An automated maneuver control framework for a remotely operated vehicle

OCEANS, 2001. MTS/IEEE Conference and Exhibition (Volume:2 )

An Optimal Control Framework for Resources Management in Agriculture

An optimal control framework to support the management and control of resources in a wide range of problems arising in agriculture is discussed. Lessons extracted from past research on the weed control problem and a survey of a vast body of pertinent literature led to the specification of key requirements to be met by a suitable optimization framework. The proposed layered control structure—including planning, coordination, and execution layers—relies on a set of nested optimization processes of which an “infinite horizon” Model Predictive Control scheme plays a key role in planning and coordination. Some challenges and recent results on the Pontryagin Maximum Principle for infinite horizon optimal control are also discussed.

System for robot control inspired by the functionality and organisation of the human nervous system

This paper presents a model of a control system for robot systems inspired by the functionality and organisation of human neuroregulatory system. Our model was specified using software agents within a formal framework and implemented through Web Services. This approach allows the implementation of the control logic of a robot system with relative ease, in an incremental way, using the addition of new control centres to the system as its behaviour is observed or needs to be detailed with greater precision, without the need to modify existing functionality. The tests performed verify that the proposed model has the general characteristics of biological systems together with the desirable features of software, such as robustness, flexibility, reuse and decoupling.

Per-antenna rate and power control for MIMO layered architectures in the low- and high-power regimes

In a MIMO layered architecture, several codewordsare transmitted from a multiplicity of antennas. Although thespectral efficiency is maximized if the rates of these codewordsare separately controlled, the feedback rate within the linkadaptation loop is reduced if they are constrained to be identical.This poses a direct tradeoff between performance andfeedback overhead. This paper provides analytical expressionsthat quantify the difference in spectral efficiency between bothapproaches for arbitrary numbers of antennas. Specifically, thecharacterization takes place in the realm of the low- and highpowerregimes via expansions that are shown to have a widerange of validity.In addition, the possibility of adjusting the transmit powerof each codeword individually is considered as an alternative tothe separate control of their rates. Power allocation, however,turns out to be inferior to rate control within the context of thisproblem.

Dispersion and size control of layered double hydroxide nanoparticles in aqueous solutions

We report a simple but efficient method to prepare stable homogeneous suspensions containing monodispersed MgAl layered double hydroxide (LDH) nanoparticles that have wide promising applications in cellular drug ( gene) delivery, polymer/LDH nanocomposites, and LDH thin films for catalysis, gas separation, sensing, and electrochemical materials. This new method involves a fast coprecipitation followed by controlled hydrothermal treatment under different conditions and produces stable homogeneous LDH suspensions under variable hydrothermal treatment conditions. Moreover, the relationship between the LDH particle size and the hydrothermal treatment conditions ( time, temperature, and concentration) has been systematically investigated, which indicates that the LDH particle size can be precisely controlled between 40 and 300 nm by adjusting these conditions. The reproducibility of making the identical suspensions under identical conditions has been confirmed with a number of experiments. The dispersion of agglomerated LDH aggregates into individual LDH crystallites during the hydrothermal treatment has been further discussed. This method has also been successfully applied to preparing stable homogeneous LDH suspensions containing various other metal ions such as Ni2+, Fe2+, Fe3+, Co2+, Cd2+, and Gd3+ in the hydroxide layers and many inorganic anions such as Cl-, CO32-, NO3-, and SO42-.

Layered smart grid architecture approach and field tests by ZigBee technology

This paper presents a layered Smart Grid architecture enhancing security and reliability, having the ability to act in order to maintain and correct infrastructure components without affecting the client service. The architecture presented is based in the core of well design software engineering, standing upon standards developed over the years. The layered Smart Grid offers a base tool to ease new standards and energy policies implementation. The ZigBee technology implementation test methodology for the Smart Grid is presented, and provides field tests using ZigBee technology to control the new Smart Grid architecture approach. (C) 2014 Elsevier Ltd. All rights reserved.

Capacity-approaching rate function for layered multiantenna architectures

The simultaneous use of multiple transmit and receive antennas can unleash very large capacity increases in rich multipath environments. Although such capacities can be approached by layered multi-antenna architectures with per-antenna rate control, the need for short-term feedback arises as a potential impediment, in particular as the number of antennas—and thus the number of rates to be controlled—increases. What we show, however, is that the need for short-term feedback in fact vanishes as the number of antennas and/or the diversity order increases. Specifically, the rate supported by each transmit antenna becomes deterministic and a sole function of the signal-to-noise, the ratio of transmit and receive antennas, and the decoding order, all of which are either fixed or slowly varying. More generally, we illustrate -through this specific derivation— the relevance of some established random CDMA results to the single-user multi-antenna problem.

Feature Selection and Classification Using Age Layered Population Structure Genetic Programming

The curse of dimensionality is a major problem in the fields of machine learning, data mining and knowledge discovery. Exhaustive search for the most optimal subset of relevant features from a high dimensional dataset is NP hard. Sub–optimal population based stochastic algorithms such as GP and GA are good choices for searching through large search spaces, and are usually more feasible than exhaustive and deterministic search algorithms. On the other hand, population based stochastic algorithms often suffer from premature convergence on mediocre sub–optimal solutions. The Age Layered Population Structure (ALPS) is a novel metaheuristic for overcoming the problem of premature convergence in evolutionary algorithms, and for improving search in the fitness landscape. The ALPS paradigm uses an age–measure to control breeding and competition between individuals in the population. This thesis uses a modification of the ALPS GP strategy called Feature Selection ALPS (FSALPS) for feature subset selection and classification of varied supervised learning tasks. FSALPS uses a novel frequency count system to rank features in the GP population based on evolved feature frequencies. The ranked features are translated into probabilities, which are used to control evolutionary processes such as terminal–symbol selection for the construction of GP trees/sub-trees. The FSALPS metaheuristic continuously refines the feature subset selection process whiles simultaneously evolving efficient classifiers through a non–converging evolutionary process that favors selection of features with high discrimination of class labels. We investigated and compared the performance of canonical GP, ALPS and FSALPS on high–dimensional benchmark classification datasets, including a hyperspectral image. Using Tukey’s HSD ANOVA test at a 95% confidence interval, ALPS and FSALPS dominated canonical GP in evolving smaller but efficient trees with less bloat expressions. FSALPS significantly outperformed canonical GP and ALPS and some reported feature selection strategies in related literature on dimensionality reduction.

Feature Selection and Classification Using Age Layered Population Structure Genetic Programming

The curse of dimensionality is a major problem in the fields of machine learning, data mining and knowledge discovery. Exhaustive search for the most optimal subset of relevant features from a high dimensional dataset is NP hard. Sub–optimal population based stochastic algorithms such as GP and GA are good choices for searching through large search spaces, and are usually more feasible than exhaustive and determinis- tic search algorithms. On the other hand, population based stochastic algorithms often suffer from premature convergence on mediocre sub–optimal solutions. The Age Layered Population Structure (ALPS) is a novel meta–heuristic for overcoming the problem of premature convergence in evolutionary algorithms, and for improving search in the fitness landscape. The ALPS paradigm uses an age–measure to control breeding and competition between individuals in the population. This thesis uses a modification of the ALPS GP strategy called Feature Selection ALPS (FSALPS) for feature subset selection and classification of varied supervised learning tasks. FSALPS uses a novel frequency count system to rank features in the GP population based on evolved feature frequencies. The ranked features are translated into probabilities, which are used to control evolutionary processes such as terminal–symbol selection for the construction of GP trees/sub-trees. The FSALPS meta–heuristic continuously refines the feature subset selection process whiles simultaneously evolving efficient classifiers through a non–converging evolutionary process that favors selection of features with high discrimination of class labels. We investigated and compared the performance of canonical GP, ALPS and FSALPS on high–dimensional benchmark classification datasets, including a hyperspectral image. Using Tukey’s HSD ANOVA test at a 95% confidence interval, ALPS and FSALPS dominated canonical GP in evolving smaller but efficient trees with less bloat expressions. FSALPS significantly outperformed canonical GP and ALPS and some reported feature selection strategies in related literature on dimensionality reduction.

A neural network enhanced generalized minimum variance self-tuning proportional, integral and derivative control algorithm for complex dynamic systems

A neural network enhanced proportional, integral and derivative (PID) controller is presented that combines the attributes of neural network learning with a generalized minimum-variance self-tuning control (STC) strategy. The neuro PID controller is structured with plant model identification and PID parameter tuning. The plants to be controlled are approximated by an equivalent model composed of a simple linear submodel to approximate plant dynamics around operating points, plus an error agent to accommodate the errors induced by linear submodel inaccuracy due to non-linearities and other complexities. A generalized recursive least-squares algorithm is used to identify the linear submodel, and a layered neural network is used to detect the error agent in which the weights are updated on the basis of the error between the plant output and the output from the linear submodel. The procedure for controller design is based on the equivalent model, and therefore the error agent is naturally functioned within the control law. In this way the controller can deal not only with a wide range of linear dynamic plants but also with those complex plants characterized by severe non-linearity, uncertainties and non-minimum phase behaviours. Two simulation studies are provided to demonstrate the effectiveness of the controller design procedure.

A comparative study of multilayered and single layered neural network based predictive controllers

The authors compare the performance of two types of controllers one based on the multilayered network and the other based on the single layered CMAC network (cerebellar model articulator controller). The neurons (information processing units) in the multi-layered network use Gaussian activation functions. The control scheme which is considered is a predictive control algorithm, along the lines used by Willis et al. (1991), Kambhampati and Warwick (1991). The process selected as a test bed is a continuous stirred tank reactor. The reaction taking place is an irreversible exothermic reaction in a constant volume reactor cooled by a single coolant stream. This reactor is a simplified version of the first tank in the two tank system given by Henson and Seborg (1989).

Vanadium Pentoxide Nanostructures: An Effective Control of Morphology and Crystal Structure in Hydrothermal Conditions

A systematic study was made of the synthesis of V(2)O(5)center dot nH(2)O nanostructures, whose morphologies, crystal structure, and amount of water molecules between the layered structures were regulated by strictly controlling the hydrothermal treatment variables. The synthesis involved a direct hydrothermal reaction between V(2)O(5) and H(2)O(2), without the addition of organic surfactant or inorganic ions. The experimental results indicate that high purity nanostructures can be obtained using this simple and clean synthetic route. Oil the basis of a study of hydrothermal treatment variables such as reaction temperature and time, X-ray diffraction (XRD) and scanning transmission electron microscopy (STEM) revealed that it was possible to obtain nanoribbons of the V(2)O(5)center dot nH(2)O monoclinic phase and nanowires or nanorods of the V(2)O(5)center dot nH(2)O orthorhombic phase. Thermal gravimetric analysis (TGA) shows also that the water content in the Structure call be controlled at appropriate hydrothermal conditions. Concerning the oxidation state of the vanadium atoms of as-obtained samples, a mixed-valence state composed of V(4+) and V(5+) was observed ill the V(2)O(5)center dot nH(2)O monoclinic phase, while the valence of the vanadium atoms was preferentially 5+ in the V(2)O(5)center dot nH(2)O orthorhombic phase. The X-ray absorption near-edge structure (XANES) results also indicated that the local structure of vanadium possessed a higher degree of symmetry in the V(2)O(5)center dot nH(2)O monoclinic phase.

Control of retention and fatigue-free characteristics in CaBi4Ti4O15 thin films prepared by chemical method

Ferroelectric CaBi4Ti4O15 (CBTi144) thin films were deposited on Pt/Ti/SiO2/Si substrates by the polymeric precursor method. The films present a single phase of layered-structured perovskite with polar axis orientation after annealing at 700 degrees C for 2 h in static air and oxygen atmosphere. The a/b-axis orientation of the ferroelectric film is considered to be associated with the preferred orientation of the Pt bottom electrode. It is noted that the films annealed in static air showed good polarization fatigue characteristics at least up to 10(10) bipolar pulse cycles and excellent retention properties up to 10(4) s. on the other hand, oxygen atmosphere seems to be crucial in the decrease of both, fatigue and retention characteristics of the capacitors. Independently of the applied electric field, the retained switchable polarization approached a nearly steady-state value after a retention time of 10 s. (C) 2006 Elsevier B.V. All rights reserved.

Controlled Synthesis of Layered Sn3O4 Nanobelts by Carbothermal Reduction Method and Their Gas Sensor Properties

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Orbital control on carbonate-lignite cycles on sediment core KAP-107 in the Ptolemais Basin, northern Greece

Time control is essential for the reconstruction of geological processes. We use a combination of relative and absolute methods to establish the chronology and related paleoclimatic processes for Late Neogene lacustrine sediment from the Ptolemais Basin, northern Greece. We determined changes in magnetic polarity and correlated them to the global magnetic polarity time scale, which again is calibrated by radiometric methods, to provide a low-resolution age model for the Upper Miocene to Lower Pliocene (7 - 3 Ma). Sedimentary successions show rhythmic alterations of lignites, clays, and marls. Using photospetrometry we measured this variability at 1-cm resolution, and correlated the pattern to known changes in earth's orbital parameters, namely to eccentricity and precession. For 230-m long borehole KAP-107 from the Amynteon Sub-Basin we obtained a high-resolution age model that spans 2 myr from 5.1 to 3.1 Ma, with age control points at insolation maxima (20-kyr resolution). We recommend using photospectrometry as reliable tool to establish orbital-based chronologies and to reconstruct paleoclimate variability at high resolution.