Nonlinear system identification using particle swarm optimisation tuned radial basis function models

A novel particle swarm optimisation (PSO) tuned radial basis function (RBF) network model is proposed for identification of non-linear systems. At each stage of orthogonal forward regression (OFR) model construction process, PSO is adopted to tune one RBF unit's centre vector and diagonal covariance matrix by minimising the leave-one-out (LOO) mean square error (MSE). This PSO aided OFR automatically determines how many tunable RBF nodes are sufficient for modelling. Compared with the-state-of-the-art local regularisation assisted orthogonal least squares algorithm based on the LOO MSE criterion for constructing fixed-node RBF network models, the PSO tuned RBF model construction produces more parsimonious RBF models with better generalisation performance and is often more efficient in model construction. The effectiveness of the proposed PSO aided OFR algorithm for constructing tunable node RBF models is demonstrated using three real data sets.

Expansion quality of epidemic protocols

Epidemic protocols are a bio-inspired communication and computation paradigm for large and extreme-scale networked systems. This work investigates the expansion property of the network overlay topologies induced by epidemic protocols. An expansion quality index for overlay topologies is proposed and adopted for the design of epidemic membership protocols. A novel protocol is proposed, which explicitly aims at improving the expansion quality of the overlay topologies. The proposed protocol is tested with a global aggregation task and compared to other membership protocols. The analysis by means of simulations indicates that the expansion quality directly relates to the speed of dissemination and convergence of epidemic protocols and can be effectively used to design better protocols.

Body-centric modelling, identification, and acceleration tracking control of a quadrotor UAV

This paper presents the mathematical development of a body-centric nonlinear dynamic model of a quadrotor UAV that is suitable for the development of biologically inspired navigation strategies. Analytical approximations are used to find an initial guess of the parameters of the nonlinear model, then parameter estimation methods are used to refine the model parameters using the data obtained from onboard sensors during flight. Due to the unstable nature of the quadrotor model, the identification process is performed with the system in closed-loop control of attitude angles. The obtained model parameters are validated using real unseen experimental data. Based on the identified model, a Linear-Quadratic (LQ) optimal tracker is designed to stabilize the quadrotor and facilitate its translational control by tracking body accelerations. The LQ tracker is tested on an experimental quadrotor UAV and the obtained results are a further means to validate the quality of the estimated model. The unique formulation of the control problem in the body frame makes the controller better suited for bio-inspired navigation and guidance strategies than conventional attitude or position based control systems that can be found in the existing literature.

Lipopeptides: from self-assembly to bioactivity

This Feature Article discusses several classes of lipopeptide with important biomedical applications as antimicrobial and antifungal agents, in immune therapies and in personal care applications among others. Two main classes of lipopeptide are considered: (i) bacterially-expressed lipopeptides with a cyclic peptide headgroup and (ii) linear lipopeptides (with one or more lipid chains) based on bio-derived and bio-inspired amino acid sequences with current clinical applications. The applications are briefly summarized, and the biophysical characterization of the molecules is reviewed, with a particular focus on self-assembly. For several of these types of biomolecule, the formation of micelles above a critical micelle concentration has been observed while others form bilayer structures, depending on conditions of pH and temperature. As yet, there are few studies on the possible relationship between self-assembly into structures such as micelles and bioactivity of this class of molecule although this is likely to attract further attention.

Connectivity recovery in epidemic membership protocols

Epidemic protocols are a bio-inspired communication and computation paradigm for extreme-scale network system based on randomized communication. The protocols rely on a membership service to build decentralized and random overlay topologies. In a weakly connected overlay topology, a naive mechanism of membership protocols can break the connectivity, thus impairing the accuracy of the application. This work investigates the factors in membership protocols that cause the loss of global connectivity and introduces the first topology connectivity recovery mechanism. The mechanism is integrated into the Expander Membership Protocol, which is then evaluated against other membership protocols. The analysis shows that the proposed connectivity recovery mechanism is effective in preserving topology connectivity and also helps to improve the application performance in terms of convergence speed.

Multidimensional polynomial powers of sigmoid (PPS) Wavelet neural networks

Wavelet functions have been used as the activation function in feedforward neural networks. An abundance of R&D has been produced on wavelet neural network area. Some successful algorithms and applications in wavelet neural network have been developed and reported in the literature. However, most of the aforementioned reports impose many restrictions in the classical backpropagation algorithm, such as low dimensionality, tensor product of wavelets, parameters initialization, and, in general, the output is one dimensional, etc. In order to remove some of these restrictions, a family of polynomial wavelets generated from powers of sigmoid functions is presented. We described how a multidimensional wavelet neural networks based on these functions can be constructed, trained and applied in pattern recognition tasks. As an example of application for the method proposed, it is studied the exclusive-or (XOR) problem.

Otimização em comitês de classificadores: uma abordagem baseada em filtro para seleção de subconjuntos de atributos

Traditional applications of feature selection in areas such as data mining, machine learning and pattern recognition aim to improve the accuracy and to reduce the computational cost of the model. It is done through the removal of redundant, irrelevant or noisy data, finding a representative subset of data that reduces its dimensionality without loss of performance. With the development of research in ensemble of classifiers and the verification that this type of model has better performance than the individual models, if the base classifiers are diverse, comes a new field of application to the research of feature selection. In this new field, it is desired to find diverse subsets of features for the construction of base classifiers for the ensemble systems. This work proposes an approach that maximizes the diversity of the ensembles by selecting subsets of features using a model independent of the learning algorithm and with low computational cost. This is done using bio-inspired metaheuristics with evaluation filter-based criteria

Classification of petroleum well drilling operations with a hybrid particle swarm/ant colony algorithm

This paper describes an investigation of the hybrid PSO/ACO algorithm to classify automatically the well drilling operation stages. The method feasibility is demonstrated by its application to real mud-logging dataset. The results are compared with bio-inspired methods, and rule induction and decision tree algorithms for data mining. © 2009 Springer Berlin Heidelberg.

Contributions to underwater glider path planning

[ES] La Planificación de Rutas o Caminos es un disciplina de Robótica que trata la búsqueda de caminos factibles u óptimos. Para la mayoría de vehículos y entornos, no es un problema trivial y por tanto nos encontramos con un gran diversidad de algoritmos para resolverlo, no sólo en Robótica e Inteligencia Artificial, sino también como parte de la literatura de Optimización, con Métodos Numéricos y Algoritmos Bio-inspirados, como Algoritmos Genéticos y el Algoritmo de la Colonia de Hormigas. El caso particular de escenarios de costes variables es considerablemente difícil de abordar porque el entorno en el que se mueve el vehículo cambia con el tiempo. El presente trabajo de tesis estudia este problema y propone varias soluciones prácticas para aplicaciones de Robótica Submarina.

Synthesis and surface modification of semiconductor nanocrystals

The last decade has witnessed an exponential growth of activities in the field of nanoscience and nanotechnology worldwide, driven both by the excitement of understanding new science and by the potential hope for applications and economic impacts. The largest activity in this field up to date has been in the synthesis and characterization of new materials consisting of particles with dimensions in the order of a few nanometers, so-called nanocrystalline materials. [1-8] Semiconductor nanomaterials such as III/V or II/VI compound semiconductors exhibit strong quantum confinement behavior in the size range from 1 to 10 nm. Therefore, preparation of high quality semiconductor nanocrystals has been a challenge for synthetic chemists, leading to the recent rapid progress in delivering a wide variety of semiconducting nanomaterials. Semiconductor nanocrystals, also called quantum dots, possess physical properties distinctly different from those of the bulk material. Typically, in the size range from 1 to 10 nm, when the particle size is changed, the band gap between the valence and the conduction band will change, too. In a simple approximation a particle in a box model has been used to describe the phenomenon[9]: at nanoscale dimensions the degenerate energy states of a semiconductor separate into discrete states and the system behaves like one big molecule. The size-dependent transformation of the energy levels of the particles is called “quantum size-effect”. Quantum confinement of both the electron and hole in all three dimensions leads to an increase in the effective bandgap of the material with decreasing crystallite size. Consequently, both the optical absorption and emission of semiconductor nanaocrystals shift to the blue (higher energies) as the size of the particles gets smaller. This color tuning is well documented for CdSe nanocrystals whose absorption and emission covers almost the whole visible spectral range. As particle sizes become smaller the ratio of surface atoms to those in the interior increases, which has a strong impact on particle properties, too. Prominent examples are the low melting point [8] and size/shape dependent pressure resistance [10] of semiconductor nanocrystals. Given the size dependence of particle properties, chemists and material scientists now have the unique opportunity to change the electronic and chemical properties of a material by simply controlling the particle size. In particular, CdSe nanocrystals have been widely investigated. Mainly due to their size-dependent optoelectronic properties [11, 12] and flexible chemical processibility [13], they have played a distinguished role for a number of seminal studies [11, 12, 14, 15]. Potential technical applications have been discussed, too. [8, 16-27] Improvement of the optoelectronic properties of semiconductor nanocrystals is still a prominent research topic. One of the most important approaches is fabricating composite type-I core-shell structures which exhibit improved properties, making them attractive from both a fundamental and a practical point of view. Overcoating of nanocrystallites with higher band gap inorganic materials has been shown to increase the photoluminescence quantum yields by eliminating surface nonradiative recombination sites. [28] Particles passivated with inorganic shells are more robust than nanocrystals covered by organic ligands only and have greater tolerance to processing conditions necessary for incorporation into solid state structures or for other applications. Some examples of core-shell nanocrystals reported earlier include CdS on CdSe [29], CdSe on CdS, [30], ZnS on CdS, [31] ZnS on CdSe[28, 32], ZnSe on CdSe [33] and CdS/HgS/CdS [34]. The characterization and preparation of a new core-shell structure, CdSe nanocrystals overcoated by different shells (CdS, ZnS), is presented in chapter 4. Type-I core-shell structures as mentioned above greatly improve the photoluminescence quantum yield and chemical and photochemical stability of nanocrystals. The emission wavelengths of type-I core/shell nanocrystals typically only shows a small red-shift when compared to the plain core nanocrystals. [30, 31, 35] In contrast to type-I core-shell nanocrystals, only few studies have been conducted on colloidal type-II core/shell structures [36-38] which are characterized by a staggered alignment of conduction and valence bands giving rise to a broad tunability of absorption and emission wavelengths, as was shown for CdTe/CdSe core-shell nanocrystals. [36] The emission of type-II core/shell nanocrystals mainly originates from the radiative recombination of electron-hole pairs across the core-shell interface leading to a long photoluminescence lifetime. Type-II core/shell nanocrystals are promising with respect to photoconduction or photovoltaic applications as has been discussed in the literature.[39] Novel type-II core-shell structures with ZnTe cores are reported in chapter 5. The recent progress in the shape control of semiconductor nanocrystals opens new fields of applications. For instance, rod shaped CdSe nanocrystals can enhance the photo-electro conversion efficiency of photovoltaic cells, [40, 41] and also allow for polarized emission in light emitting diodes. [42, 43] Shape control of anisotropic nanocrystals can be achieved by the use of surfactants, [44, 45] regular or inverse micelles as regulating agents, [46, 47] electrochemical processes, [48] template-assisted [49, 50] and solution-liquid-solution (SLS) growth mechnism. [51-53] Recently, formation of various CdSe nanocrystal shapes has been reported by the groups of Alivisatos [54] and Peng, [55] respectively. Furthermore, it has been reported by the group of Prasad [56] that noble metal nanoparticles can induce anisotropic growth of CdSe nanocrystals at lower temperatures than typically used in other methods for preparing anisotropic CdSe structures. Although several approaches for anisotropic crystal growth have been reported by now, developing new synthetic methods for the shape control of colloidal semiconductor nanocrystals remains an important goal. Accordingly, we have attempted to utilize a crystal phase control approach for the controllable synthesis of colloidal ZnE/CdSe (E = S, Se, Te) heterostructures in a variety of morphologies. The complex heterostructures obtained are presented in chapter 6. The unique optical properties of nanocrystals make them appealing as in vivo and in vitro fluorophores in a variety of biological and chemical investigations, in which traditional fluorescence labels based on organic molecules fall short of providing long-term stability and simultaneous detection of multiple emission colours [References]. The ability to prepare water soluble nanocrystals with high stability and quantum yield has led to promising applications in cellular labeling, [57, 58] deep-tissue imaging, [59, 60] and assay labeling [61, 62]. Furthermore, appropriately solubilized nanocrystals have been used as donors in fluorescence resonance energy transfer (FRET) couples. [63-65] Despite recent progress, much work still needs to be done to achieve reproducible and robust surface functionalization and develop flexible (bio-) conjugation techniques. Based on multi-shell CdSe nanocrystals, several new solubilization and ligand exchange protocols have been developed which are presented in chapter 7. The organization of this thesis is as follows: A short overview describing synthesis and properties of CdSe nanocrystals is given in chapter 2. Chapter 3 is the experimental part providing some background information about the optical and analytical methods used in this thesis. The following chapters report the results of this work: synthesis and characterization of type-I multi-shell and type-II core/shell nanocrystals are described in chapter 4 and chapter 5, respectively. In chapter 6, a high–yield synthesis of various CdSe architectures by crystal phase control is reported. Experiments about surface modification of nanocrystals are described in chapter 7. At last, a short summary of the results is given in chapter 8.

In vivo evaluation of the translations of the gleno-humeral joint using Magnetic resonance imaging

Gleno-humeral joint (GHJ) is the most mobile joint of the human body. This is related to theincongr uence between the large humeral head articulating with the much smaller glenoid (ratio 3:1). The GHJ laxity is the ability of the humeral head to be passively translated on the glenoid fossa and, when physiological, it guarantees the normal range of motion of the joint. Three-dimensional GHJ linear displacements have been measured, both in vivo and in vitro by means of different instrumental techniques. In vivo gleno-humeral displacements have been assessed by means of stereophotogrammetry, electromagnetic tracking sensors, and bio-imaging techniques. Both stereophotogrammetric systems and electromagnetic tracking devices, due to the deformation of the soft tissues surrounding the bones, are not capable to accurately assess small displacements, such as gleno-humeral joint translations. The bio-imaging techniques can ensure for an accurate joint kinematic (linear and angular displacement) description, but, due to the radiation exposure, most of these techniques, such as computer tomography or fluoroscopy, are invasive for patients. Among the bioimaging techniques, an alternative which could provide an acceptable level of accuracy and that is innocuous for patients is represented by magnetic resonance imaging (MRI). Unfortunately, only few studies have been conducted for three-dimensional analysis and very limited data is available in situations where preset loads are being applied. The general aim of this doctoral thesis is to develop a non-invasive methodology based on open-MRI for in-vivo evaluation of the gleno-humeral translation components in healthy subjects under the application of external loads.

Konstruktive Gestaltung eines bioinspirierten Kommissionier-Greifers für intralogistische Handhabungsaufgaben

In diesem Beitrag wird ein neuartiger biologisch inspirierter Universalgreifer beschrieben. Dieser soll in einem automatisierten Kommissionier-Szenario selbstständig Waren aus Kisten greifen, anheben und an anderer Stelle ablegen um somit das manuelle Kommissionieren von Hand zu substituieren. Auf dem Weg zu einer ausgereiften Konstruktion werden zahlreiche Fragestellungen zur Gestaltung und Anordnung der Finger und deren Antrieb gelöst. Ein für diesen Anwendungsfall entwickelter Biegeaktor wird zur Krümmung der Finger eingesetzt und bietet als Alleinstellungsmerkmal ein nahezu verschleißfreies Gelenk bei einem sehr einfachen konstruktiven Aufbau.

Bending continuous structures with SMAs: a novel robotic fish design

In this paper, we describe our research on bio-inspired locomotion systems using deformable structures and smart materials, concretely shape memory alloys (SMAs). These types of materials allow us to explore the possibility of building motor-less and gear-less robots. A swimming underwater fish-like robot has been developed whose movements are generated using SMAs. These actuators are suitable for bending the continuous backbone of the fish, which in turn causes a change in the curvature of the body. This type of structural arrangement is inspired by fish red muscles, which are mainly recruited during steady swimming for the bending of a flexible but nearly incompressible structure such as the fishbone. This paper reviews the design process of these bio-inspired structures, from the motivations and physiological inspiration to the mechatronics design, control and simulations, leading to actual experimental trials and results. The focus of this work is to present the mechanisms by which standard swimming patterns can be reproduced with the proposed design. Moreover, the performance of the SMA-based actuators’ control in terms of actuation speed and position accuracy is also addressed.

Análisis estático de sistemas de membranas para la determinación de reglas activas

Esta tesis doctoral se enmarca dentro de la computación con membranas. Se trata de un tipo de computación bio-inspirado, concretamente basado en las células de los organismos vivos, en las que se producen múltiples reacciones de forma simultánea. A partir de la estructura y funcionamiento de las células se han definido diferentes modelos formales, denominados P sistemas. Estos modelos no tratan de modelar el comportamiento biológico de una célula, sino que abstraen sus principios básicos con objeto de encontrar nuevos paradigmas computacionales. Los P sistemas son modelos de computación no deterministas y masivamente paralelos. De ahí el interés que en los últimos años estos modelos han suscitado para la resolución de problemas complejos. En muchos casos, consiguen resolver de forma teórica problemas NP-completos en tiempo polinómico o lineal. Por otra parte, cabe destacar también la aplicación que la computación con membranas ha tenido en la investigación de otros muchos campos, sobre todo relacionados con la biología. Actualmente, una gran cantidad de estos modelos de computación han sido estudiados desde el punto de vista teórico. Sin embargo, el modo en que pueden ser implementados es un reto de investigación todavía abierto. Existen varias líneas en este sentido, basadas en arquitecturas distribuidas o en hardware dedicado, que pretenden acercarse en lo posible a su carácter no determinista y masivamente paralelo, dentro de un contexto de viabilidad y eficiencia. En esta tesis doctoral se propone la realización de un análisis estático del P sistema, como vía para optimizar la ejecución del mismo en estas plataformas. Se pretende que la información recogida en tiempo de análisis sirva para configurar adecuadamente la plataforma donde se vaya a ejecutar posteriormente el P sistema, obteniendo como consecuencia una mejora en el rendimiento. Concretamente, en esta tesis se han tomado como referencia los P sistemas de transiciones para llevar a cabo el estudio de dicho análisis estático. De manera un poco más específica, el análisis estático propuesto en esta tesis persigue que cada membrana sea capaz de determinar sus reglas activas de forma eficiente en cada paso de evolución, es decir, aquellas reglas que reúnen las condiciones adecuadas para poder ser aplicadas. En esta línea, se afronta el problema de los estados de utilidad de una membrana dada, que en tiempo de ejecución permitirán a la misma conocer en todo momento las membranas con las que puede comunicarse, cuestión que determina las reglas que pueden aplicarse en cada momento. Además, el análisis estático propuesto en esta tesis se basa en otra serie de características del P sistema como la estructura de membranas, antecedentes de las reglas, consecuentes de las reglas o prioridades. Una vez obtenida toda esta información en tiempo de análisis, se estructura en forma de árbol de decisión, con objeto de que en tiempo de ejecución la membrana obtenga las reglas activas de la forma más eficiente posible. Por otra parte, en esta tesis se lleva a cabo un recorrido por un número importante de arquitecturas hardware y software que diferentes autores han propuesto para implementar P sistemas. Fundamentalmente, arquitecturas distribuidas, hardware dedicado basado en tarjetas FPGA y plataformas basadas en microcontroladores PIC. El objetivo es proponer soluciones que permitan implantar en dichas arquitecturas los resultados obtenidos del análisis estático (estados de utilidad y árboles de decisión para reglas activas). En líneas generales, se obtienen conclusiones positivas, en el sentido de que dichas optimizaciones se integran adecuadamente en las arquitecturas sin penalizaciones significativas. Summary Membrane computing is the focus of this doctoral thesis. It can be considered a bio-inspired computing type. Specifically, it is based on living cells, in which many reactions take place simultaneously. From cell structure and operation, many different formal models have been defined, named P systems. These models do not try to model the biological behavior of the cell, but they abstract the basic principles of the cell in order to find out new computational paradigms. P systems are non-deterministic and massively parallel computational models. This is why, they have aroused interest when dealing with complex problems nowadays. In many cases, they manage to solve in theory NP problems in polynomial or lineal time. On the other hand, it is important to note that membrane computing has been successfully applied in many researching areas, specially related to biology. Nowadays, lots of these computing models have been sufficiently characterized from a theoretical point of view. However, the way in which they can be implemented is a research challenge, that it is still open nowadays. There are some lines in this way, based on distributed architectures or dedicated hardware. All of them are trying to approach to its non-deterministic and parallel character as much as possible, taking into account viability and efficiency. In this doctoral thesis it is proposed carrying out a static analysis of the P system in order to optimize its performance in a computing platform. The general idea is that after data are collected in analysis time, they are used for getting a suitable configuration of the computing platform in which P system is going to be performed. As a consequence, the system throughput will improve. Specifically, this thesis has made use of Transition P systems for carrying out the study in static analysis. In particular, the static analysis proposed in this doctoral thesis tries to achieve that every membrane can efficiently determine its active rules in every evolution step. These rules are the ones that can be applied depending on the system configuration at each computational step. In this line, we are going to tackle the problem of the usefulness states for a membrane. This state will allow this membrane to know the set of membranes with which communication is possible at any time. This is a very important issue in determining the set of rules that can be applied. Moreover, static analysis in this thesis is carried out taking into account other properties such as membrane structure, rule antecedents, rule consequents and priorities among rules. After collecting all data in analysis time, they are arranged in a decision tree structure, enabling membranes to obtain the set of active rules as efficiently as possible in run-time system. On the other hand, in this doctoral thesis is going to carry out an overview of hardware and software architectures, proposed by different authors in order to implement P systems, such as distributed architectures, dedicated hardware based on PFGA, and computing platforms based on PIC microcontrollers. The aim of this overview is to propose solutions for implementing the results of the static analysis, that is, usefulness states and decision trees for active rules. In general, conclusions are satisfactory, because these optimizations can be properly integrated in most of the architectures without significant penalties.