Yao Lina, Wu Wei, Kang Yunfeng, Li Lifan
College of Electrical Engineering, Zhengzhou University, Zhengzhou 450001, China.
Entropy (Basel). 2018 Oct 24;20(11):820. doi: 10.3390/e20110820.
In this paper, a fault-tolerant control scheme is presented for a class of stochastic distribution collaborative control systems, which are composed of three subsystems connected in series to complete the control target. The radial basis function neural network is used to approximate the output probability density function of the third subsystem, which is also the output of the entire system. When fault occurs in the first subsystem, an adaptive diagnostic observer is designed to estimate the value of fault. However, the first subsystem does not have the ability of self-recovery, minimum rational entropy controllers are designed in the latter subsystems to compensate the influence of the fault and minimize the entropy of the system output. A numerical simulation is given to verify the effectiveness of the proposed scheme.
本文针对一类由三个串联子系统组成以完成控制目标的随机分布协同控制系统，提出了一种容错控制方案。采用径向基函数神经网络逼近第三子系统的输出概率密度函数，该函数也是整个系统的输出。当第一子系统发生故障时，设计自适应诊断观测器来估计故障值。然而，第一子系统不具备自我恢复能力，在后两个子系统中设计最小有理熵控制器以补偿故障影响并使系统输出的熵最小化。给出了数值仿真以验证所提方案的有效性。
