Particle Swarm Optimization for the Design of H∞ Static Output Feedbacks

The design of H∞ reduced order controllers is known to be a non-convex optimization problem for which no generic solution exists. In this paper, the use of Particle Swarm Optimization （PSO） for the computation of H~ static output feedbacks is investigated. Two approaches are tested. In a first part, a probabilistic-type PSO algorithm is defined for the computation of discrete sets of stabilizing static output feedback controllers. This method relies on a technique for random sample generation in a given domain. It is therefore used for computing a suboptimal Ha static output feedback solution, In a second part, the initial optimization problem is solved by PSO, the decision variables being the feedback gains. Results are compared with standard reduced order problem solvers using the COMPIeib （Constraint Matrix-optimization Problem Library） benchmark examples and appear to be much than satisfactory, proving the great potential of PSO techniques.

基于混沌序列的无线传感网络敏感数据分层加密存储方法

无线传感网络中的敏感数据加密存储过程,需要解决传感数据属性小差异的影响,这种小差异的混沌性会对分类过程造成干扰,导致以单层加密存储为基础的现有方法安全性降低。为此,提出基于混沌序列的无线传感网络敏感数据分层加密存储方法。采用矩阵补全算法采集无线传感网络敏感数据,并通过基于相似度的聚类算法对敏感数据进行聚类处理,将聚类后的数据利用混沌序列表示。结合混沌序列,利用初始密钥和编码系数矩阵对聚类后的敏感数据进行分层加密,并通过提取加密数据的索引完成无线传感网络敏感数据的分层加密存储。仿真结果表明,所提方法的加密时间在17.5 s附近波动、存储数据量区间为30 GB~39 GB、安全性较高。综上可知,所提方法具有较好的无线传感网络敏感数据分层加密存储性能。