Parallel processing applied for scientific visualization of industrial adaptive control simulation

Simulation and modelling intelligent autonomous systems often involves extremely complex analyses. It is specially true when the model is addressed for dynamic stochastic systems, which should be required to operate in real time for a chemical industry. For this purpose the use of virtual environment and the respective visualization of control parameters can lead to an advantage for a proposed automation model under study. We describe the system simulation focusing on the virtual environment with its mathematical visualization and the control optimisation, which shows an adaptive control model applied to a study case. Furthermore is presented also the use of parallel processing for computer graphics in virtual environments and scientific visualization. Such approach turns possible not only the immersion of the user in a proposed simulator model but also a better insight about parameters correlation for the manufacturing control in real time.