The change in loads in most applications whose source of nutrition is a renewable energy system. Renewable energy systems can change according to climatic conditions. To control and control these changes, the use of conventional control systems such as PIDs. The PID is one of the most common and used conventional control systems that have been chosen to output the type of power electronic devise (DC-DC converter) in different working conditions. The current study aims to improve the system performance through simulation. Simulation results demonstrate the effectiveness of the system with the controller based on setting parameters such as recording system states, embedded elevation time and transient response.

This work is presenting under the title simulation model of single phase PWM inverter by using MATLAB/Simulink. There are many researchers’ works in this field with the different ways because it is important field and it has many applications. The converter DC power to AC power for any system that mean it need the power electronic device (inverter). The inverter is using when the source DC power and the load AC power. In this work, the simulation system includes the source 300V DC power, inverter, LC filter and load (R). The simulation result shows the waveform of all part in this system like input and output current and voltage.

The main objective of this paper is to design a low cost electro-pneumatic module which can be used in the industrial automation equipment’s, robotic systems and mechatronic applications. Electro-pneumatic module includes four low-cost on/off solenoid valves and double acting cylinder. A Pulse width modulation (PWM) technique was used, which enable the model to correct the control of piston position and then to enable the system to follow the required trajectories accurately in many applications. Thus, it can be a good alternative at a lower cost than the using of proportional valves in the electro-pneumatic applications. A Fuzzy logic algorithm with PD control on the model in Matlab/Simulink environment to adjust the control values was applied. The simulation results and response of model were compared with the results from a previous practical with the similar model and controller but with a proportional valve. Finally, the simulation results showed a good accuracy with the practical results.

The current research sheds light on the electronic power devices that work as transformers and are named according to the function. A model of a single-phase transformer AC-AC type with half-wave and full-wave quality has been proposed. Its output is controlled by power, voltage and current, which is considered an input to the load. The fixed input transformer has a variable output according to the required power, voltage and current. Inverters of this type have so many uses that they are used in many different applications, including industrial, induction motor speed control, military, medical and household, including low-light circuits, among others. A simulation involving different types of single-phase AC transformers is proposed. The models were built in two ways, the first using a diode as an electronic switch, and the second using a thyristor. Different values for the load were chosen by adopting three values of 30 ohms, 40 ohms, and 50 ohms. An alternating power supply with an RMS value of 222 volts. Simulation was carried out after modeling to test the performance of the proposed transformer and its various modes of operation. Simulation models confirmed and reinforced the working theories of the proposed structures. From the results, we can reach the possibility of changing the voltage and power values using the electronic transformer by using the frequency of closing and opening the electronic keys within specific periods according to the proposed model, which can be represented or modified.

In this research a fuzzy neural network is proposed so, fuzzy mechanism and adaptive neuro fuzzy mechanism are designed and simulated to control the (flow rate) control action on cell multiplexing in (ATM). The cell flow rate on the output of neural- fuzzy controller. Has been simulated depending on the input variables, one of these inputs is the queuing message (message length), the second one is the number of inputs, and third is the type of massage. These input variables are used to build the fuzzy rules uses (FNN) as its condition and the control action as its consequence, combines these rules to represent the model or system. NN is used as a training algorithm to learn the weights of fuzzy system. The simulation process has been executed by using (MATLAB). In the light of this research, it is apparent that NNS and fuzzy logic based systems can play an important role in the control of cell multiplexing in (ATM) network, since they can provide adaptive model free, real time control to the user.