Intelligent Embedded Systems

Abstract

This work describes a modelling method for a non-linear system which is based on a multi-point linear approximation for a model predictive control (MPC) purpose. The method is derived from artificial neural network techniques and exploits good properties of a Orthogonal Activation Function based Neural Network (OAF-NN). In this work, we describe a technique of a Explicit-MPC (EMPC) which performance, ease of implementation and extension for the hybrid system gives promising direction of a algorithm design for the embedded systems (ES). Proposed modelling procedure is characterized by fast training property and wide applicability in medical systems, automotive, power-electronics industry etc.. Linearity of the model allows to transform into Piecewise Affine (PWA) system structure and to exploit existing algorithms for a explicit model predictive control design. The applicability of the technique was evaluated on a hybrid system by means of existing software tools for MPC design.

Research on the Application Value of Intelligent Heating Box in Newborn Nursing

“…Clinically, a baby is called a newborn when it is less than 28 days old, under external stimuli, due to its low physical fitness and immunity; therefore, it is extremely prone to various diseases [ 1 ]. In the process of nursing newborns, taking reasonable and effective measures to take care is particularly critical; it can not only improve the various symptoms of newborns but can also effectively reduce its various complications [ 2 ]. In recent years, as people's health awareness and health awareness continue to increase, the assessment and care of the newborn's health at birth have been paid more and more attention to [ 3 ].…”