### A class of generalized filled functions for unconstrained global optimization.

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The conjugate gradient method of Liu and Storey is an efficient minimization algorithm which uses second derivatives information, without saving matrices, by finite difference approximation. It is shown that the finite difference scheme can be removed by using a quasi-Newton approximation for computing a search direction, without loss of convergence. A conjugate gradient method based on BFGS approximation is proposed and compared with existing methods of the same class.

A network of mobile cooperative sensors is considered. The following problems are studied: (1) the “optimal“deployment of the sensors on a given territory; (2) the detection of local anomalies in the noisy data measured by the sensors. In absence of an information fusion center in the network, from “local” interactions between sensors “global“solutions of these problems are found.

A network of mobile cooperative sensors is considered. The following problems are studied: (1) the “optimal" deployment of the sensors on a given territory; (2) the detection of local anomalies in the noisy data measured by the sensors. In absence of an information fusion center in the network, from “local" interactions between sensors “global" solutions of these problems are found.

This paper details nonlinear Model-based Predictive Control (MPC) algorithms for MIMO processes modelled by means of neural networks of a feedforward structure. Two general MPC techniques are considered: the one with Nonlinear Optimisation (MPC-NO) and the one with Nonlinear Prediction and Linearisation (MPC-NPL). In the first case a nonlinear optimisation problem is solved in real time on-line. In order to reduce the computational burden, in the second case a neural model of the process is used...