Research On Structure Optimization And Control Techniques Of 6R Serial Arc Welding Manipulator

The whole industrial robot market is booming. It is estimated that there are still 1.2 to 1.5 million units market space at least for the global industrial robots market. However, in this huge market, the market share of China is less than 1%. Hence, deep research on the general common technology and the key technology of industrial robot not only means significantly to the development of robotics technology in China, but also will bring substantial economic benefits to our robotics industry. In this paper, research on structure optimization and control techniques of 6R serial arc welding manipulator was carried out systematically and deeply, and the main contents of this thesis are as follows:In chapter I, on the basis of referring to domestic and international associated documents, related study background and significance of the subject were expounded, the current research situation and application prospection of robots especially industrial robots were briefly introduced, key technologies of industrial robots were investigated, development trend of industrial robots were summed up, and the main study work was proposed.In chapter II, a six degree-of-freedom(DOF) serial arc welding manipulator named Qianjiang I was designed, based on which the kinematics model was built and a workspace calculation method for multiple DOF serial manipulators with revolute joints called surface enveloping and overlaying(SEO) method was presented. By dividing a manipulator into several low-DOF parts, the SEO method choosed the reference point of each part, calculated its boundary surface using the surface enveloping method and overlayed these boundary surfaces to obtain the whole workspace finally. By showing the workspace simulation results on Qiangjiang I, the SEO method was proved working correctly and effectively.In chapter III, research on general structure optimization index of serial industrial robot was carried out. A structure optimization method based on comprehensive performance index of workspace and energy cost was presented for serial industrial manipulators with working characteristics of implementing a long-term repeated trajectory. Optimized geometric parameters of Qianjiang I was obtained based on the mentioned comprehensive performance index by real-coded genetic algorithm. It was proved by structure optimization results of Qianjiang I that the structure optimization method base on the comprehensive performance index of workspace and energy cost not only satisfied all workspace constraints, but also saved robot running energy cost and reduced robot running costs.In chapter IV, a spatial regulation method for robot joint position feedback was presented. In order to get the real position feedback of end-effector reference point by the robot kinematics model, a spatial regulation filter was built, through which position feedback signals of each robot joint could be filtered to eliminate robot structure error. Optimization-based solving methods for weight matrix of the spatial regulation filter was studied and the least mean square (LMS) adaptive algorithm was adopted. Base on the piecewise spline, the fitting method for joint regulation weights was studied and the polynomial spline function for each robot joint regulation weights was deduced. By showing the simulation results on Qianjiang I, the mentioned solving method for weight matrix of the spatial regulation filter was proved working correctly and effectively and the regulated trajectory of end-effector reference point fitted its real trajectory.In chapter V, a joint position closed-loop control system of Qianjiang I was realized and the joint velocity closed-loop control model was identified using the recursive generalized least-square algorithm. Based on the identified joint velocity model, parameters of the joint position closed-loop control system was optimized by an improved real-coded adaptive genetic algorithm, with which the system response time, overshoot and steady-state error were highly improved, which was proved by experimental results.In chapter VI, an adaptive real-time predictive compensation control (ARTPCC) is proposed for the time delay problem of serial manipulators to minimize real-time tracking control errors. Based on artificial neural network (ANN), a predictive model of the joint velocity closed-loop control system was built and modified functions of model weights between layers were deduced. With the ANN predictive model, an ARTPCC model for Qianjiang I was built and trajectory tracking control experiments were carried out. The racking control experiment results of the end-effector reference point of Qianjiang I showed that the ARTPCC reduced the tracking error, enhanced the system response and tracking accuracy efficiently. Meanwhile, the welding experiment results showed that the welding seam turned more continuous, uniform and smooth after using the ARTPCC.In chapter VII, the major work of the study was summarized, and the conclusions and innovations of the study were elaborated. And the future study of the serial manipulator was also prospected...