Object-oriented programming characteristics

Simulation programs have been developed by using object-oriented-language C-b-f to evaluate the proposed system. Table 1 shows major exogenous vjiriables and parameters of simulation models, and the values of the exogenous vjuriables and parameters used for thermodynamic characteristics simulation. As shown in Teible 1, turbine inlet temperature is assumed to be 1473 K, condenser outlet pressure is 39.2 kPa (0.40 kg/cm ), and the fuel used is the natural gas composed of only methane. 

The characteristics of the system presented here requires a simulation tool which supports the decomposition into subsystems. With the parameters we used the system is stiff [6]. Algorithms for the numerical integration of stiff differential equations [5] and numerical libraries for solving nonlinear implicit equations like eq. (2.7) must be available. The simulation tool MATLAB/SIMULINK was used because it fulfils these requirements [11],[16]. Object-oriented visual programming helps to represent the model as shown in Fig. 2.3 and 2.4. The costly numerical solution of eq. (2.7) has been performed before the simulation and the results has been stored in a data field. 

This article provides an explanation of the characteristics and the benefits of OOP followed by a discussion of simple conceptual examples that highlight OOP features. The presentation is independent of specific programming languages or development environments. Real-world applications of OOP, along with more comprehensive coverage of the design of object-oriented systems can be found elsewhere,"" as can applications from the field of chemical process engineering. 

There are two problems in the algorithm previously discussed the fiict that only the position is calculated versus both the position and orientation, and that the object and proximity sensor characteristics are modeled as being spherical. Also, there is a limitation in the sensor frame orientations that will allow the least-squares program to converge, which is a result of developing the equations using triangulation. 

The main focus of this paper was on the pose estimation problem, which was to determine the position and object models, an algorithm based on a triangulation scheme was developed. The position of the object coordinate frame was found using a nonlinear kast-squares technique. Some of the problems with the software are the fact that only the position of the object is calculated versus both the position and orientation of the object, and that both the object to be grasped and the proximity sensor characteristics are modeled as spherical. This was done to make the equation development, and thus programming, simpler. 

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