speed variable load conditions, a novel adaptive nonsingular fast terminal sliding mode (ANFTSM) trajectory tracking control method with model feedforward compensation is proposed. Firstly, a new model feedforward compensation method is introduced to enable real-time estimation and compensation of disturbances, which consists of load torque estimation compensation based on an improved harmonic drive compliance model and friction compensation based on a hybrid friction model. Secondly, a novel ANFTSM surface is proposed to accelerate the convergence speed. Then, the model feedforward compensation is combined with the ANFTSM control, which effectively reduces the dependency on the upper bound of uncertainty disturbances and minimizes chattering, and the algorithm is proved to be able to converge in finite time by Lyapunov stability theory. Finally, comparative experiments under various operating conditions validate that the proposed algorithm significantly improves the trajectory tracking accuracy of the robotic manipulator under high-speed variable load conditions, while also exhibiting better robustness to changes in operating conditions.