Real-Time Contour-Error Estimation Methods for Three-Dimensional Free-Form Parametric Curves in Contour-Following Tasks

Author(s):  
Zhen-Yuan Jia ◽  
De-Ning Song ◽  
Jian-Wei Ma ◽  
Xiao-Xuan Zhao ◽  
Ning Zhang
2018 ◽  
Vol 141 (4) ◽  
Author(s):  
Jian-Wei Ma ◽  
De-Ning Song ◽  
Zhen-Yuan Jia ◽  
Wen-Wen Jiang ◽  
Fu-Ji Wang ◽  
...  

To reduce the contouring errors in computer-numerical-control (CNC) contour-following tasks, the cross-coupling controller (CCC) is widely researched and used. However, most existing CCCs are well-designed for two-axis contouring and can hardly be generalized to compensate three-axis curved contour following errors. This paper proposes an equivalent-plane CCC scheme so that most of the two-axis CCCs or flexibly designed algorithms can be utilized for equal control of the three-axis contouring errors. An initial-value regeneration-based Newton method is first proposed to compute the foot point from the actual motion position to the desired contour with a high accuracy, so as to establish the equivalent plane where the estimated three-dimensional contouring-error vector is included. After that, the signed contouring error is computed in the equivalent plane, thus a typical two-axis proportional-integral-differential (PID)-based CCC is utilized for its control. Finally, the two-axis control commands generated by the typical CCC are coupled to three-axis control commands according to the geometry of the established equivalent plane. Experimental tests are conducted to verify the effectiveness of the presented method. The testing results illustrate that the proposed equivalent-plane CCC performs much better than conventional method in both error estimation and error control.


2019 ◽  
Vol 42 (5) ◽  
pp. 1059-1069
Author(s):  
Baolin Zhang ◽  
Rongmin Cao ◽  
Zhongsheng Hou

In order to improve the contour error accuracy of two-dimensional linear motor, an improved cross-coupled control (CCC) scheme combining real-time contour error estimation and model-free adaptive control (MFAC) is proposed. The real-time contour error estimation method is based on CCC theory and coordinate transformation idea. It can accurately determine the contour error point of regular contour and avoid the influence of tracking error on the contour error. At the same time, for the design of two-axis error controller, only the input and output data generated by two-dimensional linear motor in reciprocating motion are used to design a multiple input multiple output-model-free adaptive control (MIMO-MFAC) algorithm, this algorithm avoids the dependence on accurate mathematical model and reduces the control difficulty. The experimental comparison showed that the proposed method improves the system tracking accuracy and contour accuracy, and verifies the proposed method correctness and effectiveness.


2011 ◽  
Vol 383-390 ◽  
pp. 7054-7059 ◽  
Author(s):  
Li Mei Wang ◽  
Qi Yang ◽  
Yi Biao Sun ◽  
Chun Fang Liu

The contour accuracy of XY table directly driven by two linear motors was influenced by the complicated reel-time contour error model of free-form curves, uncertainty external disturbance and dynamic matching between X axis and Y axis. To establish XY table model that easily calculated and suitable for free-form curves, real-time contour error estimate method was adopted. In order to reduce uncertainty external disturbance and dynamic matching between X axis and Y axis, the iterative learning cross-coupled controller (ILCCC) was designed for current compensation on X axis and Y axis. Simulation results show that the control scheme can enhance the robustness of the system, and effectively improve the XY table of contour precision.


Author(s):  
Mikola Lysenko ◽  
Keyvan Rahmani ◽  
Roshan D’Souza

In this paper a new hardware accelerated method is presented to evaluate the machinability of free-form surfaces. This method works on tessellated models that are commonly used by CAD systems to render three-dimensional shaded images of solid models. Modern Graphics Processing Units (GPUs) can be programmed in hardware to accelerate specialized rendering techniques. In this research, we have developed new algorithms that utilize the programmability of GPUs to evaluate machinability of free-form surfaces. The method runs in real time on fairly inexpensive hardware (<$600), and performs well regardless of the surface type. The complexity of the method is dictated by the size of the projected view of the model. The proposed method can be used as a plug-in in a CAD system to evaluate manufacturability of a part at early design stages. The efficiency and the speed of the proposed method are demonstrated on some complex objects.


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