Temperature Control of a Solar Furnace with Exact Linearization and Off-Line Identification
The ability to predict the behavior of materials is crucial in several industries due to safety aspects, such as in high temperature furnaces for the production of glass, in the nuclear energy industry or in the high concentrated thermal solar systems. Solar furnaces use concentrated solar radiation that can be used to perform material stress tests with high temperatures. These devices have nonlinear dynamics that are caused by the actuator, the shutter, and by the interaction between the solar energy and the properties of the material. The contribution of this paper consists in the design of a controller for practical use based on the exact linearization method with off-line identification. The aim is to improve the controller performance to track the temperature profile. In this context it is assumed that the thermodynamic properties of the sample material to be tested are unknown.
Predictive adaptive temperature control in a solar furnace for material stress tests
This paper explores the adaptive predictive Musmar algorithm to control the temperature of material samples in a solar furnace. Solar furnaces are devices that are powered by concentrated solar energy and are used in material stress applications. Solar furnaces are characterized by having a nonlinear dynamics, the nonlinear effect between the incident energy and the temperature of the sample, the nonlinear relation between the positioning of the shutter and the incident power applied on the sample, the interaction between the shutter dynamics and the temperature dynamics of the sample and the presence of fast perturbations on sunlight induced by clouds. This work is being developed in the framework of the SFERA project, to automate material stress experiments in solar furnaces of the Odeillo Processes Materials and Solar Energy Laboratory, located at the Oriental Pyrenees in the South of France.
Convergence Anatomization of Aquaculture Production in Leading Fish-Producing Countries During the Period of 1997-2013
Growth and national importance of aquaculture production is empirically assessed as an important indicator of development. The present article aims to test whether the major aquaculture producing countries of the world are converging over time. The authors have applied the absolute and conditional beta convergence and sigma convergence approaches on the data of FAO for the period 1997-2013. The results show that there is an absolute beta convergence and sigma convergence among 25 major aquaculture producing countries; negative sign of coefficient of conditional beta convergence with per capita income is also noticed. It implies, the growth rates of aquaculture for developed nations are declining with rise in per capita income and backward fish-intensive countries are catching up with the giant producers like China and India. The cross-country variations are also going down which means that the countries' development gaps are getting narrowed by means of growth of aquaculture resources.