title: Improved single neuron controller for multivariable stochastic systems with non-Gaussianities and unmodeled dynamics.
abstract: In this paper, a new adaptive control approach is presented for multivariate nonlinear non-Gaussian systems with unknown models. A more general and systematic statistical measure, called (h,ϕ)-entropy, is adopted here to characterize the uncertainty of the considered systems. By using the "sliding window" technique, the non-parameter estimate of the (h,ϕ)-entropy is formulated. Then, the improved neuron based controllers are developed for multivariate nonlinear non-Gaussian systems by minimizing the entropies of the tracking errors in closed loops. The condition to guarantee the strictly decreasing entropy of tracking error is presented. Moreover, the convergence in the mean-square sense has been analyzed for all the weights in the neural controllers. Finally, the comparative simulation results are presented to show that the performance of the proposed algorithm is superior to that of PID control strategy.
authors.affiliation: State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power University, Beijing 102206, PR China. Electronic address: zjh@ncepu.edu.cn.
authors.forename: Jianhua
authors.initials: J
authors.lastname: Zhang
authors.forename: Man
authors.initials: M
authors.lastname: Jiang
authors.forename: Mifeng
authors.initials: M
authors.lastname: Ren
authors.forename: Guolian
authors.initials: G
authors.lastname: Hou
authors.forename: Jinliang
authors.initials: J
authors.lastname: Xu
mesh_terms: D000200:Action Potentials / Q000502:physiology*; D000465:Algorithms; D000818:Animals; D003198:Computer Simulation; D025461:Feedback, Physiological / Q000502:physiology; D006801:Humans; D008959:Models, Neurological; D015233:Models, Statistical; D015999:Multivariate Analysis; D009415:Nerve Net / Q000502:physiology*; D016571:Neural Networks, Computer; D009474:Neurons / Q000502:physiology*; D016011:Normal Distribution; D013269:Stochastic Processes
keywords: -entropy; Improved neuron controller; Multivariable systems; Non-Gaussian noise; Sliding window