具有状态约束的基因调控网络的集员滤波器研究
Set-membership filter design for genetic regulatory networks with state constraints

针对基因调控网络中切实存在状态约束现象，在考虑一类含时滞、参数不确定、噪声干扰的离散基因调控网络模型基础上设计一种集员滤波器，实现基因调控网络状态的估计. 通过假设测量噪声是未知但有界的，采用LMI方法设计集员滤波器，获得滤波器的增益矩阵，运用递归优化算法对集员滤波器进行优化. 最后，通过数值仿真证明了所提算法的有效性，实现了基因调控网络中的mRNA和蛋白质浓度的准确估计.
The state constraints is an important problem in the area of genetic regulatory networks. A class of discrete-time genetic regulatory networks with time delays，parameter uncertainties and noise is considered. A set-membership filtering method is proposed to estimate the states of the underlying genetic regulatory networks. In this filtering method，it assumes that measurement noises of the process is unknown-but-bounded. The desired filter gains are characterized as the solution of a set of linear matrix inequalities，and a recursive algorithm is developed for computing the set membership filtering. Finally，a numerical example is provided to illustrate the effectiveness of the proposed method，which shows that by using the proposed set-membership filtering algorithm，the concentrations of mRNA and protein could be estimated accurately