scholarly journals Motion planning optimization of trajectory path of space manipulators

Author(s):  
Dong Qiao

With the development of the aerospace industry, the work carried out inside and outside the weightless space station is becoming more and more complicated. In order to ensure the safety of astronauts, space manipulators are used for operation, but it will disturb the space station that is a base during work. In order to solve the above problems, in this paper, the planning method of the motion trajectory of manipulators, the motion model of manipulators and the particle swarm optimization (PSO) algorithm used for optimizing the trajectory are briefly introduced, the multi-population co-evolution method is used to improve the PSO algorithm, and the above two algorithms are used to optimize the motion trajectory of the floating pedestal space manipulator with three free degrees of rotation in the same plane by the matrix laboratory (MATLAB) software. It is compared with genetic algorithm. The results show that the improved PSO algorithm can converge to a better global optimal fitness with fewer iterations compared with the traditional PSO algorithm and genetic algorithm. The obtained motion trajectory optimized by the improved PSO algorithm has less disturbances to the pedestal posture, and less time is required to achieve the target motion; moreover the changes of mechanical arm joint are more stable during the motion.

2013 ◽  
Vol 401-403 ◽  
pp. 1805-1808
Author(s):  
Yan Juan Ren

For the same controlled process, different controller is radically different in control effect. Aimed at the puzzle of being difficult to select the controller for the incompatibility among control performance index, the paper proposed a sort of improved PSO algorithm. Based on the construction of objective function in multi-performance index parameter, the algorithm could quickly search and converge to control parameter in global optimal extremum corresponded to each controller and single out the controller through performance comparison excellently. In the paper, it took the controller selection of wastewater treatment system as an example, designed the algorithm of multi-modal HSIC controller of DO parameter, made the experiment of system simulation, and the simulation demonstrated that the HSIC controller could be stronger in robustness and better in dynamical and steady control quality compared with improved PID controller. The research result shows that it is reasonable and applicable to optimize selection of controller.


2015 ◽  
Vol 734 ◽  
pp. 522-525 ◽  
Author(s):  
Liang Tang ◽  
Zhi Chao Wang ◽  
Lei Gao

To solve large linear equations using SOR method, the most important thing is to ascertain relaxation factor. Considering current methods can not get the factor from global aspect, iteration times become larger and speed become slower. We pose a method to fix optimal factor using global search quality, genetic operational quality and compare the factor value obtaining from PSO algorithm and genetic algorithm, parabolic method. As a result, it shows that it is easier for PSO method to get optimal value than genetic and parabolic method from simulation result. PSO algorithm has huge advantage on solving global optimal problems. It is definite that PSO algorithm has great advantage then other methods and this method, and another advantage is it’s feasibility and convenience.


2009 ◽  
Vol 29 (8) ◽  
pp. 2245-2249 ◽  
Author(s):  
Xiang XU ◽  
Dong-bo ZHANG ◽  
Hui-xian HUANG ◽  
Zi-wen LIU

2013 ◽  
Vol 33 (2) ◽  
pp. 319-322
Author(s):  
Min ZHANG ◽  
Qiang HUANG ◽  
Zhouzhao XU ◽  
Baizhuang JIANG

Author(s):  
Chen Chen ◽  
Bingjie Li ◽  
Wei Zhang ◽  
Hongda Zhao ◽  
Ciwei Gao ◽  
...  

2021 ◽  
Vol 1820 (1) ◽  
pp. 012185
Author(s):  
Shunjie Han ◽  
Xinchao Shan ◽  
Jinxin Fu ◽  
Weijin Xu ◽  
Hongyan Mi

2011 ◽  
Vol 460-461 ◽  
pp. 117-122 ◽  
Author(s):  
Guang Yu Zhu ◽  
Lian Fang Chen

In this paper, a multi-level method has been adopted to optimize the holes machining process with genetic algorithm (GA). Based on the analyzing of the features of the part with multi-holes, the local optimal processing route for the holes with the same processing feature is obtained with GA, then try to obtain the global optimal route with GA by considering the obtained local optimal route and the holes with different features. That is what the multi-level method means. The optimal route means the minimum moving length of the cutting tool and the minimum changing times of the cutting tool. The experiment is carried out to verify the algorithm and the proposed method, and result indicates that with GA and using the multi-level method the optimal holes machining route can be achieved efficiently.


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