Abstract:

In order to improve the flexibility of the mechanical gripper， a pressure mechanical gripper adsorption force balance control method based on the white shark optimization algorithm was proposed. The structure of the pressure mechanical gripper was divided， the axial stress and deformation of the internal cavity of the gripper was calculated， and the mechanism of action between the mechanical gripper and the object was clarified. Based on the adsorption and release states of the mechanical gripper， fully consider external influences such as vibration and airflow， the positive pressure between the adsorption target and the suction head was adjusted， and an adsorption force balance control model was output. Introducing the white shark optimization algorithm， the optimal parameters of the model were solved through initialization， position update， and optimal positioning to achieve the expected adsorption force equilibrium control goal. The experimental analysis results confirm that the proposed method's adsorption force curve is basically consistent with the optimal adsorption force curve at different angles of the mechanical gripper， controlled between 3~5 N， and stable control can be achieved within 3 seconds. The duty cycle is still higher than 0.2 at a pressure of 0.7 Pa. This method effectively improves the smoothness and accuracy of the gripper object adsorption， achieving high-quality adaptive adjustment of the gripper adsorption force.

Key words: white shark optimization algorithm, mechanical gripper, adsorption capacity, balanced control, D'Alembert theorem