Cross-coupling control method for five-axis computer numerical control machine with dual rotary tables

On-line contour error estimation and control for corner smoothed five-axis tool paths

In this paper, neural networks are presented to solve the inverse kinematic models of continuum robots. Firstly, the forward kinematic models are calculated for variable curvature continuum robots. Then, the forward kinematic models are implemented in the neural networks which present the position of the continuum robot’s end effector. After that, the inverse kinematic models are solved through neural networks without setting up any constraints. In the same context, to validate the utility of the developed neural networks, various types of trajectories are proposed to be followed by continuum robots. It is found that the developed neural networks are powerful tool to deal with the high complexity of the non-linear equations, in particular when it comes to solving the inverse kinematics model of variable curvature continuum robots. To have a closer look at the efficiency of the developed neural network models during the follow up of the proposed trajectories, 3D simulation examples through Matlab have been carried out with different configurations. It is noteworthy to say that the developed models are a needed tool for real time application since it does not depend on the complexity of the continuum robots' inverse kinematic models.

Contour error reduction for free-form contour following tasks of biaxial motion control systems

In 3DP process, part has a large contour error due to the print machine, printing parameters, the characters of part materials and other factors. In this paper, based on the result from the Part I, the experimental method is used to study on the part contour error by placing 56 cubes in the manufacturing box in 3DP process. When the binder saturation level and the powder layer thickness are fixed, the contour error for cubes in X, Y and Z directions is obtained, and the leaking error compensation value, also means bleed compensation for the binder in different directions are achieved, and bleed compensation is used to calibrate the printer parameters. The case study also verifies the result in 3DP process, which is effectiveness in parts’ contour error compensation.

In multi-axis machining, the processing of curves and surfaces in the two-dimensional space and the three-dimensional space requires the coordinated motion of each axis, and the machining accuracy is determined by both the tracking error and the contouring error. Tacking and contouring accuracy resulting from not only the high performance controller of each axis to improve the tracking accuracy but also the well controlled coordination motion of each axis to improved contouring accuracy. The sliding mode control and contour error compensation is adopted to achieve the target First, to improve the tracking accuracy, an adaptive PID controller based on sliding mode control which consists of a PID controller and a fuzzy compensator is designed for each axis. The adaptive PID controller can automatically online tune the PID controller gains using the gradient descent method, and the fuzzy compensator is designed to compensate the output of the PID controller. Second, to improve contouring accuracy, considering the mutual dynamic effects among each axis, a contour error compensator is designed to calculate the compensation of each axis by the contouring error and to carry out the contouring error compensation. The simulation results indicated that the proposed control method has a good performance on both tracking and contouring accuracy in three-axis machining.

Reliability of joint kinematic calculations based on direct kinematic and inverse kinematic models in obese children

A sliding mode control for active disturbance rejection was utilized for uniaxial tracking control, and a cross-coupled contour error compensation controller based on nonlinear position domain (PD) was devised for enhanced contour machining precision and robustness of biaxial moving platform. For single-axis tracking control, the total disturbance of the system was initially considered to be the external disturbance plus internal unmodeled dynamics, and the overall disturbance was estimated and compensated in real time using a linear extended state observer. A sliding mode controller was built on this foundation to obtain satisfactory uniaxial control performance. Secondly, based on the estimated value of each axis component of contour error, a nonlinear PD contour error compensation controller was designed to coordinate the tracking motion between axes and further reduced the contour error. The proposed work is compared against state-of-the-art works from literature for various metrics such as tracking error curves, average comparison of tracking errors, and cross-coupled controller parameters. The simulation results showed that the proposed method can effectively improve the contour processing accuracy of the system.

Chapter 3 - Description and modeling of experimental platforms

Inverse Kinematic Model (IKM) is very crucial for real-time control of a robot for any application. Computing the IKM of continuum manipulators is a challenging task. Two types of methods exists; quantitative methods describing a model-based approach; and qualitative methods, based on learning approach. As quantitative methods are based on mathematical expression, they are more flexible for extension (increase in number of sections or collaboration between more than one manipulator). In this paper, two quantitative approaches based on Newton Raphson iterative method and Damped Least Square method, are proposed for Compact Bionic Handling Assistant (CBHA) manipulator to solve inverse kinematics directly using Forward Kinematic Model (FKM). Experimental validation is done for these methods as well as they are compared with the existing approaches named Hybrid approach and Neural Network based learning approach.

Musculoskeletal disorders are major concern globally not just for the pain and suffering by the individual but also due to its adverse impact on the economy of the individual and the society. This results in productivity loss in both manufacturing and service sector, which has an adverse impact over the economy. The main aim of this work is to design and test an upper body exoskeleton arm that will be used for empowering the able-bodied, i.e., healthy users. The exoskeleton arm is intended to power or amplify the ability of the human elbow. Inverse dynamic model of the system is simulated through kinematic analysis and workspace analysis. The mathematical model developed by MATLAB is validated using ADAMS simulation tool. The obtained model is used to analyze the assistive torque requirements and position analysis of each task defined in the problem statement. Finally, the forward kinematic model, the inverse kinematic model, and the workspace analysis of the system are done which is universally flexible with respect to the dynamic parameters of the material used.

In this paper, a dual quaternion-based methodology for computing the forward and inverse kinematic models for a serial manipulator is presented. A dual quaternion-based forward kinematics model is developed for the Kuka LBR IIWA 7 R800 cobot. An inverse kinematics model is developed that uses dual quaternion differential kinematics and includes Jacobian transpose and damped least squares methods for determining Jacobian pseudo-inverse. Implementation of these methods on a given trajectory shows that, compared to damped least squares, the Jacobian transpose method is faster, but is less immune to singularity and gives more jerky motions.

With the continuous development of manufacturing industry, the application range of NC machining technology has been further expanded. The contour accuracy is strongly related to the NC machining quality as a key machine tool performance indicator. Its application efficiency is plainly low as the majority of offline compensation-based contour accuracy adjustments rely heavily on manual experience. Moreover, the isolated research on automatic error compensation and its combination with algorithms does not start with the characteristics of contour accuracy in data processing. Therefore, based on the advantages of strong the robustness of the fuzzy algorithm and the high effectiveness of parameter adjustment, an automatic compensation method for NC machining contour error based on fuzzy control is proposed. The contour error prediction model is designed according to the machining path, and then the automatic compensation strategy for contour error under fuzzy control is designed based on the feed speed. The results showed that under this method, the contour error can reach a maximum of 0.06 and a minimum of 0.025, which was 0.015 lower than the minimum contour error of genetic algorithm. This indicated that the method greatly reduced the CNC machining contour error and improved the contour accuracy, as well as reducing the time cost of contour error compensation, improving the efficiency of contour error compensation, and realizing the automation of error compensation control capability. This is helpful for advancing CNC machining automation technology and supporting the intelligent development of machinery manufacturing.

Improvement of contour precision is one of the important issues in counter-following applications. Currently cross-coupled control method is widely adopted in industrial motion controller, which can significantly reduce contouring error composed by multiaxis. Conventional cross-coupled controller, however, is a centralized one which must be implemented as a whole in computer numerical controller (CNC). Thus it results in many disadvantages such as augment of computing task, degradation of control performance, and so on. This paper analyzes the numerical control system structure, cross-coupled control characteristics and fieldbus technology, proposes a design method of distributed cross-coupled controller (DCCC) based on motion control bus (MCB). The advantages of the DCCC is analyzed in theory, and verified through experiments. Making full use of currently advanced numerical motion control bus and servo in motion control, this method is consistent with the technology development of motion control system.

Iterative learning contouring control: Theory and application to biaxial systems

Contour error, primarily induced by the coupling of multi-axis dynamics and servo lag, is a critical factor limiting the machining accuracy of computer numerical control (CNC) machine tools during complex surface machining. Traditional theoretical modeling methods based on dynamics and parameter identification are difficult to cope with complex nonlinear errors. To address the challenges, this study proposes a data-driven deep learning method to achieve high-precision prediction of contour errors. In this paper, the VMC2100B vertical machining center is used as the experimental platform, and the high-speed dynamic coordinate data acquisition research is carried out with the help of dynamic coordinate acquisition technology, which provides strong data support for the training of deep learning model. A hybrid deep learning prediction model named CLA-Net (CNN-LSTMAttention Network) was constructed: 1D Convolutional Neural Networks (1D-CNN) were employed to extract local spatial features, Long Short-Term Memory networks (LSTM) were used to learn long-term temporal dependencies, and an Attention was introduced to dynamically focus on critical historical information. The experimental results show that the proposed CLA-Net model can control the mean square error (MSE) at about <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\mathbf{3 ~ \mu m}$</tex>, which verifies the effectiveness and superiority of the model in the prediction task. This study provides a new solution for the contour error prediction task of five-axis machine tools.