Optimization of structural parameter of mulberry leaf picking machine based on improved real coded genetic algorithm
In order to solve the problem of local optimization and low solving accuracy of the structural optimization of mulberry leaf picking machine,an improved real genetic algorithm is proposed.Firstly,a roulette selection operator based on order combination fitness function is given,the operator selects one of the two fitness functions through an adaptive parameter change on the basis of roulette,and then calculates the fitness value.Then,an improved heuristic crossover operator based on direction is designed,which not only preserves the influence of the best of the two parent individuals on the offspring individuals,but also increases the influence of the best of the population on the offspring individuals,so as to increase the possibility of crossover producing potential offspring.Then,the improved algorithm is applied to the optimization parameter design of rocker mulberry leaf picker,and the superiority of the algorithm is verified by simulation and comparison test with other algorithms,and the optimal parameter combination of the picker is obtained as follows,the speed of the walking structure is 24 mm/s,the angular speed of the flipping structure is 1.2 rad/s,and the speed of the picking structure is 440 mm/s.The performance of the whole machine is improved by 13%compared with that before optimization.Finally,field tests with the optimized parameter combination show that the performance of the mulberry leaf picker is improved by 10.9%and the error is less than 2.1%.It can be seen that the improved real genetic algorithm is an effective algorithm to optimize the parameters of the picker.
万方数据
维普
