基于AWDO算法的主动悬架LQR控制优化

Active suspension LQR control optimization based on AWDO algorithm

车辆主动悬架LQR控制研究的关键是性能指标加权系数的选择,针对这个问题,文中提出了一种基于改进风驱动优化算法的LQR控制器加权系数优化方法。利用协方差矩阵自适应评价策略算法(CMAES)确定传统风驱动优化算法(WDO)的固有参数,得到自适应风驱动优化算法(AWDO)。将LQR控制器性能指标的加权系数作为优化目标,在解空间中迭代搜索,寻找目标函数值最小的位置。通过实验仿真,并与粒子群算法(PSO)和遗传算法(GA)比较,该算法的收敛速度、收敛精度和鲁棒性更好,优化后的主动悬架性能比相应被动悬架的性能更优。

The key to the study of LQR control of vehicle active suspension is the selection of the weighting coefficient of performance index,aiming at solving this problem,an LQR controller weighting coefficient optimization method based on WDO algorithm was proposed.Using the covariance matrix adaptive evaluation strategy(CMAES)adaptive algorithm to determine the inherent parameters of the traditional wind-driven optimization algorithm(WDO),the adaptive wind-driven optimization algorithm(AWDO)is developed.Taking the weighting coefficient of LQR controller's performance index as the optimization objective and iteratively searching in the solution space,the minimum position of the objective function value is found.Through experimental simulation and comparison with particle swarm optimization(PSO)and genetic algorithm(GA),it shows that the algorithm has better convergence speed,convergence accuracy and robustness,and the performance of optimized active suspension is better than that of the corresponding passive suspension.