This chapter contains sections titled: Historical Review Supervised Multilayer Networks Unsupervised Neural Networks: Kohonen Network Unsupervised Networks: Adaptive Resonance Theory Network Model Validation Summary References Recommended Exercises

Nonlinear System Identification

Wireless body area networks (WBANs) form a new and interesting area in the world of remote health monitoring. An important concern in such networks is the communication between the sensors. This communication needs to be energy efficient and highly reliable while keeping delays low. Mobility also has to be supported as the nodes are positioned on different parts of the body that move with regard to each other. In this paper, we present a new cross-layer communication protocol for WBANs: CICADA or Cascading Information retrieval by Controlling Access with Distributed slot Assignment. The protocol sets up a network tree in a distributed manner. This tree structure is subsequently used to guarantee collision free access to the medium and to route data towards the sink. The paper analyzes CICADA and shows simulation results. The protocol offers low delay and good resilience to mobility. The energy usage is low as the nodes can sleep in slots where they are not transmitting or receiving.

A low-delay protocol for multishop wireless body area networks

Adaptive receding horizon control for constrained MIMO systems

Rolling element bearings are among the most widely used and also vulnerable components in rotating machinery equipment. Recently, prognostics and health management of rolling element bearings is more and more attractive both in academics and industry. However, many studies have been focusing on the prognostic aspect of bearing prognostics and health management and few efforts have been performed in relation to the optimal degradation feature selection issue. For more effective and efficient remaining useful life predictions, three goodness metrics of correlation, monotonicity and robustness are defined and combined for automatically more relevant degradation feature selection in this paper. Effectiveness of the proposed method is verified by rolling element bearing degradation experiments. Copyright © 2015 John Wiley & Sons, Ltd.

Degradation Feature Selection for Remaining Useful Life Prediction of Rolling Element Bearings

The field of photovoltaics gives the opportunity to make our buildings "smart'' and our portable devices "independent", provided effective energy sources can be developed for use in ambient indoor ...

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Dye-sensitized solar cells under ambient light powering machine learning : towards autonomous smart sensors for the internet of things

This paper handles a duality problem between the Generalized Predictive Control (GPC) strategy and the identification of parameter membership set. The predictor is rewritten so that it is linear with respect to the parameters of member-ship set. The convexity of criterion to be optimised is satisfied.

Robust GPC using limited complexity polytopes

Robust filtering for descriptor large scale systems via LMI

In this article, we consider the synthesis of finite time observers for some class of nonlinear systems by solving some LMI problem. First, we develop a method to calculate a constant gain which is used to determine an observer for a class of nonlinear systems. Secondly, we use an affine gain to synthesis the observer. The method can also be applied to the case of another class of nonlinear systems with nonlinear output. An application to the manipulator arm and a numerical example illustrate the proposed theory and point out the ameliorations comparing with asymptotic observers.

Finite Time Observers for Nonlinear System by Solving LMIs Problem: Application to the Manipulator Arm

In this paper, we propose to use the Model Predictive Control (MPC) based on the ARX (Auto Regressive with Exogenous Input) model expansion on Laguerre orthonormal bases, which provides a better performances with respect to the classical ARX model. The resulting model is entitled the ARX-Laguerre model that enables to identify a large class of linear systems with drastically reduction of involved parameters. An l2 - norm finite moving horizon cost function is used to obtain the control law formulated as an analytical expression.

Model Predictive Control based on the ARX-Laguerre model

Cet article traite le probleme de synthese des observateurs des systemes lineaires de grande dimension. L'approche que nous proposons ici presente l'observateur decentralise pour ces systemes quand les interconnexions ne sont pas disponibles. Les conditions necessaires et suffisantes d'existence de tels observateurs sont donnees. Un exemple sera presente pour valider ces resultats.

https://hal.archives-ouvertes.fr/hal-00543080/document

Hassani Messaoud

Papers

Robust GPC using limited complexity polytopes

Robust filtering for descriptor large scale systems via LMI

Finite Time Observers for Nonlinear System by Solving LMIs Problem: Application to the Manipulator Arm

Model Predictive Control based on the ARX-Laguerre model

Observateur décentralisé des systèmes de grande dimension à entrées inconnues