Constrained Nonlinear Model Predictive Control of an MMA Polymerization Process via Evolutionary Optimization

In this work, a nonlinear model predictive controller is developed for a batch polymerization process. The physical model of the process is parameterized along a desired trajectory resulting in a trajectory linearized piecewise model (a multiple linear model bank) and the parameters are identified for an experimental polymerization reactor. Then, a multiple model adaptive predictive controller is designed for thermal trajectory tracking of the MMA polymerization. The input control signal to the process is constrained by the maximum thermal power provided by the heaters. The constrained optimization in the model predictive controller is solved via genetic algorithms to minimize a DMC cost function in each sampling interval.Comment: 12 pages, 9 figures, 28 reference

Smartdevices development for visual impairment and colour vision deficiency

The research concerns with the development of an app-based system to assist those with vision impairment to better interact with mobile phones and computers achieving maximum advantages. In particular, the system helps to detect colour deficiency and can automatically adjust view screens to increase contrast and arrive at optimal view result. Preliminary results when asking observers to evaluate the system demonstrate the advantages of the developed software system