Total energy consumption optimization via genetic algorithm in flexible manufacturing systems

2017 ◽  
Vol 104 ◽  
pp. 188-200 ◽  
Author(s):  
Xiaoling Li ◽  
Keyi Xing ◽  
Yunchao Wu ◽  
Xinnian Wang ◽  
Jianchao Luo
2018 ◽  
Vol 2018 ◽  
pp. 1-26
Author(s):  
Ying He ◽  
Jiangping Mei ◽  
Zhiwei Fang ◽  
Fan Zhang ◽  
Yanqin Zhao

Palletizing robot is widely used in logistics operation. At present, people pay attention to not only the loading capacity and working efficiency of palletizing robots, but also the energy consumption in their working process. This paper takes MD1200-YJ palletizing robot as the research object and studies the problem of low energy consumption optimization of joint driving system from the perspective of trajectory optimization. Firstly, a multifactor dynamic model of palletizing robot is established based on the conventional inverse rigid body dynamic model of the robot, the Stribeck friction model and the spring balance torque model. And then based on joint torque, friction torque, motion parameter, and joule’s law, the useful work model, thermal loss model of joint motor, friction energy consumption model of joint system, and total energy consumption model of palletizing robot are established, and through simulation and experiment, the correctness of the multifactor dynamic model and energy consumption model is verified. Secondly, based on the Fourier series approximation method to construct the joint trajectory expression, the minimum total energy consumption as the optimization objective, with coefficients of Fourier series as optimization variables, the motion parameters of initial and final position, and running time constant as constraint conditions, the genetic algorithm is used to solve the optimization problem. Finally, through the simulation analysis the optimized Fourier series motion law and the 3-4-5 polynomial motion law are comprehensively evaluated to verify the effectiveness of the optimization method. Moreover, it provides the theoretical basis for the follow-up research and points out the direction of improvement.


2014 ◽  
Vol 620 ◽  
pp. 625-631
Author(s):  
Guang You Yang ◽  
Xiong Gan ◽  
Tuo Zheng ◽  
Zhi Yan Ma

In wireless sensor networks where the volume and energy of nodes are limited by batteries, which are difficult or prohibitively expensive to replace or recharge in the most of its application scenarios, so improving energy efficiency has very important significance.Cooperative beamforming forms virtual antenna arrays by multiple adjacent wireless sensor nodes, which improves the signal strength at the receiver and reduces the energy consumption of the transmitter by multiplexing gain and interference management.In this paper, the problem of energy consumption optimization for cooperative beamforming in wireless sensor networks was studied. First, considering both amplifier energy consumption and circuit energy consumption,energy consumption models for both broadcast phase and cooperative beamforming phase was presented.Then,we propose a two-step optimization to minimize the total energy consumption by optimizing the modulation parameter and the number of cooperative nodes.We simulate the total energy consumption for various transmission distances,modulation parameters , path losses and the number of cooperative nodes.The numerical results show that,for different system parameters, selecting the optimal modulation parameter and the optimal number of cooperative nodes can reduce total energy consumption and improve energy efficiency.


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