Rigid tapping of NC Tapping center is an electromechanical control system which is strongly nonlinear, uncertain and difficult to precise modeling. It is unavoidable to be affected by some nonlinear and uncertain factors such as friction and mechanical resonance. The traditional control method could not fundamentally solve the contradiction between rapid stability and high stable precision of the system response. As an intelligent control method, fuzzy control is actually a kind of PID regulator, and it exists a strong complementary to PID control in the system dynamic and static characteristics. This paper introduced fuzzy adaptive PID control applied to NC rigid tapping in engineering practice, the control method need not to build the controlled object, using mathematical model of fuzzy reasoning method for the online PID parameters auto-tuning, it met the system well for the rapidity and smoothness of comprehensive index requirement and technical realizability, finally through test platform test, numerical control machine tool actual tapping was validated.
Inherent uncertainties always exist in the positioning picking manipulators in complex environment, modeling and simulation of positioning. The manipulators were discussed based on binocular stereo vision in virtual environment (VE). Based on stereo vision, a method how virtual manipulators locate picking object by human-computer interaction (HCI) was proposed. The data input from vision were mapped to virtual picking manipulators so that it could enable the positioning and simulation with route and events-driven mechanism. The positioning experimental platform in VE consists of hardware of CCD stereo vision and simulation software. The visualized simulation system was exploited by EON SDK. The simulation of manipulator’s positioning was realized in VE by the platform. This method can be used for virtual robot to locate objects’ long-distance positioning in complex environment.
According to different environment and working requirement, the manipulators with diverse shapes and functions are required. In this paper, a virtual design and simulation system for manipulators of multi-degree of freedom (DOF) was put forward. Knowledge classification and modeling were carried out for the manipulator’s mechanism and motion behaviors. The software architecture framework and platform of the hardware and software were described. The overall program approach and its realization of the system were introduced. Based on the VC++ 6.0 development platform, the manipulator’s design and simulation system was developed and tested by examples. The results show that it provides a theoretical method and a tool for the virtual design and virtual manufacturing of multi-DOF manipulators in complex environment, which elevates the speed and lowers the cost of research and development.
Aiming at the problem of low recognition rate and easy affected by environment during the process of robot target recognition in complex environments, the target recognition method combining support vector machine (SVM) with D-S evidence theory was proposed. Taking citrus recognition as an example, SVM was used by the method to local classification according to citrus color and geometry feature information respectively, and the results of SVM were transformed to probability outputs through Platt model, and treated them as the basic probability assignment (BPA) of D-S evidence theory to reason and fuse local recognition results, and then realized the combination of SVM and D-S evidence theory in citrus recognition, finally improved the recognition rate. The experimental results showed that: the recognition rate of the method combining SVM with D-S evidence theory and integrating color features and geometry features was higher than SVM method with only color or geometry features.
In order to reduce the research and experimental cost of hand-picking machine, to make the design of manipulator more reasonable, and to provide more optimized program for the design, an agricultural picking manipulator simulation system based on intelligent design was designed. Firstly ,based on the research needs, to simplify the real picking manipulator under the premise of that the simulation accuracy reach the requirement, the model of picking manipulator had been simplified. Secondly, the finished model was put into EON Studio to build the virtual procedure, and movement properties were added to the manipulator to realize the function of motion simulation. Thirdly, the picking manipulator mathematics motion model of 4 freedoms was established, and the inverse kinematics of the picking manipulator was analyzed by MATLAB analysis tools, and the reverse solution program was written. Finally, Microsoft Visual C++ was used to complete the design of simulation platform, in order to realize the calling of various functions of the manipulator.
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