An innovative approach of model order reduction using ant colony optimization
In this paper, a generic solution in the area of model order reduction is presented. The proposed method is based on artificial intelligence, which depends on a probabilistic optimization algorithm called Ant Colony. This approach aims to obtain a reduced-order model out of a relatively complex model represented as a transfer function. This reduced order model is obtained in a reasonable run time. It has acceptable error in time domain represented by the unit step time response, and the least error in frequency domain represented by Bode plot compared to other conventional methods in model order reduction regardless the targeted transfer function.
Model order reduction using genetic algorithm
Model order reduction has been one of the most challenging topics in the past years. Conventional mathematical methods have been used to obtain a reduced order model of high order complex models. In this paper, genetic algorithm (GA) which is one of the artificial intelligence algorithms is used to approximate high-order transfer functions (TFs) as lower-order TFs. Genetic algorithm is considered as one of the evolutionary techniques which are used in optimization problems. In this approach, genetic algorithm is applied to model order reduction putting in consideration improving accuracy and preserving the properties of the original model which are two important issues for improving the performance of simulation and computation and maintaining the behavior of the original complex models being reduced. The proposed technique could be used in EDA tools.
Urea removal strategies for dialysate regeneration in a wearable artificial kidney.
The availability of a wearable artificial kidney (WAK) that provides dialysis outside the hospital would be an important advancement for dialysis patients. The concept of a WAK is based on regeneration of a small volume of dialysate in a closed-loop. Removal of urea, the primary waste product of nitrogen metabolism, is the major challenge for the realization of a WAK since it is a molecule with low reactivity that is difficult to adsorb while it is the waste solute with the highest daily molar production. Currently, no efficient urea removal technology is available that allows for miniaturization of the WAK to a size and weight that is acceptable for patients to carry. Several urea removal strategies have been explored, including enzymatic hydrolysis by urease, electro-oxidation and sorbent systems. However, thus far, these methods have toxic side effects, limited removal capacity or slow removal kinetics. This review discusses different urea removal strategies for application in a wearable dialysis device, from both a chemical and a medical perspective.