A virtual environment for evolutionary autonomous optimization of real time stochastic control design

The work leads with three dimensional environments for industrial processes visualization and the study of control parameters for the optimisation of real time systems simulation with evolutionary approach. The initial motivation behind the development of adaptive control models was the need to account for uncertainty in the parameters and structure of physical systems. When such a system to be controlled should be simulated by a computer with some stochastic model, then it is suitable to use evolutionary computing to determine automatically the role of each parameter on the system performance, what can lead to an advantage in the optimisation of some proposed automation model under study. Concurrently the use of virtual environments with the visualization of the model's performance in a three dimensional perspective could open the possibility for the user to taste some kind of immersion as close as possible into the reality of the system in simulation.