NETWORKED CONTROL SYSTEMS: A PERSPECTIVE FROM CHAOS

Networked Control Systems: a Perspective from Chaos

In this paper, a nonlinear system aiming at reducing the signal transmission rate in a networked control system is constructed by adding nonlinear constraints to a linear feedback control system. Its stability is investigated in detail. It turns out that this nonlinear system exhibits very interesting dynamical behaviors: in addition to local stability, its trajectories may converge to a nonori...

Markovian Delay Prediction-Based Control of Networked Systems

A new Markov-based method for real time prediction of network transmission time delays is introduced. The method considers a Multi-Layer Perceptron (MLP) neural model for the transmission network, where the number of neurons in the input layer is minimized so that the required calculations are reduced and the method can be implemented in the real-time. For this purpose, the Markov process order...

Neural-Smith Predictor Method for Improvement of Networked Control Systems

Networked control systems (NCSs) are distributed control systems in which the nodes, including controllers, sensors, actuators, and plants are connected by a digital communication network such as the Internet. One of the most critical challenges in networked control systems is the stochastic time delay of arriving data packets in the communication network among the nodes. Using the Smith predic...

Chaos in Glassy Systems from a TAP Perspective

We discuss level crossing of the free-energy of TAP solutions under variations of external parameters such as magnetic field or temperature in mean-field spin-glass models that exhibit one-step ReplicaSymmetry-Breaking (1RSB). We study the problem through a generalized complexity that describes the density of TAP solutions at a given value of the free-energy and a given value of the extensive q...

Networked Control Systems