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As soft computing techniques are more and more widely used in machining process, Artificial Neural Network (ANN) has become an effective way to construct predicting model in grinding process. The present paper reviews the efforts made in recent two decades on modeling grinding process via ANN in a sequence as input and output parameters, ANN topology and the details of the ANN training algorithm....
Modelling and control of gas turbines (GTs) have always been a controversial issue because of the complex dynamics of these kinds of equipment. Considerable research activities have been carried out so far in this field in order to disclose the secrets behind the nonlinear behaviour of these systems. Although the results of the research in this area have been satisfactory so far, it seems that there...
Although surface electromyography (sEMG) has a high correlation to muscle force, an accurate model that can estimate joint torque from sEMG is still elusive. Artificial neural networks (NN), renowned as universal approximators, have been employed to capture this complex nonlinear relation. This work focuses on investigating possible improvements to the NN methodology and algorithm that would consistently...
Using haptic interface to control manipulator which is critical in intracellular injection has many beneficial implications. In particular, the haptic device should be able to control the microrobot in ??m resolution, requiring an accurate model of the system. As the system has an unknown internal structure with a nonlinear behavior, a neuro-fuzzy dynamic model has been developed. Adaptive Neuro-Fuzzy...
In this paper, we consider the tracking problem of propeller shaft speed and simultaneously minimizing torsional vibrations in marine shafting system, in the presence of parametric/functional uncertainties and unmodelled dynamics. Torsional vibrations within the shafting system can be induced by the hydrodynamic forces acting on the propeller and the inertia forces of the crank mechanism. Excessive...
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