基于粒子群优化的鲁棒Minimax估计

Robust Minimax Estimation Based on Particle Swarm Optimization

针对未知但有界噪声干扰下的动态系统提出一种基于粒子群优化的鲁棒minimax估计方法。方法的基本思想是将鲁棒minimax估计问题转化为参数空间上的优化问题,然后采用一种改进粒子群优化算法获得模型参数的最优估计。仿真结果显示该方法可以在估计模型参数的同时准确估计误差界的大小。

A robust minimax estimation method based on particle swarm optimization is proposed for dynamic systems with unknown but bounded disturbances. The basic idea of the method is that the problems of robust minimax estimation are cast as optimization problems in parameter space, and then a modified particle swarm optimization algorithm is used to find the optimal estimation of the model parameters. Simulation results show that the proposed method can accurately estimate the model parameters and error bound.