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In this paper, a minimum entropy filter is presented for estimating states in networked control systems with multiple-packet transmission mechanism and non-Gaussian time-delay and noises. The filter is designed for nonlinear NCSs via information theoretic learning approach based on stochastic gradient algorithm. A numerical example is given to illustrate the effectiveness of the proposed scheme.
Stochastic distribution control (SDC) for non-Gaussian system is a mathematically complicated yet practical problem to solve. The most recent solution involves a radial basis function neural network (RBFNN) framework to approximate non-Gaussian output probability density function (PDF). The dynamic weights of such neural network are controlled within each batch of ILC, using a dedicated adaptive controller...
A novel control method is proposed for networked control systems with nonlinear process, probably non-Gaussian process noise and time delays. The performance index of closed loop control system consists of entropy, mean value and control energy constraint. Two stochastic control methods for networked control systems are given under the same general frame. One method utilizes gradient optimal techniques...
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