This paper presents a neurocomputational model for estimation of feed-position in circular microstrip antenna. The difficulty in computing the feed position in circular microstrip antenna lies due to the involvement of a large number of physical parameters including their associated optimal values. It is indeed very difficult to formulate an exact numerical solution merely on practical observat...

This paper presents an application of Neural Networks to the control of a real system with measurement noise. The details of the system and the implementation of sensor, controller and actuator are described. Saturation in the actuator is present and dealt with. The results of controlling the kiln with Direct Inverse Control and Additive Feedforward strategies are presented and compared. Proble...

Hairpin bandpass filter are compact structures they may theoretically be obtained by folding the resonator of parallel-coupled half wave length resonator which reduces the coupling between resonators. This type of U shape resonator is so called hair pin resonator. In the present paper a novel technique has been proposed for the estimation of bandwidth for variation of slot length on the bandpas...

Background and aims: Depression disorder is one of the most common diseases, but the diagnosis is widely complicated and controversial because of interventions, overlapping and confusing nature of the disease. So, keeping previous patients’ profile seems effective for diagnosis and treatment of present patients. Use of this memory is latent in synthetic neuro-fuzzy algorithm. P...

common heat transfer fluids such as water, ethylene glycol, and engine oil have limited heat transfer capabilities due to their low heat transfer properties. nanofluids are suspensions of nanoparticles in base fluids, a new challenge for thermal sciences provided by nanotechnology. in this study, we are to optimize and report the effects of various parameters such as the ratio of the thermal co...

A neural network may be considered as an adaptive system that progressively self-organizes in order to approximate the solution, making the problem solver free from the need to accurately and unambiguously specify the steps towards the solution. Moreover, Evolutionary Artificial Neural Networks (EANNs) have the ability to progressively improve their performance on a given task by executing lear...

The application of neural network (ANN) for the prediction of fermentation variables in batch fermenter for the production of ethanol from grape waste using Saccharomyces cerevisiae yeast has been discussed in this article. Artificial neural network model, based on feed forward architecture and back propagation as training algorithm, is applied in this study. The LevenbergMarquardt optimization...

Iterative learning control is a feedforward control technique applied to systems or processes that operate in a repetitive fashion over a fixed interval of time to improve tracking/regulation performance in response to reference inputs/disturbance inputs that are repeatable in each cycle. In this paper, learning control is applied to coil-to-coil gauge and tension control during the thread-up p...

The present report summarizes the work conducted during the internship on Feedforward Control of the Magnetic Levitation Setup. Different feedforward strategies, specifically tailored for this setup, are developed and reviewed. These feedforward methods explicitly take the intrinsic position-dependent behavior of the magnetic levitation setup into account. Additionally, closed-loop stability of...