| In the background of the increasing demand for high precision,high velocity and high efficiency in high-end precision manufacturing,the direct drive XY motion platform has become the main functional component of the direct drive transmission system,where the advantage of simple mechanical structure is favorable to obtain the direct drive characteristics.Therefore,it is widely used in advanced manufacturing industries such as optical inspection systems,3D printing,semiconductor processing,and multi-axis CNC machine tools.Limited by the lag characteristics of servo systems and dynamics incompatibility,however,when the system processes complex contour tasks such as high velocity,large curvature and sharp corners,the methods of approximately establishing contouring errors only consider the tracking error of single-axis obviously cannot meet the processing requirements of multi-axis linkage control for motion coordination.When the control systems execute contouring tasks,uncertainties such as external disturbances,parameter variations,nonlinear friction,measurement noise,and unmodeled dynamics become the main factors that affect the stable operation of the system,and further increase the difficulty to control the system.Therefore,under the joint influence of motion coordination and uncertainty,the thorough research on contouring control scheme is of great significance to improve the theoretical guidance and practical application in the field of high-precision manufacturing.This dissertation takes the direct drive XY motion platform as the research object and proposes a design of contouring control scheme with equal emphasis on the coordination controller and motion controller.Based on the construction of the contour error model,the Newton extremum search algorithm is used to achieve a dynamic contouring error estimation.A coordination controller is established combined with the adaptive iterative learning controller(AILC)to realize the coordinated motion of the system.The influence of nonlinear uncertainty in the system is suppressed by the combination of adaptive jerk controller(AJC)and neural networks.Then,a continuous control law is designed,and the convergence of the control scheme is analyzed to achieve high-precision contouring tracking control in finite time.The main research contents of this dissertation are shown as follows:(1)The basic structure of the direct drive XY motion platform is introduced.The dynamic models such as the voltage equation,the flux linkage equation,and the electromagnetic thrust equation of the direct drive XY motion platform servo systems are described and derived.The controlled object is regarded as a second-order nonlinear system,and then the mechanical motion equation with uncertainty is established.The main factors affecting the control performance and contouring error of the system are analyzed in detail,which provides a theoretical basis for further guidance and the proposed contouring control scheme.(2)The problem that contouring error cannot be accurately established when machining complex contours such as high velocity,large curvature and sharp corners,is studied.A Newton extremum search algorithm is designed to achieve the dynamic contouring error estimation.Firstly,it is analyzed that the contour error is related to the shape of the reference contour.The shortest distance from the actual position to the reference contour is defined to measure the contouring error.Based on this,a cost function is established,and thus the establishment of various contouring errors is unified as a cost function minimization problem.Then,the Newton algorithm is used to optimize and solve the minimum value of the cost function.The contour error analysis is improved from a static first-order estimation to a dynamic second-order estimation.The improvement has been made in the accuracy and convergence rate of the contour error model,which is not only suitable for simple linear contours,but can also be regularly extended to complex contours such as high velocity,large curvature and sharp corners.Meanwhile,a sliding mode controller is designed to suppress the uncertainty in a nonlinear system.Finally,the effectiveness of the dynamic contouring error estimation based on the Newton algorithm is completely verified by the simulation comparisons with the static contouring error estimation,which provides a basis for further construction of the coordination controller and realization of the coordinated motion for the system.(3)The problem of motion coordination in multi-axis linkage control is studied.The serial structure of iterative learning controller(ILC)is easy to implement,which has a strong learning ability to deal with contouring errors.Thus,the coordination controller based on Newton-ILC is proposed.The iterative learning feedforward control is utilized to improve the transient performance of the system.The control signal after iterative learning is used to modify the reference contour,which can achieve contour trajectory optimization and pre-compensation of contouring performance.The motion coordination for the system can be also improved.In addition,a complementary sliding mode controller is proposed to weaken the chattering phenomenon and enhance the tracking performance of the system.The comparison of the simulation results validates the feasibility of the Newton-ILC coordination controller.Moreover,an idea for further research on the contouring control scheme in practical applications is provided.(4)To improve the motion coordination for the system,an adaptive PD-type learning law is designed,and an asymmetric Gaussian-like function is introduced into the learning law to make the improvement to the learning performance of the ILC.Therefore,the coordination controller based on the Newton-AILC is proposed to develop the coordinated motion control of the system.Furthermore,considering that the control law generated by the discontinuous control structure excites high-order terms in the uncertainty,which can affect the stable operation of the system and degrade the control performance,an adaptive jerk controller is adopted to design the motion controller.This controller can generate a continuous control signal to suppress the chattering phenomenon.Taking into account the robust performance and adaptive performance of the control scheme,a new adaptive feedback gain is designed for the real-time online update to suppress the influence of uncertainties such as measurement noise.The convergence rate is improved by the terminal attractor,which can achieve asymptotic tracking convergence of the system.An experimental platform based on Links-RT is built to verify the effectiveness of the proposed control scheme.The comparative experimental results confirm the superiority of Newton-AILC-AJC in practical applications,which can meet the task requirements of complex contouring tracking.(5)To further improve the contouring performance of the system under different machining conditions,the influence of the error term generated by the model parameter estimation on the contouring tracking performance is analyzed.The compensation scheme that comprehensively considers transient performance and steady-state accuracy is proposed.The neural networks are introduced into AJC,whose better approximation properties are used to estimate the error term.Then,the intelligent adaptive jerk controller(IAJC)is proposed to improve the design of the motion controller,which can realize the finite-time contouring tracking of the control systems.Moreover,the large control input generation can be avoided,which improves the working efficiency of the system.The comparative experimental results plenty verify that the proposed Newton-AILC-IAJC scheme can ensure the stable operation in practical applications,and further improve the contouring performance of the system. |
PDF Full Text Request