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As a key assembly in the 5-axis CNC machine tools, positioning precision of the A-axis directly affects the machining accuracy and surface quality of the parts. First of all, mechanical structure and control system of the A-axis are designed. Then, considering the influence of nonlinear friction, backlash, unmodeled dynamics, uncertain cutting force and other external disturbance on the control precision of the A-axis, an adaptive sliding mode control(ASMC) based on extended state observer(ESO) is proposed. ESO is employed to estimate the state variables of the unknown system and an adaptive law is adopted to compensate for the input dead-zone caused by friction,backlash and other nonlinear characteristics. Finally, stability of the closed-loop system is guaranteed by the Lyapunov theory. Positioning experiments illustrate the perfect estimation of ESO and the stronger anti-interference and robustness of ASMC, which can improve the control precision of the A-axis by about 40 times. Processing experiments show that the ASMC can reduce the waviness,average error and roughness of the processed surface by 35.63%, 31.31% and 30.35%, respectively.
As a key assembly in the 5-axis CNC machine tools, positioning precision of the A-axis directly affects the machining accuracy and surface quality of the parts. , considering the influence of nonlinear friction, backlash, unmodeled dynamics, uncertainty cutting force and other external disturbance on the control precision of the A-axis, an adaptive sliding mode control (ASMC) based on extended state observer (ESO) is proposed. is employed to estimate the state variables of the unknown system and an adaptive law is adopted to compensate for the input dead-zone caused by friction, backlash and other nonlinear characteristics. Finally, stability of the closed-loop system is guaranteed by the Lyapunov theory . Positioning experiments illustrate the perfect estimation of ESO and the stronger anti-interference and robustness of ASMC, which can improve the control precision of the A-axis by about 40 times. Pro cessing experiments show that the ASMC can reduce the waviness, average error and roughness of the processed surface by 35.63%, 31.31% and 30.35%, respectively.