Robot Manipulator Systems: Analysis and Control

Manipulator systems are rather complex and highly nonlinear which makes difficult their analysis and control. Classic system theory is veil known, however it is inadequate in the presence of strong nonlinear dynamics. Nonlinear controllers produce good results [1] and work has been done e. g. relating the manipulator nonlinear dynamics with frequency response [2–5]. Nevertheless, given the complexity of the problem, systematic methods which permit to draw conclusions about stability, imperfect modelling effects, compensation requirements, etc. are still lacking. In section 2 we start by analysing the variation of the poles and zeros of the descriptive transfer functions of a robot manipulator in order to motivate the development of more robust (and computationally efficient) control algorithms. Based on this analysis a new multirate controller which is an improvement of the well known “computed torque controller” [6] is announced in section 3. Some research in this area was done by Neuman [7,8] showing tbat better robustness is possible if the basic controller structure is modified. The present study stems from those ideas, and attempts to give a systematic treatment, which results in easy to use standard engineering tools. Finally, in section 4 conclusions are presented.

Ciencias de la complejidad: estado actual

Los aportes teóricos y aplicados de la complejidad en economía han tomado tantas direcciones y han sido tan frenéticos en las últimas décadas, que no existe un trabajo reciente, hasta donde conocemos, que los compile y los analice de forma integrada. El objetivo de este proyecto, por tanto, es desarrollar un estado situacional de las diferentes aplicaciones conceptuales, teóricas, metodológicas y tecnológicas de las ciencias de la complejidad en la economía. Asimismo, se pretende analizar las tendencias recientes en el estudio de la complejidad de los sistemas económicos y los horizontes que las ciencias de la complejidad ofrecen de cara al abordaje de los fenómenos económicos del mundo globalizado contemporáneo.

Onboard and real-time artificial satellite orbit determination using GPS

An algorithm for real-time and onboard orbit determination applying the Extended Kalman Filter (EKF) method is developed. Aiming at a very simple and still fairly accurate orbit determination, an analysis is performed to ascertain an adequacy of modeling complexity versus accuracy. The minimum set of to-be-estimated states to reach the level of accuracy of tens of meters is found to have at least the position, velocity, and user clock offset components. The dynamical model is assessed through several tests, covering force model, numerical integration scheme and step size, and simplified variational equations. The measurement model includes only relevant effects to the order of meters. The EKF method is chosen to be the simplest real-time estimation algorithm with adequate tuning of its parameters. In the developed procedure, the obtained position and velocity errors along a day vary from 15 to 20 m and from 0.014 to 0.018 m/s, respectively, with standard deviation from 6 to 10 m and from 0.006 to 0.008 m/s, respectively, with the SA either on or off. The results, as well as analysis of the final adopted models used, are presented in this work. © 2013 Ana Paula Marins Chiaradia et al.

Um novo modelo de transformadores trifásicos para análise harmônica trifásica em sistemas de distribuição

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

MODEL UPDATING AND STRUCTURAL HEALTH MONITORING OF HORIZONTAL AXIS WIND TURBINES VIA ADVANCED SPINNING FINITE ELEMENTS AND STOCHASTIC SUBSPACE IDENTIFICATION METHODS

Wind energy has been one of the most growing sectors of the nation’s renewable energy portfolio for the past decade, and the same tendency is being projected for the upcoming years given the aggressive governmental policies for the reduction of fossil fuel dependency. Great technological expectation and outstanding commercial penetration has shown the so called Horizontal Axis Wind Turbines (HAWT) technologies. Given its great acceptance, size evolution of wind turbines over time has increased exponentially. However, safety and economical concerns have emerged as a result of the newly design tendencies for massive scale wind turbine structures presenting high slenderness ratios and complex shapes, typically located in remote areas (e.g. offshore wind farms). In this regard, safety operation requires not only having first-hand information regarding actual structural dynamic conditions under aerodynamic action, but also a deep understanding of the environmental factors in which these multibody rotating structures operate. Given the cyclo-stochastic patterns of the wind loading exerting pressure on a HAWT, a probabilistic framework is appropriate to characterize the risk of failure in terms of resistance and serviceability conditions, at any given time. Furthermore, sources of uncertainty such as material imperfections, buffeting and flutter, aeroelastic damping, gyroscopic effects, turbulence, among others, have pleaded for the use of a more sophisticated mathematical framework that could properly handle all these sources of indetermination. The attainable modeling complexity that arises as a result of these characterizations demands a data-driven experimental validation methodology to calibrate and corroborate the model. For this aim, System Identification (SI) techniques offer a spectrum of well-established numerical methods appropriated for stationary, deterministic, and data-driven numerical schemes, capable of predicting actual dynamic states (eigenrealizations) of traditional time-invariant dynamic systems. As a consequence, it is proposed a modified data-driven SI metric based on the so called Subspace Realization Theory, now adapted for stochastic non-stationary and timevarying systems, as is the case of HAWT’s complex aerodynamics. Simultaneously, this investigation explores the characterization of the turbine loading and response envelopes for critical failure modes of the structural components the wind turbine is made of. In the long run, both aerodynamic framework (theoretical model) and system identification (experimental model) will be merged in a numerical engine formulated as a search algorithm for model updating, also known as Adaptive Simulated Annealing (ASA) process. This iterative engine is based on a set of function minimizations computed by a metric called Modal Assurance Criterion (MAC). In summary, the Thesis is composed of four major parts: (1) development of an analytical aerodynamic framework that predicts interacted wind-structure stochastic loads on wind turbine components; (2) development of a novel tapered-swept-corved Spinning Finite Element (SFE) that includes dampedgyroscopic effects and axial-flexural-torsional coupling; (3) a novel data-driven structural health monitoring (SHM) algorithm via stochastic subspace identification methods; and (4) a numerical search (optimization) engine based on ASA and MAC capable of updating the SFE aerodynamic model.

Modeling soil system: complexity under your feet

A clear statement in these lines textually cited (Byers et al., 1938) defines the framework of this special issue: “True soil is the product of the action of climate and living organism upon the parent material, as conditioned by the local relief. The length of time during which these forces are operative is of great importance in determining the character of the ultimate product. Drainage conditions are also important and are controlled by local relief, by the nature of the parent material or underlying rock strata, or by the amount of precipitation in relation to rate of percolation and runoff water. There are, therefore, five principal factors of soil formation: Parent material, climate, biological activity, relief and time. These soil forming factors are interdependent, each modifying the effectiveness of the others.” Due to these various processes associated to its formation and genesis soil dynamics reveals high complexity that creates several levels of structure using this term in a broad sense

Improving novice analyst performance in modeling the sequence diagram in systems analysis: A cognitive complexity approach

The Unified Modeling Language (UML) has quickly become the industry standard for object-oriented software development. It is being widely used in organizations and institutions around the world. However, UML is often found to be too complex for novice systems analysts. Although prior research has identified difficulties novice analysts encounter in learning UML, no viable solution has been proposed to address these difficulties. Sequence-diagram modeling, in particular, has largely been overlooked. The sequence diagram models the behavioral aspects of an object-oriented software system in terms of interactions among its building blocks, i.e. objects and classes. It is one of the most commonly-used UML diagrams in practice. However, there has been little research on sequence-diagram modeling. The current literature scarcely provides effective guidelines for developing a sequence diagram. Such guidelines will be greatly beneficial to novice analysts who, unlike experienced systems analysts, do not possess relevant prior experience to easily learn how to develop a sequence diagram. There is the need for an effective sequence-diagram modeling technique for novices. This dissertation reports a research study that identified novice difficulties in modeling a sequence diagram and proposed a technique called CHOP (CHunking, Ordering, Patterning), which was designed to reduce the cognitive load by addressing the cognitive complexity of sequence-diagram modeling. The CHOP technique was evaluated in a controlled experiment against a technique recommended in a well-known textbook, which was found to be representative of approaches provided in many textbooks as well as practitioner literatures. The results indicated that novice analysts were able to perform better using the CHOP technique. This outcome seems have been enabled by pattern-based heuristics provided by the technique. Meanwhile, novice analysts rated the CHOP technique more useful although not significantly easier to use than the control technique. The study established that the CHOP technique is an effective sequence-diagram modeling technique for novice analysts.

Improving Novice Analyst Performance in Modeling the Sequence Diagram in Systems Analysis: A Cognitive Complexity Approach

The Unified Modeling Language (UML) has quickly become the industry standard for object-oriented software development. It is being widely used in organizations and institutions around the world. However, UML is often found to be too complex for novice systems analysts. Although prior research has identified difficulties novice analysts encounter in learning UML, no viable solution has been proposed to address these difficulties. Sequence-diagram modeling, in particular, has largely been overlooked. The sequence diagram models the behavioral aspects of an object-oriented software system in terms of interactions among its building blocks, i.e. objects and classes. It is one of the most commonly-used UML diagrams in practice. However, there has been little research on sequence-diagram modeling. The current literature scarcely provides effective guidelines for developing a sequence diagram. Such guidelines will be greatly beneficial to novice analysts who, unlike experienced systems analysts, do not possess relevant prior experience to easily learn how to develop a sequence diagram. There is the need for an effective sequence-diagram modeling technique for novices. This dissertation reports a research study that identified novice difficulties in modeling a sequence diagram and proposed a technique called CHOP (CHunking, Ordering, Patterning), which was designed to reduce the cognitive load by addressing the cognitive complexity of sequence-diagram modeling. The CHOP technique was evaluated in a controlled experiment against a technique recommended in a well-known textbook, which was found to be representative of approaches provided in many textbooks as well as practitioner literatures. The results indicated that novice analysts were able to perform better using the CHOP technique. This outcome seems have been enabled by pattern-based heuristics provided by the technique. Meanwhile, novice analysts rated the CHOP technique more useful although not significantly easier to use than the control technique. The study established that the CHOP technique is an effective sequence-diagram modeling technique for novice analysts.

Hybrid modeling of convective laminar flow in a permeable tube associated with the cross-flow process

The confined flows in tubes with permeable surfaces arc associated to tangential filtration processes (microfiltration or ultrafiltration). The complexity of the phenomena do not allow for the development of exact analytical solutions, however, approximate solutions are of great interest for the calculation of the transmembrane outflow and estimate of the concentration, polarization phenomenon. In the present work, the generalized integral transform technique (GITT) was employed in solving the laminar and permanent flow in permeable tubes of Newtonian and incompressible fluid. The mathematical formulation employed the parabolic differential equation of chemical species conservation (convective-diffusive equation). The velocity profiles for the entrance region flow, which are found in the connective terms of the equation, were assessed by solutions obtained from literature. The velocity at the permeable wall was considered uniform, with the concentration at the tube wall regarded as variable with an axial position. A computational methodology using global error control was applied to determine the concentration in the wall and concentration boundary layer thickness. The results obtained for the local transmembrane flux and the concentration boundary layer thickness were compared against others in literature. (C) 2007 Elsevier B.V. All rights reserved.

Optimization and Complexity Reduction of Switch-Reconfigured Antennas Using Graph Models

This letter addresses the optimization and complexity reduction of switch-reconfigured antennas. A new optimization technique based on graph models is investigated. This technique is used to minimize the redundancy in a reconfigurable antenna structure and reduce its complexity. A graph modeling rule for switch-reconfigured antennas is proposed, and examples are presented.

Modeling of transpiration reduction in van Genuchten-Mualem type soils

We derive an analytic expression for the matric flux potential (M) for van Genuchten-Mualem (VGM) type soils which can also be written in terms of a converging infinite series. Considering the first four terms of this series, the accuracy of the approximation was verified by comparing it to values of M estimated by numerical finite difference integration. Using values of the parameters for three soils from different texture classes, the proposed four-term approximation showed an almost perfect match with the numerical solution, except for effective saturations higher than 0.9. Including more terms reduced the discrepancy but also increased the complexity of the equation. The four-term equation can be used for most applications. Cases with special interest in nearly saturated soils should include more terms from the infinite series. A transpiration reduction function for use with the VGM equations is derived by combining the derived expression for M with a root water extraction model. The shape of the resulting reduction function and its dependency on the derivative of the soil hydraulic diffusivity D with respect to the soil water content theta is discussed. Positive and negative values of dD/d theta yield concave and convex or S-shaped reduction functions, respectively. On the basis of three data sets, the hydraulic properties of virtually all soils yield concave reduction curves. Such curves based solely on soil hydraulic properties do not account for the complex interactions between shoot growth, root growth, and water availability.

Topological Complexity and Predictability in the Dynamics of a Tumor Growth Model with Shilnikov's Chaos

Dynamical systems modeling tumor growth have been investigated to determine the dynamics between tumor and healthy cells. Recent theoretical investigations indicate that these interactions may lead to different dynamical outcomes, in particular to homoclinic chaos. In the present study, we analyze both topological and dynamical properties of a recently characterized chaotic attractor governing the dynamics of tumor cells interacting with healthy tissue cells and effector cells of the immune system. By using the theory of symbolic dynamics, we first characterize the topological entropy and the parameter space ordering of kneading sequences from one-dimensional iterated maps identified in the dynamics, focusing on the effects of inactivation interactions between both effector and tumor cells. The previous analyses are complemented with the computation of the spectrum of Lyapunov exponents, the fractal dimension and the predictability of the chaotic attractors. Our results show that the inactivation rate of effector cells by the tumor cells has an important effect on the dynamics of the system. The increase of effector cells inactivation involves an inverse Feigenbaum (i.e. period-halving bifurcation) scenario, which results in the stabilization of the dynamics and in an increase of dynamics predictability. Our analyses also reveal that, at low inactivation rates of effector cells, tumor cells undergo strong, chaotic fluctuations, with the dynamics being highly unpredictable. Our findings are discussed in the context of tumor cells potential viability.

Modeling Movement of Tourists : Tools and Application in São Miguel Island, Portugal

Tourism contributes to the development of many regions. Different factors affect the movement of tourists within a destination. Those factors are related to the tourist characteristics, like the time budgets, preferences or destination knowledge, and to the destination features, like the attraction characteristics or accessibility level. Tourist decisions aren’t always done in a rational way. Emotions add further complexity to the human decision process. The use of footpaths can play an important role in the satisfaction of tourists, helping them discover the territory and giving them access to different types of attractions. The existence of a mathematical model that integrates the main factors related to the movement of independent tourists within a destination, in a dynamic way, will make possible the creation of an adaptable software tool. This tool will meet the specific needs of tourists, allowing the use of the network in an optimal way by the different tourist profiles, and the needs of the regional government and business, permitting better decisions and the offer of relevant tourism products. This article identifies the main tourists’ mobility criteria in the São Miguel island territory, Azores, Portugal, recognizes the necessary modelling process and identifies the basis for the construction of the mathematical model that explains the movement of tourists within the destination.

Modeling for control design of a multi-reach water canal

This article addresses the problem of obtaining reduced complexity models of multi-reach water delivery canals that are suitable for robust and linear parameter varying (LPV) control design. In the first stage, by applying a method known from the literature, a finite dimensional rational transfer function of a priori defined order is obtained for each canal reach by linearizing the Saint-Venant equations. Then, by using block diagrams algebra, these different models are combined with linearized gate models in order to obtain the overall canal model. In what concerns the control design objectives, this approach has the advantages of providing a model with prescribed order and to quantify the high frequency uncertainty due to model approximation. A case study with a 3-reach canal is presented, and the resulting model is compared with experimental data. © 2014 IEEE.

Correlation modeling for a distributed scalable video codec based on the HEVC standard

The growing heterogeneity of networks, devices and consumption conditions asks for flexible and adaptive video coding solutions. The compression power of the HEVC standard and the benefits of the distributed video coding paradigm allow designing novel scalable coding solutions with improved error robustness and low encoding complexity while still achieving competitive compression efficiency. In this context, this paper proposes a novel scalable video coding scheme using a HEVC Intra compliant base layer and a distributed coding approach in the enhancement layers (EL). This design inherits the HEVC compression efficiency while providing low encoding complexity at the enhancement layers. The temporal correlation is exploited at the decoder to create the EL side information (SI) residue, an estimation of the original residue. The EL encoder sends only the data that cannot be inferred at the decoder, thus exploiting the correlation between the original and SI residues; however, this correlation must be characterized with an accurate correlation model to obtain coding efficiency improvements. Therefore, this paper proposes a correlation modeling solution to be used at both encoder and decoder, without requiring a feedback channel. Experiments results confirm that the proposed scalable coding scheme has lower encoding complexity and provides BD-Rate savings up to 3.43% in comparison with the HEVC Intra scalable extension under development. © 2014 IEEE.