基于改进粒子群算法的飞机刹车控制律参数寻优研究

Parameter Optimization of Aircraft Brake Control Law Based on Improved Particle Swarm Optimization Algorithm

飞机防滑刹车控制律参数的选取不仅直接影响着飞机的刹车性能,还对飞机着陆的安全性起着重要作用,而实际飞机刹车过程异常复杂,其模型通常具有高维非线性的特点,且从工程角度出发,刹车距离的缩短并非单一核心诉求,轮胎磨损同样需要考虑,这就使得刹车控制律参数的选取异常困难。为解决上述问题,在刹车值目标函数的基础上,引入了机轮打滑值评价目标,优化了飞机刹车控制系统的目标函数。在标准粒子群算法的基础上引入了二阶振荡环节,融合了差分变异策略,并对算法的惯性权重和加速度系数进行改进,使得算法的寻优性能得到提升。将该算法应用至飞机刹车系统MATLAB/Simulink模型中进行仿真,证明了所提算法在飞机防滑刹车控制律参数寻优方面的有效性和科学性。

The selection of aircraft anti-skid brake control law parameters not only affects the brake performance of the aircraft,but also plays an important role in the safe landing of aircraft.The practical aircraft brake process is extremely complex,and the model of the aircraft brake process usually has a highdimensional nonlinearity characteristics.From an engineering point of view,the reduction of brake distance is not a single core demand,and tire wear also needs to be considered,which makes the selection of brake control law parameters extremely difficult.To solve the above-mentioned problems,based on the objective function of brake values,the evaluation objective of wheel slip values is introduced,the objective function of aircraft brake control system is optimized.Secondly,based on the standard particle swarm algorithm,second-order oscillation link is introduced,differential mutation strategy is fused,the inertia weights and acceleration coefficients of the algorithm are improved so that the optimization performance of the algorithm is improved.Finally,the simulation is carried out by applying this algorithm to MTLAB/Simulink model of the aircraft brake system,the effectiveness and scientificity of this algorithm in optimizing aircraft brake control law parameters is proved.