The batch dyeing process is a typical nonlinear process with time-delay,where precise controlling of temperature plays a vital role on the dyeing quality.Because the accuracy and robustness of the commonly used propor...The batch dyeing process is a typical nonlinear process with time-delay,where precise controlling of temperature plays a vital role on the dyeing quality.Because the accuracy and robustness of the commonly used proportion integration differentiation(PID) algorithm had been limited,a novel method was developed to precisely control the heating and cooling stages for batch dyeing process based on predictive sliding mode control(SMC) algorithm.Firstly,a special predictive sliding mode model was constructed according to the principle of generalized predictive control(GPC);secondly,an appropriate reference trajectory for SMC was designed based on the improved approaching law;finally,the predictive sliding mode model and the Diophantine equation were used to predict the output and then the optimized control law was derived using the generalized predictive law.This method combined GPC and the SMC with their respective advantages,so it could be applied to time-delay process,making the control system more robust.Simulation experiments show that this algorithm can well track the temperature variation for the batch dyeing process.展开更多
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...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 nonlin- ear 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 guaran- teed 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, averaKe error and roughness of the nrocessed surface by 35.63%, 31.31% and 30.35%, respectively.展开更多
基金National Natural Science Foundation of China(No.61074154)
文摘The batch dyeing process is a typical nonlinear process with time-delay,where precise controlling of temperature plays a vital role on the dyeing quality.Because the accuracy and robustness of the commonly used proportion integration differentiation(PID) algorithm had been limited,a novel method was developed to precisely control the heating and cooling stages for batch dyeing process based on predictive sliding mode control(SMC) algorithm.Firstly,a special predictive sliding mode model was constructed according to the principle of generalized predictive control(GPC);secondly,an appropriate reference trajectory for SMC was designed based on the improved approaching law;finally,the predictive sliding mode model and the Diophantine equation were used to predict the output and then the optimized control law was derived using the generalized predictive law.This method combined GPC and the SMC with their respective advantages,so it could be applied to time-delay process,making the control system more robust.Simulation experiments show that this algorithm can well track the temperature variation for the batch dyeing process.
基金supported by National Science and Technology Major Project of the Ministry of Science and Technology of China (No. 2013ZX04001081)
文摘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 nonlin- ear 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 guaran- teed 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, averaKe error and roughness of the nrocessed surface by 35.63%, 31.31% and 30.35%, respectively.
