36321696
Adaptive Notch Filter Control for the Torsion Vibration in Lead-Screw Feed Drive System Based on Neural Network
In the machining process, the nature vibration characteristics of feed drive frames are in time-varying. The nature frequencies of the torsion vibration in the lead-screw feed drives are notably changed with the table position, which further influences the stability of servo control. Building the model of servo drive system under consideration of torsion vibration of rotor-screw system, this paper analyzes the effect of changing torsion vibration modes on the notch filter control. The results display that the compensation using the conventional notch filter cannot suppress those disturbances induced by the time-varying vibration modes. Therefore, an adaptive notch filter control method is presented based on an improved BP neural network in this paper. A case study demonstrates that the parameters of the notch filter can be adjusted rightly according to the different table position. Consequently, the torsion vibration modes are compensated efficiently for the time-varying table positions.
29762263
Look-Ahead Scheme for High Speed Consecutive Micro Line Interpolation Based on Dynamics of Machine Tool
This paper presents a new look-ahead Scheme with adaptability of dynamics of machine tool for high speed consecutive micro-line interpolation. A backtracking arithmetic is used to calculate the speeds in the link points of consecutive micro-lines. Moreover, the speed limitations in the link points are analyzed in detail and the compound constraint conditions of the motion axes is introduced based the dynamic characteristics of machine tool. The case studies indicate that, using the scheme presented by this paper, the actual interpolation speed is closer to the command speed and the shock that results from the sharp fluctuate of feed speed is depressed, which will improve the machining efficiency and quality.
31996271
A Method of General Stiffness Modeling for Multi-axis Machine Tool
In this paper, a new method for computing general stiffness model at tool tip for multi-axis machine tool is presented. The formula of general stiffness model at tool tip is derived from virtual-work principle and point transformation matrix method. Point transformation matrix method indicates the transformation relationship of elastic displacement on both ends of flexible axes as well as the transformation relationship of force. By multiplying the point transformation matrix, the final stiffness matrix at tool tip will be obtained efficiently. In this modeling method, the final stiffness matrix is composed of local compliance matrixes according to their contribution to the final stiffness matrix.
196401
An ID-based Anonymous Proxy Signature From Bilinear Pairings
Abstract: A new ID-based anonymous proxy signature scheme from bilinear pairings was proposed in this paper. Anonymous proxy signature is suitable for the situation that the proxy signer’s identity needs to be kept secret. The verifier needs to reveal the real identity of the proxy signer with the help of the original signer. The signature is based on Gap Diffie-Hellman group problems and meets the security requirements such as verifiability, unforgeability, undeniability, anonymity and traceability.
7632071
Position-sensing based a new docking system of RPRS
Docking is an essential function for reconfigurable planetary robot system (RPRS), it supports almost all metamorphic characteristics of the system. This paper presents a space docking method for self-reconfigurable modular robot system. The method adopts a position sensory detector (PSD) to get the space geometrical relation between modular child robots. By using the kinematics and inverse kinematics modeling of the child robot, a docking control algorithm is developed to achieve space dock automatically. To validate the method, simulation experiments were done on a platform based on OPENGL, and the simulating results were given as well.
38250707
Minimizing Spatial Deformation Method for Online Signature Matching
Elastic matching is an important algorithm for online signature verification. Most of elastic matching algorithms are based on dynamic time warping(DTW). In this paper, we propose a new points matching algorithm for online signature verification. After resampling a signature with equidistant spacing, we describe the resampling point by its (3+1) demesional((3+1)D) information: 3D spatial information (x-axis, y-axis, time) and a feature vector. A soft-assign matrix and two special restrictions are introduced for recording the correspondence between two signatures. With a deterministic annealing framework, the mapping between two sets of (3+1)D signature points is achieved by minimizing the warping energy of the thin-plate spline(TPS). Experimental results demonstrate that the proposed algorithm outperforms the DTW-based matching algorithms.
2257792
An in-pipe inspection robot based on adaptive mobile mechanism: mechanical design and basic experiments
A robot, which is composed of adaptive mobile mechanism, is developed for the purpose of performing the internal inspection tasks of pipelines. Adaptability and efficiency are the basic considerations for this robot. Based on these concepts, a prototype is designed and fabricated. The proposed adaptive mobile mechanism equipped with one actuator can perform two working modes, a normal working mode and an assistant enhanced mode. Robot under the normal working mode is used for moving in pipe or monitoring the inner surface of the pipe. On the other hand, robot under the assistant enhanced mode will produce a larger torque to help itself surmount an obstacle in the pipe without any other driving actuator. This special feature is achieved by applying a power transmission mechanism. The rotation problem of the stator is solved according to the calculation results of the robot kinematics. Basic experiments have been conducted to testify the adaptability and efficiency of the robot.
45662594
Neural Network Based Kinematic Control of the Hyper-Redundant Snake-Like Manipulator
In a sinusoid like curve configuration, the snake-like manipulator (also called snake arm) has a wide range of potential applications for its redundancy to overcome conventional industrial robot's limitation when carrying out a complex task. It can perform many kinds of locomotion like the nature snake or the animal's tentacle to avoid obstacles, follow designated trajectories, and grasp objects. Effectively control of the snake-like manipulator is difficult for its redundancy. In this study, we propose an approach based on BP neural network to kinematic control the hyper-redundant snake-like manipulator. This approach, inspired by the Serpenoid curve and the concertina motion principle of the nature snake, is completely capable of solving the control problem of a planar snake-like manipulator with any number of links following any desired direction and trajectory. With shape transformation and base rotation, the manipulator's configuration changes accordingly and moves actively to perform the designated tasks. By using BP neural networks in modeling the inverse kinematics, this approach has such superiorities as few control parameters and high precision. Simulations have demonstrated that this control technique for the snake-like manipulator is available and effective.