Verification of periodically controlled hybrid systems: Application to an autonomous vehicle

This article introduces Periodically Controlled Hybrid Automata (PCHA) for modular specification of embedded control systems. In a PCHA, control actions that change the control input to the plant occur roughly periodically, while other actions that update the state of the controller may occur in the interim. Such actions could model, for example, sensor updates and information received from higher-level planning modules that change the set point of the controller. Based on periodicity and subtangential conditions, a new sufficient condition for verifying invariant properties of PCHAs is presented. For PCHAs with polynomial continuous vector fields, it is possible to check these conditions automatically using, for example, quantifier elimination or sum of squares decomposition. We examine the feasibility of this automatic approach on a small example. The proposed technique is also used to manually verify safety and progress properties of a fairly complex planner-controller subsystem of an autonomous ground vehicle. Geometric properties of planner-generated paths are derived which guarantee that such paths can be safely followed by the controller. © 2012 ACM.

Organic-inorganic hybrid material for the cells immobilization: Long-term viability mechanism and application in BOD sensors

In this paper, organic-inorganic hybrid material, which is composed of silica and the grafting copolymer of poly (vinyl alcohol) and 4-vinylpyridine (PVA-g-P(4-VP)), was employed to immobilize Trichosporon cutaneum strain 2.570 cells. Cells entrapped into the hybrid material were found to keep a long-term viability. The mechanism of such a long-term viability was investigated by using confocal laser scanning microscopy (CLSM). Our studies revealed that arthroconidia produced in the extracellular material might play an important role in keeping the long-term viability of the immobilized microorganism. After the arthroconidia were activated, an electrochemical biochemical oxygen demand (BOD) sensor based on cell/hybrid material-modified supporting membrane was constructed for verifying the proposed mechanism.

Gold/platinum hybrid nanoparticles supported on multiwalled carbon nanotube/silica coaxial nanocables: Preparation and application as electrocatalysts for oxygen reduction

A simple approach combining sonication and sol-gel chemistry was employed to synthesize silica coated carbon nanotube (CNTs) coaxial nanocables. It was found that a homogeneous silica layer can be coated on the surface of the CNTs. This method is simple, rapid, and reproducible. Furthermore, gold nanoparticle supported coaxial nanocables were facilely obtained using amino-functionalized silica as the interlinker. Furthermore, to reduce the cost of Pt in fuel cells, designing a Pt shell on the surface of a noble metal such as gold or silver is necessary. High-density gold/platinum hybrid nanoparticles were located on the surface of I-D coaxial nanocables with high surface-to-volume ratios. It was found that this hybrid nanomaterial exhibits a high electrocatalytic activity for enhancing oxygen reduction (low overpotential associated with the oxygen reduction reaction and almost four-electron electroreduction of dioxygen to water).

Noncovalent functionalization of multiwalled carbon nanotubes: Application in hybrid nanostructures

We developed a reproducible, noncovalent strategy to functionalize multiwalled carbon nanotubes (MWNTs) via embedding nanotubes in polysiloxane shells. (3-Aminopropyl)triethoxysilane molecules adsorbed to the nanotube surfaces via hydrophobic interactions are polymerized simply by acid catalysis and form a thin polysiloxane layer. On the basis of the embedded MWNTs, negatively charged gold nanoparticles are anchored to the nanotube surfaces via electrostatic interactions between the protonated amino groups and the gold nanoparticles. Furthermore, these gold nanoparticles can further grow and magnify along the nanotubes through heating in HAuCl4 aqueous solution at 100 degrees C; as a result these nanoparticles are joined to form continuous gold nanowires with MWNTS acting as templates.

Improving fuel economy application of the organic Rankine Cycle on a hybrid bus

Globally vehicle operators are experiencing rising fuel costs and increased
running expenses as governments around the world attempt to decrease carbon dioxide emissions and fossil fuel consumption, due to global warming and the drive to reduce dependency on fossil fuels. Recent advances in hybrid vehicle design have made great strides towards more efficient operation, with regenerative braking being widely used to capture otherwise lost energy. In this paper a hybrid series bus is developed a step further, by installing another method of energy capture on the vehicle. In this case, it is in the form of the Organic Rankine Cycle (ORC). The waste heat expelled to the exhaust and coolant streams is recovered and converted to electrical energy which is then stored in the hybrid vehicles batteries. The electrical energy can then be used for the auxiliary power circuit or to assist in vehicle propulsion, thus reducing the load on the engine, thereby improving the overall fuel economy of the vehicle and reducing carbon dioxide emissions.

Nanoporous carbons from sisal residues and their application in hybrid TiO2/carbon photocatalysts for the removal and degradation of phenol in solution

Tese de doutoramento, Química (Química Tecnológica), Universidade de Lisboa, Faculdade de Ciências, 2016

Synthesis of Zinc oxide nanorods via conductive polymeric template and its potential application in hybrid solar cells.

Tesis (Doctorado en Ciencias con orientación en Química de los Materiales) UANL, 2014.

Application of neural network to hybrid systems with binary inputs

Boolean input systems are in common used in the electric industry. Power supplies include such systems and the power converter represents these. For instance, in power electronics, the control variable are the switching ON and OFF of components as thyristors or transistors. The purpose of this paper is to use neural network (NN) to control continuous systems with Boolean inputs. This method is based on classification of system variations associated with input configurations. The classical supervised backpropagation algorithm is used to train the networks. The training of the artificial neural network and the control of Boolean input systems are presented. The design procedure of control systems is implemented on a nonlinear system. We apply those results to control an electrical system composed of an induction machine and its power converter.