Stochastic Stability of Event-triggered Anytime Control

We investigate control of a non-linear process when communication and processing capabilities are limited. The sensor communicates with a controller node through an erasure channel which introduces i.i.d. packet dropouts. Processor availability for control is random and, at times, insufficient to calculate plant inputs. To make efficient use of communication and processing resources, the sensor only transmits when the plant state lies outside a bounded target set. Control calculations are triggered by the received data. If a plant state measurement is successfully received and while the processor is available for control, the algorithm recursively calculates a sequence of tentative plant inputs, which are stored in a buffer for potential future use. This safeguards for time-steps when the processor is unavailable for control. We derive sufficient conditions on system parameters for stochastic stability of the closed loop and illustrate performance gains through numerical studies.Comment: IEEE Transactions on Automatic Control, under revie

Bagging Approach for Increasing Classification Accuracy of CART on Family Participation Prediction in Implementation of Elderly Family Development Program

Classification and Regression Tree (CART) was a method of Machine Learning where data exploration was done by decision tree technique. CART was a classification technique with binary recursive reconciliation algorithms where the sorting was performed on a group of data collected in a space called a node / node into two child nodes (Lewis, 2000). The aim of this study was to predict family participation in Elderly Family Development program based on family behavior in providing physical, mental, social care for the elderly. Family involvement accuracy using Bagging CART method was calculated based on 1-APER value, sensitivity, specificity, and G-Means. Based on CART method, classification accuracy was obtained 97,41% with Apparent Error Rate value 2,59%. The most important determinant of family behavior as a sorter was society participation (100,00000), medical examination (98,95988), providing nutritious food (68.60476), establishing communication (67,19877) and worship (57,36587). To improved the stability and accuracy of CART prediction, used CART Bootstrap Aggregating (Bagging) with 100% accuracy result. Bagging CART classifies a total of 590 families (84.77%) were appropriately classified into implement elderly Family Development program class

Event-triggered Data-efficient Observers of Perturbed Systems

International audienceIn this paper, an event-triggered, data-rate constrained observer for discrete-time linear systems with perturbations is presented. The system is connected to a remote location by a communication channel which can only transmit limited numbers of bits per time interval. The system is subject to perturbations in its state as well as errors in the output measurement. The objective is to reconstruct estimates of the state at the remote location, by sending messages over the communication channel. A new type of data-rate constrained observer which can be more efficient in terms of communication rate is presented. Relation between an admissible communication rate and the system parameters is evaluated. The observer's efficiency is illustrated by simulations