Using fractional derivatives for the joint ontrol of hexapod robots

This article studies several Fractional Order Control algorithms used for joint control of a hexapod robot. Both Padé and series approximations to the fractional derivative are considered for the control algorithm. The walking performance is evaluated through two indices: The mean absolute density of energy used per unit distance travelled, and the control effort. A set of simulation experiments reveals the influence of the different approximations upon the proposed indices. The results show that the fractional proportional and derivative algorithm, implemented using the Padé approximation with a small number of terms, gives the best results.

A historical perspective of legged robots

The objective of this paper is to present the evolution and the state-of-the-art in the area of legged locomotion systems. In a first phase different possibilities for implementing mobile robots are discussed, namely the case of artificial legged locomotion systems, while emphasizing their advantages and limitations. In a second phase a historical overview of the evolution of these systems is presented, bearing in mind several particular cases often considered as milestones of technological and scientific progress. After this historical timeline, some of the present-day systems are examined and their performance is analyzed. In a third phase the major areas of research and development that are presently being followed in the construction of legged robots are pointed out. Finally, some still unsolved problems that remain defying robotics research, are also addressed.

Control of a 6-DOF parallel manipulator through a mechatronic approach

This paper shows that a hierarchical architecture, distributing several control actions in growing levels of complexity and using resources of reconfigurable computing, enables one to take into account the ease of future modifications, updates and improvements in robotic applications. An experimental example of a Stewart—Gough platform control (a platform applied as the solution to countless practical problems) is presented using reconfigurable computing. The software and hardware developed are structured in independent blocks. This open architecture implementation allows easy expansion of the system and better adaptation of the platform to its related tasks.

Performance of fractional PID algorithms controlling nonlinear systems with saturation and backlash phenomena

The development of fractional-order controllers is currently one of the most promising fields of research. However, most of the work in this area addresses the case of linear systems. This paper reports on the analysis of fractional-order control of nonlinear systems. The performance of discrete fractional-order PID controllers in the presence of several nonlinearities is discussed. Some results are provided that indicate the superior robustness of such algorithms.

Analysis of the Van der Pol oscillator containing derivatives of fractional order

In this paper a modified version of the classical Van der Pol oscillator is proposed, introducing fractional-order time derivatives into the state-space model. The resulting fractional-order Van der Pol oscillator is analyzed in the time and frequency domains, using phase portraits, spectral analysis and bifurcation diagrams. The fractional-order dynamics is illustrated through numerical simulations of the proposed schemes using approximations to fractional-order operators. Finally, the analysis is extended to the forced Van der Pol oscillator.

Fractional central differences and derivatives

Journal of Vibration and Control, 14(9–10): 1255–1266, 2008

Paleoalterações e cimentações nos depósitos continentais terciários de Portugal central: importância na interpretação de processos antigos

This paper describes the palaeoweathering, cementation, clay minerals association and other closely related characteristics of central Portugal allostratigraphic Tertiary units (SLD's), that can be used for palaeoclimatic interpretation and palaeoenvironmental reconstruction. Lateral and vertical changes in palaeosols are of value for improving our understanding of the autocyclic and allocyclic controls on sediment acumulation in an alluvial basin, but they can also have stratigraphic importance. In some cases it is concluded that the geomorphological setting may have been more decisive than climatic conditions to the production of the palaeoweathering. During late Palaeogene (SLD7-8), surface and near-surface silicification were developed on tectonically stable land surfaces of minimal local relief under a semi-arid climate; groundwater flow was responsible for some eodiagenesis calcareous accumulations, with the neoformation of palygorskite. Conditions during the Miocene (SLD9-11) were favourable for the smectization of the metamorphic basement and arenization of granites. Intense rubefaction associated with basement conversion into clay (illite and kaolinite), is ascribed to internal drainage during late Messinian-Zanclean (SLD12). During Piacenzian (SLD13) intense kaolinization and hydromorphism are typical, reflecting a more humid and hot temperate climate and important Atlantic fluvial drainage. Later on (Gelasian-early Pleistocene ?; SLD14). more cold and dry conditicns are interpreted, at the beginning of the fluvial incision sage. Silica cementation is identified in the upper Eocence-Oligocene ? (SLD18; the major period of silicification), middle to upper Miocene (SLD10)and upper Tortonian-Messinian (SLD11); these occurrences are compatible with either arid or semi-arid conditions and the establishment of a flat landscape upon which a silcrete was developed.

Desenvolvimento e aluguer de software de faturação

As aplicações de Gestão ou Faturação são uma presença indispensável hoje em dia. Tendo o seu início nas aplicações “MS-DOS” em modo de texto, estas aplicações acompanharam a evolução dos sistemas operativos adotando um ambiente gráfico de forma natural. Se há poucos anos apenas as empresas com volumes de negócio significativo possuíam software de faturação, este foi sendo adotado por cada vez mais empresas e pequenos negócios. As alterações legislativas introduzidas desde 2011 conduziram a uma adoção generalizada por parte de pequenas e microempresas. O mercado de aplicações de gestão está saturado pelos grandes produtores de software nacionais: Primavera, Sage, etc. Estas aplicações, tendo sido construídas para PMEs (Pequenas e Médias Empresas) e mesmo grandes empresas, são excessivamente complexas e onerosas para muito pequenas e microempresas. O Modelo de negócio destes produtores de software é primordialmente a venda de Licenças e contratos de Manutenção, nalguns casos através de redes de Agentes. Este projeto teve como objetivo o desenvolvimento de uma Aplicação de Faturação, de baixo custo, simples e cross-platform para ser comercializada em regime de aluguer em Pequenas e Micro Empresas.

Efficient Legendre spectral tau algorithm for solving two-sided space-time Caputo fractional advection-dispersion equation

In this paper we present the operational matrices of the left Caputo fractional derivative, right Caputo fractional derivative and Riemann–Liouville fractional integral for shifted Legendre polynomials. We develop an accurate numerical algorithm to solve the two-sided space–time fractional advection–dispersion equation (FADE) based on a spectral shifted Legendre tau (SLT) method in combination with the derived shifted Legendre operational matrices. The fractional derivatives are described in the Caputo sense. We propose a spectral SLT method, both in temporal and spatial discretizations for the two-sided space–time FADE. This technique reduces the two-sided space–time FADE to a system of algebraic equations that simplifies the problem. Numerical results carried out to confirm the spectral accuracy and efficiency of the proposed algorithm. By selecting relatively few Legendre polynomial degrees, we are able to get very accurate approximations, demonstrating the utility of the new approach over other numerical methods.

State Space Analysis of Forest Fires

This paper studies forest fires from the perspective of dynamical systems. Burnt area, precipitation and atmospheric temperatures are interpreted as state variables of a complex system and the correlations between them are investigated by means of different mathematical tools. First, we use mutual information to reveal potential relationships in the data. Second, we adopt the state space portrait to characterize the system’s behavior. Third, we compare the annual state space curves and we apply clustering and visualization tools to unveil long-range patterns. We use forest fire data for Portugal, covering the years 1980–2003. The territory is divided into two regions (North and South), characterized by different climates and vegetation. The adopted methodology represents a new viewpoint in the context of forest fires, shedding light on a complex phenomenon that needs to be better understood in order to mitigate its devastating consequences, at both economical and environmental levels.

Limit Cycle Prediction of Systems with Fractional Controllers and Backlash

This article investigates the limit cycle (LC) prediction of systems with backlash by means of the describing function (DF) when using discrete fractional-order (FO) algorithms. The DF is an approximate method that gives good estimates of LCs. The implementation of FO controllers requires the use of rational approximations, but such realizations produce distinct dynamic types of behavior. This study analyzes the accuracy in the prediction of LCs, namely their amplitude and frequency, when using several different algorithms. To illustrate this problem we use FO-PID algorithms in the control of systems with backlash.

Modeling Vegetable Fractals by means of Fractional-order Equations

This paper characterizes four ‘fractal vegetables’: (i) cauliflower (brassica oleracea var. Botrytis); (ii) broccoli (brassica oleracea var. italica); (iii) round cabbage (brassica oleracea var. capitata) and (iv) Brussels sprout (brassica oleracea var. gemmifera), by means of electrical impedance spectroscopy and fractional calculus tools. Experimental data is approximated using fractional-order models and the corresponding parameters are determined with a genetic algorithm. The Havriliak-Negami five-parameter model fits well into the data, demonstrating that classical formulae can constitute simple and reliable models to characterize biological structures.

Visualizing control systems performance: A fractional perspective

This article presents a novel method for visualizing the control systems behavior. The proposed scheme uses the tools of fractional calculus and computes the signals propagating within the system structure as a time/frequency-space wave. Linear and nonlinear closed-loop control systems are analyzed, for both the time and frequency responses, under the action of a reference step input signal. Several nonlinearities, namely, Coulomb friction and backlash, are also tested. The numerical experiments demonstrate the feasibility of the proposed methodology as a visualization tool and motivate its extension for other systems and classes of nonlinearities.

High-Content Analysis of Breast Cancer Using Single-Cell Deep Transfer Learning

High-content analysis has revolutionized cancer drug discovery by identifying substances that alter the phenotype of a cell, which prevents tumor growth and metastasis. The high-resolution biofluorescence images from assays allow precise quantitative measures enabling the distinction of small molecules of a host cell from a tumor. In this work, we are particularly interested in the application of deep neural networks (DNNs), a cutting-edge machine learning method, to the classification of compounds in chemical mechanisms of action (MOAs). Compound classification has been performed using image-based profiling methods sometimes combined with feature reduction methods such as principal component analysis or factor analysis. In this article, we map the input features of each cell to a particular MOA class without using any treatment-level profiles or feature reduction methods. To the best of our knowledge, this is the first application of DNN in this domain, leveraging single-cell information. Furthermore, we use deep transfer learning (DTL) to alleviate the intensive and computational demanding effort of searching the huge parameter's space of a DNN. Results show that using this approach, we obtain a 30% speedup and a 2% accuracy improvement.

Familial Amyloidotic Polineuropathy and Systemic Lupus

Familial amyloidotic polineuropathy is a genetic disorder, leading to systemic amyloid deposits, manifested as sensory-motor and autonomic neuropathy. In the Portuguese classical form, the disease is evident at a young age, and causes death if no specific treatment is received. Variability in penetrance, age of onset and clinical course has been published; environmental and genetic factors are believed to contribute to this variability. The authors report a case of a 51-year-old white female, with a medical history of acquired angioedema, late-onset familial amyloidotic polineuropathy and systemic lupus erythemathosus. The authors consider that these associated diseases could modulate their expression.