Gain-Scheduling Multi-Bit Delta-Modulator for Networked Controlled System

International audienceWe analyze in this paper stabilization issues for a Networked Control System that uses a Delta-Modulator Scheme within the encoder/decoder structures. We also analyze the packet-loss issue, and determine a maximum allowable number of consecutive bits lost while keeping stability. We then design a compensation scheme for re-synchronizing the encoder and decoder, after a bit is lost in a network without acknowledgment signals. We finally present a compensation scheme that ensures stability after a pre-determined number of bits is lost. Examples and simulations are provided to demonstrate the results

Analysis Tools and Compensation Methods for the Control of Ma-chines with Friction

Physically it is always possible to construct a system so that a 2 is negative, (by making (r/a) sufficiently large, for example). The difficulty arises because the Coulomb friction law is not always compatible with the equations of rigid-body dynamics. Everything will be resolved if either the beatings or the rotating body are made elastic. When no rigid-body solution exists, the shaft seizes up, and no motion occurs. We note that the phenomenon does not occur in the case of a balanced rotor as it results in F = 0. It may be shown that the paradox also occurs when the c.g. is off the axis of rotation

Estimation of fundamental diagrams in large-scale traffic networks with scarce sensor measurements

The macroscopic fundamental diagram (MFD) relates space mean flow density and the speed of an entire network. We present a method for the estimation of a ``normalized'' MFD with the goal to compute specific Fundamental Diagram in places where loop sensors data is no available. The methodology allows using some data from different points in the city and possibly combining several kinds of information. To this aim, we tackle at least three major concerns: the data dispersion, the sparsity of the data, and the role of the link (with data) within the network. To preserve the information we decided to treat it as two dimensional signals (images), so we based our estimation algorithm on image analysis, preserving data veracity until the last steps (instead of first matching curves that induce a first approximation). Then we use image classification and filtering tools for merging of main features and scaling. Finally, just the Floating Car Data (FCD) is used to map back the general form to the specific road where sensors are missing. We obtained a representation of the street by means of its likelihood with other links within the same network

Stabilisation of Network Controlled Systems with a Predictive Approach

This paper deals with network controlled systems. A state predictor is used to stabilize such system as in [1], [2]. The full characterization of the prediction horizon is provided, which allows to prove the stability of the closed-loop system with the state predictor (using an estimated horizon)