×
The submission system is temporarily under maintenance. Please send your manuscripts to
Go to Editorial ManagerAn intelligent and anticipatory speed controller for internal combustion engines was designed theoretically and examined experimentally. This design was based on the addition of a torque loop to the main speed loop. The model can sense the external load with the help of a load cell and send this signal to a soft computing unit for analysis and processing. This scheme will improve the ability of anticipation of controller since it treats the factors that affect the speed, not the speed itself. The experimental design was implemented using two types of actuating techniques; an intelligent throttling actuator and an intelligent injection actuator. The signal was analyzed by using intelligent techniques such as fuzzy logic, neural network and genetic algorithm. The experimental data were used to train the neural and the Adaptive Neuro–Fuzzy Inference System. The comparison of the results obtained in this work with other available models proved the efficiency and the robustness of the present model.
An experimental study has been implemented to study the effect of the central radial groove on the bearing pressure distribution. This study is based on the artificial neural network in the prediction of the complex and uncertain positions. Both width and depth of the groove have been varied at some magnitudes in order to investigate their effects on the pressure distribution and the stability of the bearing. Also, the effect of the groove parameters on the noise at the bearing situation in the systems have been analyzed and discussed. The results show that the use of neural network in the prediction of some points with range is very powerful in the minimization of the overall cost of groove design.