IEEE Trans Cybern. 2022 Jun;52(6):4916-4925. doi: 10.1109/TCYB.2020.3024997. Epub 2022 Jun 16.
In this article, a novel control algorithm is developed for a class of nonlinear stochastic systems subject to multiple disturbances, including exogenous dynamic disturbance and general non-Gaussian noise. An observer is designed to estimate the exogenous disturbance, and then the disturbance compensation is incorporated into a feedback control strategy for the non-Gaussian system. Considering the ability of entropy in randomness quantification, a performance index is established based on the generalized entropy optimization principle. Furthermore, it is adjusted to be available for the controller solution, which also solves the coupling between two kinds of disturbances. On this basis, the optimal controller is provided in a recursive way, with which the closed-loop stability and good antidisturbance ability can be guaranteed simultaneously. Compared with the existing studies on the non-Gaussian stochastic systems, the proposed control algorithm has merits in multiple disturbances decoupling and enhanced antidisturbance performance. Finally, a simulation example is given to demonstrate the effectiveness of theoretical results.
本文针对一类存在多重干扰的非线性随机系统，包括外生动态干扰和广义非高斯噪声，提出了一种新的控制算法。设计了一个观测器来估计外生干扰，然后将干扰补偿纳入非高斯系统的反馈控制策略中。考虑到熵在随机性量化方面的能力，基于广义熵优化原理建立了一个性能指标。进一步地，将其调整为控制器的解，从而解决了两种干扰之间的耦合问题。在此基础上，以递推的方式给出了最优控制器，保证了闭环稳定性和良好的抗干扰能力。与现有的非高斯随机系统研究相比，所提出的控制算法在多重干扰解耦和增强抗干扰性能方面具有优势。最后，通过仿真示例验证了理论结果的有效性。
