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Remote control involves several issues that degrade seriously the performance of the plant to be controlled. This paper presents a strategy improving the characteristics of the remote control system, using an online adaptive neural net, in order to learn the variations of the remote system parameters to minimize the errors. This strategy is successfully applied to a client-server remote control system...
In this work, we have explored a novel model of learning machine which seems to be able to emulate effectively the way of functioning of the traditional on-off lambda sensors (i.e. O2 sensor). These sensors are a low cost solution used in the SI (spark ignition) engines to monitor the air-fuel ratio and so to maintain a strict control of the air-fuel mixture close the stoichiometric condition. The...
In the present work, an innovative nonlinear controller of nonholonomic mechanical systems, characterized by a dynamic not well known model a priori, using a new neural model obtained by the combination of a Petri net with a neural network is proposed. The performances of the control algorithm are evaluated for tasks of tracking of time trajectories. The study of the stability of the total system...
This paper presents an implementation approach of artificial neural networks in industrial network environment, through the use of function blocks standardized by field-bus foundation (FF). This enables the implementation of a wide range of applications that involve this mathematical tool, such as intelligent control, failure detection, etc in standard FF system. For validation propose, some examples...
This paper presents the SC-MER, safety control for Mars exploration rover, an innovative traction control scheme for wheeled mobile vehicles. The system is thought to be used on space mission rovers and is based on fuzzy logic and competitive neural networks to achieve optimal navigation on rough terrain with variable morphology. The main goal of this research is to minimize the power consumption...
In this work-in-progress the problem with the future integration of large quantity of wind generators in the Portuguese electric grid is presented. A method based in artificial neural networks (ANN) is used to predict the average hourly wind speed. The work starts by choosing the patterns set length, the ANN structure and the learning method. As well as the dimensions of the data sets, training, validation...
The use of hybrid technologies creates the opportunity to combine nano-scale technologies, microelectronics and neuroscience in order to build devices for non-invasive stimulation and recording of cultured neural cells at nano-level. A hybrid neuro-electronic platform for neuroprocessing is proposed as a means to develop a new intelligent information system biologically inspired. The platform is designed...
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