This paper presents a multivariable generalized predictive controller with proportion and integration structure by modifying the quadratic criterion of the usual MGPC. The control performance has been improved greatl...This paper presents a multivariable generalized predictive controller with proportion and integration structure by modifying the quadratic criterion of the usual MGPC. The control performance has been improved greatly. The effectiveness of the controller is demonstrated by the simulation result.展开更多
Nonlinear friction is a dominant factor afecting the control accuracy of CNC machine tools.This paper proposes a friction pre-compensation method for CNC machine tools through constructing a nonlinear model predictive...Nonlinear friction is a dominant factor afecting the control accuracy of CNC machine tools.This paper proposes a friction pre-compensation method for CNC machine tools through constructing a nonlinear model predictive scheme.The nonlinear friction-induced tracking error is frstly modeled and then utilized to establish the nonlinear model predictive scheme,which is subsequently used to optimize the compensation signal by treating the friction-induced tracking error as the optimization objective.During the optimization procedure,the derivative of compensation signal is constrained to avoid vibration of machine tools.In contrast to other existing approaches,the proposed method only needs the parameters of Stribeck friction model and an additional tuning parameter,while fnely identifying the parameters related to the pre-sliding phenomenon is not required.As a result,it greatly facilitates the practical applicability.Both air cutting and real cutting experiments conducted on an in-house developed open-architecture CNC machine tool prove that the proposed method can reduce the tracking errors by more than 56%,and reduce the contour errors by more than 50%.展开更多
The dividing wall column （DWC） is considered as a major breakthrough in distillation technology and has good prospect of industrialization. Model predictive control （MPC） is an advanced control strategy that has a...The dividing wall column （DWC） is considered as a major breakthrough in distillation technology and has good prospect of industrialization. Model predictive control （MPC） is an advanced control strategy that has acquired extensive applications in various industries. In this study, MPC is applied to the process for separating ethanol, n-propanol, and n-butanol ternary mixture in a fully thermally coupled DWC. Both composition control and tem- perature inferent/al control are considered. The multiobjective genetic algor/thm function ＂gamult/obj＂ in Matlab is used for the weight tuning of MPC. Comparisons are made between the control performances of MPC and PI strategies. Simulation results show that although both MPC and PI schemes can stabilize the DWC in case of feed disturbances, MPC generally behaves better than the PI strategy for both composition control and tempera- ture inferential control, resulting in a more stable and superior performance with lower values of integral of squared error （ISE）.展开更多
The variation of plant dead-time deeply a?ects the stability of the predictive PI controlsystem. It is important for designing and applying the PPI controller to calculate the delay margin.A criterion of stability for...The variation of plant dead-time deeply a?ects the stability of the predictive PI controlsystem. It is important for designing and applying the PPI controller to calculate the delay margin.A criterion of stability for the PPI system and the quantitive relationship among the delay margin,the time constant of the closed-loop system, and the dead-time of the model are given. A graphicalgorithm to compute the delay margin is also developed. The phenomenon that there exist morethan one stability delay zones is discussed. The algorithm is shown to be precise by some simulations.展开更多
文摘This paper presents a multivariable generalized predictive controller with proportion and integration structure by modifying the quadratic criterion of the usual MGPC. The control performance has been improved greatly. The effectiveness of the controller is demonstrated by the simulation result.
基金Supported by National Natural Science Foundation of China(Grant No.51975481)Fundamental Research Funds for the Central Universities of China(Grant No.D5000220061).
文摘Nonlinear friction is a dominant factor afecting the control accuracy of CNC machine tools.This paper proposes a friction pre-compensation method for CNC machine tools through constructing a nonlinear model predictive scheme.The nonlinear friction-induced tracking error is frstly modeled and then utilized to establish the nonlinear model predictive scheme,which is subsequently used to optimize the compensation signal by treating the friction-induced tracking error as the optimization objective.During the optimization procedure,the derivative of compensation signal is constrained to avoid vibration of machine tools.In contrast to other existing approaches,the proposed method only needs the parameters of Stribeck friction model and an additional tuning parameter,while fnely identifying the parameters related to the pre-sliding phenomenon is not required.As a result,it greatly facilitates the practical applicability.Both air cutting and real cutting experiments conducted on an in-house developed open-architecture CNC machine tool prove that the proposed method can reduce the tracking errors by more than 56%,and reduce the contour errors by more than 50%.
基金Supported by the National Natural Science Foundation of China(21676299,21476261and 21606255)
文摘The dividing wall column （DWC） is considered as a major breakthrough in distillation technology and has good prospect of industrialization. Model predictive control （MPC） is an advanced control strategy that has acquired extensive applications in various industries. In this study, MPC is applied to the process for separating ethanol, n-propanol, and n-butanol ternary mixture in a fully thermally coupled DWC. Both composition control and tem- perature inferent/al control are considered. The multiobjective genetic algor/thm function ＂gamult/obj＂ in Matlab is used for the weight tuning of MPC. Comparisons are made between the control performances of MPC and PI strategies. Simulation results show that although both MPC and PI schemes can stabilize the DWC in case of feed disturbances, MPC generally behaves better than the PI strategy for both composition control and tempera- ture inferential control, resulting in a more stable and superior performance with lower values of integral of squared error （ISE）.
文摘The variation of plant dead-time deeply a?ects the stability of the predictive PI controlsystem. It is important for designing and applying the PPI controller to calculate the delay margin.A criterion of stability for the PPI system and the quantitive relationship among the delay margin,the time constant of the closed-loop system, and the dead-time of the model are given. A graphicalgorithm to compute the delay margin is also developed. The phenomenon that there exist morethan one stability delay zones is discussed. The algorithm is shown to be precise by some simulations.
