A robust speed control technique for permanent-magnet synchronous motor (PMSM) drives is proposed in this paper for electric vehicle applications. The robust controller consists of a neural-network controller (NNC) in the speed feed-back loop in addition to an on-line trained neural-network model-following controller (NNMFC) in the feedforward loop. The adaptive neural-network model-following c...

injection molding is one of the most important and common plastic formation methods. combination of modeling tools and optimization algorithms can be used in order to determine optimum process conditions for the injection molding of a special part. because of the complication of the injection molding process and multiplicity of parameters and their interactive effects on one another, analytical...

Abstract—Control of a semi-batch polymerization reactor using an adaptive radial basis function (RBF) neural network method is investigated in this paper. A neural network inverse model is used to estimate the valve position of the reactor; this method can identify the controlled system with the RBF neural network identifier. The weights of the adaptive PID controller are timely adjusted based ...

Graph neural networks (GNNs) have demonstrated great success in representation learning for graph-structured data. The layer-wise graph convolution GNNs is shown to be powerful at capturing topology. During this process, are usually guided by pre-defined kernels such as Laplacian matrix, adjacency or their variants. However, the adoptions of may restrain generalities different graphs: mismatch ...

Personalized ambient intelligent systems should meet changes in user’s needs, which evolve over time. Our objective is to create an adaptive system that learns the user behaviour preferences. We propose *BAM – * Behaviour Adaptation Mechanism, a neural-network based control system that is trained, supervised by user’s (affective) feedback in real-time. The system deduces the preferred behaviour...

The paper applied a Recurrent Neural Network (RNN) model in two Integral-Plus-State (IPS) schemes of real-time adaptive neural control. The proposed control modify and extend a previously published direct adaptive neural control scheme with one or two I-control terms, so to obtain a neural, IPS adaptive, offset compensational and trajectory tracking control. The control scheme contains only two...

unknown noise and artifacts present in medical signals with  non-linear fuzzy filter will be estimate and then removed. an adaptive neuro-fuzzy interference system which has a nonlinear  structure presented  for the noise function prediction by before samples. this paper is about a neuro-fuzzy method to estimate unknown noise of electrocardiogram (ecg) signal. adaptive neural combined with fuzz...

nowadays, it has demonstrated that viruses can be transmitted by water and foods. therefore, it causes the research to develop for detecting different viruses in water and foods. among foods, milk can transfer potentially pathogenic viruses. on the other hand, to achieve every method for recovery and extraction of viruses in raw milk it needs to know about impact of milk components on viruses. ...