Application Design of Thrust Allocation Based on Multi Strategy Improved Dung Beetle Algorithm
The solution of thrust allocation is a complex nonlinear constrained optimization problem.Traditional thrust allocation algorithms have low accuracy and are prone to falling into local extreme points when dealing with such problems.Although swarm intelligence algorithms can easily solve these problems,they need to solve stability and fast convergence problems.To solve them,an improved dung beetle thrust allocation algorithm(IDBO)is proposed.It im-proves the convergence speed and stability of the algorithm by selecting solution coefficients as individual variables,using Latin hypercube and reverse learning methods for population initialization,improving the position update strategy for dung beetle dancing behavior,and designing the optimal dung beetle position update strategy.The simulation re-sults show that the convergence speed of it is superior to the compared swarm intelligence algorithms,and the thrust allocation accuracy and energy consumption are also significantly better than all the comparison algorithms.