Improved Numerical Simulation for a Novel Adaptive Control Using Fractional Order Derivatives

A novel control technique is investigated in the adaptive control of a typical paradigm, an approximately and partially modeled cart plus double pendulum system. In contrast to the traditional approaches that try to build up ”complete” and ”permanent” system models it develops ”temporal” and ”partial” ones that are valid only in the actual dynamic environment of the system, that is only within some ”spatio-temporal vicinity” of the actual observations. This technique was investigated for various physical systems via ”preliminary” simulations integrating by the simplest 1st order finite element approach for the time domain. In 2004 INRIA issued its SCILAB 3.0 and its improved numerical simulation tool ”Scicos” making it possible to generate ”professional”, ”convenient”, and accurate simulations. The basic principles of the adaptive control, the typical tools available in Scicos, and others developed by the authors, as well as the improved simulation results and conclusions are presented in the contribution.

Fractional Dynamics in Forest Fires

Every year forest fires consume large areas, being a major concern in many countries like Australia, United States and Mediterranean Basin European Countries (e.g., Portugal, Spain, Italy and Greece). Understanding patterns of such events, in terms of size and spatiotemporal distributions, may help to take measures beforehand in view of possible hazards and decide strategies of fire prevention, detection and suppression. Traditional statistical tools have been used to study forest fires. Nevertheless, those tools might not be able to capture the main features of fires complex dynamics and to model fire behaviour [1]. Forest fires size-frequency distributions unveil long range correlations and long memory characteristics, which are typical of fractional order systems [2]. Those complex correlations are characterized by self-similarity and absence of characteristic length-scale, meaning that forest fires exhibit power-law (PL) behaviour. Forest fires have also been proved to exhibit time-clustering phenomena, with timescales of the order of few days [3]. In this paper, we study forest fires in the perspective of dynamical systems and fractional calculus (FC). Public domain forest fires catalogues, containing data of events occurred in Portugal, in the period 1980 up to 2011, are considered. The data is analysed in an annual basis, modelling the occurrences as sequences of Dirac impulses. The frequency spectra of such signals are determined using Fourier transforms, and approximated through PL trendlines. The PL parameters are then used to unveil the fractional-order dynamics characteristics of the data. To complement the analysis, correlation indices are used to compare and find possible relationships among the data. It is shown that the used approach can be useful to expose hidden patterns not captured by traditional tools.

Diffusion characteristics of ethylene glycol in skeletal muscle

Part of the optical clearing study in biological tissues concerns the determination of the diffusion characteristics of water and optical clearing agents in the subject tissue. Such information is sufficient to characterize the time dependence of the optical clearing mechanisms—tissue dehydration and refractive index (RI) matching. We have used a simple method based on collimated optical transmittance measurements made from muscle samples under treatment with aqueous solutions containing different concentrations of ethylene glycol (EG), to determine the diffusion time values of water and EG in skeletal muscle. By representing the estimated mean diffusion time values from each treatment as a function of agent concentration in solution, we could identify the real diffusion times for water and agent. These values allowed for the calculation of the correspondent diffusion coefficients for those fluids. With these results, we have demonstrated that the dehydration mechanism is the one that dominates optical clearing in the first minute of treatment, while the RI matching takes over the optical clearing operations after that and remains for a longer time of treatment up to about 10 min, as we could see for EG and thin tissue samples of 0.5 mm.

Analysis of Natural and Artificial Phenomena Using Signal Processing and Fractional Calculus

In this paper we study several natural and man-made complex phenomena in the perspective of dynamical systems. For each class of phenomena, the system outputs are time-series records obtained in identical conditions. The time-series are viewed as manifestations of the system behavior and are processed for analyzing the system dynamics. First, we use the Fourier transform to process the data and we approximate the amplitude spectra by means of power law functions. We interpret the power law parameters as a phenomenological signature of the system dynamics. Second, we adopt the techniques of non-hierarchical clustering and multidimensional scaling to visualize hidden relationships between the complex phenomena. Third, we propose a vector field based analogy to interpret the patterns unveiled by the PL parameters.

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.

Development of computer application for determination of chemical diffusion properties in biological tissues

The main objective of this work was to develop an application capable of determining the diffusion times and diffusion coefficients of optical clearing agents and water inside a known type of muscle. Different types of chemical agents can also be used with the method implemented, such as medications or metabolic products. Since the diffusion times can be calculated, it is possible to describe the dehydration mechanism that occurs in the muscle. The calculation of the diffusion time of an optical clearing agent allows to characterize the refractive index matching mechanism of optical clearing. By using both the diffusion times and diffusion of water and clearing agents not only the optical clearing mechanisms are characterized, but also information about optical clearing effect duration and magnitude is obtained. Such information is crucial to plan a clinical intervention in cooperation with optical clearing. The experimental method and equations implemented in the developed application are described in throughout this document, demonstrating its effectiveness. The application was developed in MATLAB code, but the method was personalized so it better fits the application needs. This process significantly improved the processing efficiency, reduced the time to obtain he results, multiple validations prevents common errors and some extra functionalities were added such as saving application progress or export information in different formats. Tests were made using glucose measurements in muscle. Some of the data, for testing purposes, was also intentionally changed in order to obtain different simulations and results from the application. The entire project was validated by comparing the calculated results with the ones found in literature, which are also described in this document.