A boundary Integral method is used to simulate spilling breakers. The bottom is also included in the introduced closed boundary and the problem is directly solved in the physical plane. The method has been shown to be remarkably stable, and no numerical instability has occurred in any of the calculations. The results reveal that both the momentum and total energy are almost constant in time during the simulation period. As a result, the breaking process of a spilling breaker is fairly well simulated.

The objective of this work is to develop deep theoretical methods that are based on the solution of the Integral boundary layer equations for investigating film cooling in liquid rocket engine. The Integral model assumes that heat is transferred from hot free stream gas to the liquid film both by convection and radiation. The mass is transferred to the free srteam gas by the well-known blowing process.Downstream of the liquid film, the gas effectiveness is obtained by solving boundary layer Integral equations. It incorporates a differential model for calorimeter mixing between liquid vapors in the boundary layer with the free stream gas entrained in the boundary layer. Comparisons with existing theoretical and experimental results indicate the film coating trends were well predicted by the present Integral model proposed by us.

In this paper, an optimal adaptive fuzzy Integral sliding mode control is presented to control the robot manipulator position tracking in the presence of uncertainties and permanent magnet DC motor. In the proposed control, sliding surface of the sliding mode control is defined according to the information of position tracking error, derivatives, and error Integral. In order to estimate bounds of the existing structured and unstructured uncertainties in the dynamics of the robot manipulator and the permanent magnet DC motor, a MIMO fuzzy adaptive approximator is designed. This helps to overcome the undesired chattering phenomenon in the control input by using fuzzy logic. Mathematical proof shows that the closed-loop system with the adaptive fuzzy Integral sliding mode control in the presence of all the uncertainties has the global asymptotic stability. Furthermore, modified harmony search optimization algorithm is used to define the input coefficients of the proposed control and also to reduce the control input amplitude. In order to validate performance of the proposed controller, a case study on the SCARA robot manipulator is conducted in the presence of permanent magnet DC motor. Results of the Simulation show desired performance of the proposed controller.

Plant development can be defined as a programmed qualitative change in plant form, which leads plant to maturity, and researchers call it as phasic development or phenology. Recognizing the timing of occurring each development stage is necessary for managing system in order to yield increment. The timing of occurring development stages depend on climate, genotype specifications and sowing date then determination of these times in different regions is difficult and it is only possible through the using of crop simulation models which can predict the timing of occurrence each development stage by integrating effective factors. The model was constructed based on linear equation of plant temperature response. In order to model evaluation two experiments were carried out in agricultural and natural resources research center of Khuzistan in 2003-2004 and 2004-2005 cropping years. Wheat development stages were determined based on Kirby and Appleyard’s scale by stereoscopic microscope and required GDD for each development stage as well. The constructed model was calibrated and run for simulation. Comparison of simulated and observed data showed that the model can strongly predict wheat development stages.

This study intends to investigate a new control structure using a model reference fuzzy controller based on state feedback Integral control. Motivated by the fact that most of the controlled systems are nonlinear and subject to uncertainty. Hence, designing control structures which can satisfy these cases is essential. The state feedback control is one of the control methods; however this method does not show an appropriate performance when the non-zero disturbance is applied to the system. To cope with the mentioned drawback, using an Integral control with state feedback would be an effective way. The classic state feedback Integral control is considered as a beneficial way to control of linear or weakly nonlinear systems. For this reason, this paper concerns state feedback Integral control using a model reference fuzzy controller. At the first stage of designed control approach, the nonlinear system is modeled by TS fuzzy. At the second stage, control method is discussed. The proposed controller is applicable to a broad class of nonlinear systems subject to non-zero disturbance. The simulation results applied to control of inverted pendulum, magnetic levitation and Chua's circuit systems, verify the high control accuracy and appropriate performance of the proposed controller.

In this research paper, we introduce a new transform belonging to the class of Laplace transforms, called the Yasser-Jassim Transform (YJ Transform). We explore its properties and compare it to the classical Laplace transform. Furthermore, we provide proofs for the key properties associated with this transform and demonstrate its application in solving differential and Integral equations. By employing this new transform, we can reduce the original problem to an algebraic equation that can be solved directly, followed by applying the inverse transform to obtain the solution to the original problem.