In machining operation, the quality of surface finish is an important requirement for many turned work pieces. cutting temperature is one of the most important parameters in determining the cutting performance and tool life. the objective for this work is to estimate the cutting temperature in 3D model on tool-chip interface and the interface temperature during turning process, using the digital simulation software COMSOL Multiphysics.The tool–chip interface temperature results obtained from experimental results by using C45 medium carbon steel work piece with natural contact tools, without the application of cooling and lubricating agents and a K type thermocouple technique was used for estimating cutting temperatures in a turning operation.This procedure facilitates the determination of the temperature at tool-chip interface in dry turning process, which is still a challenge for existing experimental and numerical methods.

This paper presents an intelligent control strategy that uses a feedforward artificial neural network in order to improve the performance of the MPPT (Maximum Power Point Tracker) MPPT photovoltaic (PV) power system based on a modified Cuk converter. The proposed neural network control (NNC) strategy is designed to produce regulated variable DC output voltage. The mathematical model of Cuk converter and artificial neural network algorithm is derived. Cuk converter has some advantages compared to other type of converters. However the nonlinearity characteristic of the Cuk converter due to the switching technique is difficult to be handled by conventional controller. To overcome this problem, a neural network controller with online learning back propagation algorithm is developed. The NNC designed tracked the converter voltage output and improve the dynamic performance regardless load disturbances and supply variations. The proposed controller effectiveness during dynamic transient response is then analyze and verified using MATLAB-Simulink. Simulation results confirm the excellent performance of the proposed NNC technique for the studied PV system. 

The multilevel multi-string inverter has gained much attention in recent years due to its advantages in lower switching loss, better electromagnetic compatibility, higher voltage capability, and lower harmonic distortion. Solar Energy is one of the favorable renewable energy resources and the multilevel inverter has been proven to be one of the important enabling technologies in photovoltaic (PV) utilization. As the number of levels increases, it is important to control more switches in parallel with their concurrent processing capability. This paper proposes an IGBT clamped three phase nine levels photovoltaic inverter topology with a multicarrier dual reference pulse-width modulated (PWM) control scheme. Four carrier waves of the fundamental frequency and different amplitudes are compared with two references (a sine wave and its opposite) for generating the control signals of the switches. Some DC/DC boost converters are used to amplify the voltage produced by the photovoltaic generators. Each of these converters is controlled by an MPPT algorithm in order to track the maximum power point of the GPV. Results of simulation in Matlab environment are given and discussed.