This study analyzes the problem of robust stability of fractional-order delay systems of neutral type under actuator saturation. A Lyapunov-Krasovskii (LK) function is constructed and conditions of the asymptotic robust stability of such systems are given, which are formulated by linear matrix inequalities (LMIs), using the Lyapunov direct method. An algorithm is introduced to compute the gain of the state feedback controller for extending the domain of attraction. The theoretical results are validated using some numerical examples.

Computational modeling of visual attention has been a research field focused on emulating the behavior of biological visual systems in a given scenario, by using mechanisms developed for fixation prediction or salient region detection. In the literature, different approaches have been presented to emulate the interactions that occur in the early vision system of biological structures. However, mathematical modeling of these systems applying theories related to fractional operators could outperform the existing models. In this paper, we present a fractional bio-inspired filter for salient color detection in natural scenarios, based on the behavior and distribution of the cone photoreceptors cells in the retina. The filter was compared with two classic saliency algorithms over a natural color image dataset in terms of saliency prediction and processing time, using a Similarity (SIM) score and runtime performance, respectively. Our approach reach the second best result in therms of saliency prediction with a 48,9% of SIM with ground truth fixations maps and the fastest time response, with an average time of 0.12 s when processing a high resolution image, being 25% faster than Itti et al. algorithm, one of the most applied in robotic vision tasks.

A novel color image encryption algorithm based on dynamic deoxyribonucleic acid (DNA) encoding and chaos is presented. A three-neuron fractional-order discrete Hopfield neural network (FODHNN) is employed as a pseudo-random chaotic sequence generator. Its initial value is obtained with the secret key generated by a five-parameter external key and a hash code of the plain image. The external key includes both the FODHNN discrete step size and order. The hash is computed with the SHA-2 function. This ensures a large secret key space and improves the algorithm sensitivity to the plain image. Furthermore, a new three-dimensional projection confusion method is proposed to scramble the pixels among red, green, and blue color components. DNA encoding and diffusion are used to diffuse the image information. Pseudo-random sequences generated by FODHNN are employed to determine the encoding rules for each pixel and to ensure the diversity of the encoding methods. Finally, confusion II and XOR are used to ensure the security of the encryption. Experimental results and the security analysis show that the proposed algorithm has better performance than those reported in the literature and can resist typical attacks.

This paper examines the time series of four important agricultural commodities, namely the soybean, corn, coffee and sugar prices. Time series can exhibit long-range dependence and persistence in their observation. The long memory feature of data is

In this paper we discuss different definitions of variable-order derivatives of high order and we propose accurate and robust algorithms for their approximate calculation. The proposed algorithms are based on finite difference approximations and B-spline interpolation. We compare the performance of the algorithms by experimental convergence order. Numerical examples are presented demonstrating the efficiency and accuracy of the proposed algorithms.

A new family of the local fractional PDEs is investigated in this article. The linear, quasilinear, semilinear and nonlinear local fractional PDEs are presented. Furthermore, three types of the local fractional PDEs are discussed, namely, parabolic, hyperbolic and elliptic. Several examples illustr ate the corresponding models in nonlinear mathematical physics.

This paper reports on the analysis of tidal breathing patterns measured during noninvasive forced oscillation lung function tests in six individual groups. The three adult groups were healthy, with prediagnosed chronic obstructive pulmonary disease, and with prediagnosed kyphoscoliosis, respectively. The three children groups were healthy, with prediagnosed asthma, and with prediagnosed cystic fibrosis, respectively. The analysis is applied to the pressure-volume curves and the pseudophase-plane loop by means of the box-counting method, which gives a measure of the area within each loop. The objective was to verify if there exists a link between the area of the loops, power-law patterns, and alterations in the respiratory structure with disease. We obtained statistically significant variations between the data sets corresponding to the six groups of patients, showing also the existence of power-law patterns. Our findings support the idea that the respiratory system changes with disease in terms of airway geometry and tissue parameters, leading, in turn, to variations in the fractal dimension of the respiratory tree and its dynamics.

MOTIVATION: We describe a novel approach to explore DNA nucleotide sequence data, aiming to produce high-level categorical and structural information about the underlying chromosomes, genomes and species. RESULTS: The article starts by analyzing chromosomal data through histograms using fixed length DNA sequences. After creating the DNA-related histograms, a correlation between pairs of histograms is computed, producing a global correlation matrix. These data are then used as input to several data processing methods for information extraction and tabular/graphical output generation. A set of 18 species is processed and the extensive results reveal that the proposed method is able to generate significant and diversified outputs, in good accordance with current scientific knowledge in domains such as genomics and phylogenetics. AVAILABILITY AND IMPLEMENTATION: Source code freely available for download at http://www4.dei.isep.ipp.pt/etc/dnapaper2010, implemented in Free Pascal and UNIX scripting tools. Study input data available online for download at University of California at Santa Cruz Genome Bioinformatics, http://hgdownload.cse.ucsc.edu/downloads.html.

This paper presents a genetic algorithm to optimize uni-objective problems with an infinite number of optimal solutions. The algorithm uses the maximin concept and e-dominance to promote diversity over the admissible space. The proposed algorithm is tested with two well-known functions. The practical results of the algorithm are in good agreement with the optimal solutions of these functions. Moreover, the proposed optimization method is also applied in two practical real-world engineering optimization problems, namely, in radio frequency circuit design and in kinematic optimization of a parallel robot. In all the cases, the algorithm draws a set of optimal solutions. This means that each problem can be solved in several different ways, all with the same maximum performance.

This paper presents a simple approach for implementing Interactive Evolutionary Computation (IEC) - a paradigm in which humans directly intervene in fitness evaluation - in the field of musical melody generation. Music is an art and, as all kinds of art, it involves creativity. However, creativity is still a human capability. A Genetic Algorithm (GA) based application has been developed and tested. The initial population was generated according to Zipf's Law. Simple melodies, obtained in a few iterations, can be quickly transformed into complete and interesting songs.

Obtaining a well distributed non-dominated Pareto front is one of the key issues in multi-objective optimization algorithms. This paper proposes an algorithm which promotes well distributed non-dominated fronts in the parameters space when a single-objective function is optimized. The proposed technique is described and tested in an automated synthesis circuit design problem. The project consists in designing CMOS radio-frequency and microwave binaryweighted differential switched capacitor arrays (RFDSCAs) from user top-level specification to component size. The genetic synthesis tool optimizes a fitness function based on the performance parameter of the RFDSCAs. To validate the proposed design methodology, a CMOS RFDSCA is synthesized, using a 0.25 μm BiCMOS technology, and verified by the SpectreRF simulator of the Cadence design environment. The results show that the synthesis and simulation outcomes are in very good agreement.

In this paper we present a general discretization scheme for digital fractional-order integrators and differentiators. The proposed scheme yields many of the widely classical s rarr z conversion formulas. A least-squares method for the design of IIR fractional filters is proposed. The design of the recursive digital filter only requires the solution of linear equations. An illustrative example is presented showing the effectiveness of the resulting approximations.

In this work we study a heat diffusion system on a fractional calculus perspective. Several fractional PID tuning methodologies are investigated and compared. The simulations demonstrate the good performance of the proposed fractional algorithm.

This article reports the study of fractional dynamics during the evolution of a particle swarm optimization (PSO) algorithm. Some initial swarm particles are randomly changed, for stimulating the system response, and its effect is compared with a non-perturbed reference. The perturbation effect in the PSO evolution is observed in the perspective of the fitness time behavior of the best particle. The dynamics is represented through the median of a sample of experiments, while adopting the Fourier analysis for describing the phenomena. The influence of the PSO parameters influence upon the global dynamics is also analyzed.

This paper studies the fractional dynamics during the evolution of a Particle Swarm Optimization (PSO). Some swarm particles of the initial population are randomly changed for stimulating the system response. After the result is compared with a reference situation. The perturbation effect in the PSO evolution is observed in the perspective of the time behavior of the fitness of the best individual position visited by the replaced particles. The dynamics is investigated through the median of a sample of experiments, while adopting the Fourier analysis for describing the phenomena. The influence of the PSO parameters upon the global dynamics is also analyzed by performing several experiments for distinct values.

This paper presents two evolutionary schemes and a swarm intelligence algorithm for the design of combinational logic circuits. A Genetic and a Memetic schemes as the evolutionary algorithms. The Particle Swarm Optimization as the swarm algorithm. The fitness function used in these three algorithms is sequential, that is, divided in two parts. The first part of the fitness function ƒ1evaluates the circuit functionality, while the second part ƒ2 deals with the circuit complexity. The experiments consist in applying the algorithms in the design of two arithmetic circuits: the one-bit full adder and the one-bit full subtractor. We also present a scalability analysis using the parity checker family of circuits.

This paper proposes and analyses the performance of a Genetic Algorithm (GA) using two new concepts, namely a static fitness function including a discontinuity measure and a fractional-order dynamic fitness function. The GA is adopted for the synthesis of combinational logic circuits. In both cases, experiments reveal superior results in terms of speed and convergence to achieve a solution.

This paper addresses the problem of modelling and control of a biped robot by combining Cartesian-based position and force control algorithms. The walking cycle is divided in two phases: single support, in which one leg is in contact with the ground and the other leg swings forward, and double support, in which the forward leg absorbs the impact and gradually accepts the robot's weight. The contact of the foot with the constrained surface is modelled through nonlinear spring-damper systems. The proposed control approach is based on simple motion goals taking into account the reaction forces between the feet and the ground. The control algorithm is tested through several experiments and its robustness is discussed.

This work presents the simulator of intelligent transportation systems (SITS). The SITS is based on a microscopic simulation approach to reproduce real traffic conditions in an urban or nonurban network and considers different types of vehicles, drivers, and roads. A dynamical analysis of several traffic phenomena is then addressed. The results of using classical system theory tools notes that it is possible to study traffic systems, taking advantage of the knowledge gathered with automatic control algorithms. In this line of thought, a new modeling formalism based on the embedding of statistics and Fourier transform is also presented.

This paper discusses the problem of modelling and simulation of traffic systems, and presents the traffic simulator SIS (simulator of intelligent transportation systems). The SITS is based on a microscopic simulation approach considering different types of vehicles, drivers and roads. A dynamical analysis of several traffic phenomena is then addressed.

Redundant manipulators have some advantages when compared with classical arms because they allow the trajectory optimization, both on the free space and on the presence of obstacles, and the resolution of singularities. For this type of arms the proposed kinematic control algorithms adopt generalized inverse matrices but, in general, the corresponding trajectory planning schemes show important limitations. Motivated by these problems this paper studies the chaos revealed by the pseudoinverse-based trajectory planning algorithms, using the theory of fractional calculus.

Studies periodic gaits of multi-legged robot locomotion systems based on dynamic models. The purpose is to determine the system performance during walking and the best set of locomotion variables. For that objective the prescribed motion of the robot is completely characterized in terms of several locomotion variables such as gait, duty factor, body height, step length, stroke pitch, foot clearance, legs link lengths, foot-hip offset, body and legs mass and cycle time. In this perspective, we formulate four performance measures of the walking robot namely, the locomobility of the foot, the mean absolute power, the mean power dispersion and the mean power lost in the joint actuators per walking distance. A set of model-based experiments reveals the influence of the locomotion variables in the proposed indices.

Analyses periodic gaits of multi-legged locomotion systems. The joint signals are studied in the Fourier domain, namely from the point of view of its reproducibility through low-pass actuators. The influence of several parameters is also considered and their critical values are investigated.

Addresses the problem of modelling and control of a biped robot by combining Cartesian-based position and force control algorithms. The walking cycle is divided in two phases: single support, in which one leg is in contact with the ground and the other leg swings forward, and double support, in which the forward leg absorbs the impact and gradually accepts the robot's weight. The contact of the foot with the constrained surface is modelled through linear and nonlinear spring-damper systems. The proposed control approach is based on simple motion goals taking into account the reaction forces between the feet and the ground. The control algorithm is tested through several experiments and its effectiveness and robustness is discussed.

This paper proposes a genetic algorithm to generate trajectories for robotic manipulators. The objective is to minimize the ripple in the trajectory time evolution and to minimize the actuator energy requirements without colliding with any obstacles in the workspace. The article presents the results for several redundant and hyper-redundant manipulators.

Several kinematic control algorithms for redundant manipulators adopt generalized inverse matrices. In this line of thought, the generalized inverse control scheme is tested through experiments that reveal the difficulties that often arise. Motivated by these problems this paper studies kinematics and dynamics of the trajectory planning scheme. The experiment confirm the nonlinear and chaotic performance of the algorithm and gives a deeper insight towards the future development of superior trajectory control systems.

The paper addresses the problem of modelling and control of a biped robot by combining Cartesian based position and force control algorithms. The complete walking cycle is divided into two phases: i) single support, in which is studied the trajectory controllability based on simple motion goals and ii) exchange of support, in which the forward leg absorbs the impact and then gradually accepts the robot's weight. The contact of the foot with the constrained surface is modelled through linear spring-damper systems. The system's controllability is enhanced through the insertion of a dynamic selection matrix that modifies the actuating profile in each phase. The control algorithms are simulated and their effectiveness and robustness are discussed.

Describes the dynamic analysis of biped locomotion systems. A planar biped is modelled and studied focusing on the problem of energy efficiency. First, the motion of the system is characterised in terms of a set of locomotion variables, namely: step length, hip height, hip ripple, hip offset, foot clearance and link lengths. Afterwards, three cost functions related to energy are proposed: absolute power, power dispersion and power lost. The aim is to understand the influence of these locomotion variables on the energy flow. The performance measures are discussed and the results compared with those observed in nature.

Presents the energy analysis of a bipedal walking system. The main goal is to understand the movement strategies in walking and to search for the optimal locomotion variables that minimise a cost function related to energy. Three different indices are proposed: mean absolute power, mean power dispersion and mean power lost. In order to accomplish this goal in the description and analysis of the motion we use a set of locomotion variables, namely: step length, hip height, hip ripple, hip offset, foot clearance and link lengths. Based on these variables and their influence on the energy flow, the performance measures are discussed and the results compared with those observed in nature.

This paper studies the performance of a variable structure algorithm in the position/force hybrid control of robotic manipulators: It is shown that a reformulation of the kinematic position loop using pseudo-inverses improves the system response namely in the neighbourhood of singular points. The robustness and the system dynamics are analysed in terms of frequency and time responses.

In this paper it is studied the implementation of fractional-order algorithms in the position/force hybrid control of robotic manipulators. The system robustness and performances are analysed, in terms of time responses, and compared with other control approaches. Moreover, it is also investigated the effect of nonlinear phenomena at the robot joints such as nonlinear friction, dynamic backlash and flexibility.

A new approach to the analysis and design of robot manipulators is presented. The novel feature resides on a non-standard formulation to the modelling problem. Usually, system descriptions are based on a set of differential equations which, in general, require laborious computations and may be difficult to analyse. These facts motivate the need of alternative models based on different mathematical concepts. The proposed statistical approach to the Fourier modelling gives clear guidelines towards the optimisation of the robot kinematics and points out structural characteristics of the trajectory planning algorithms.

This paper presents the kinematic study of robotic biped locomotion systems. The main purpose is to determine the kinematic characteristics and the system performance during walking. For that objective, the prescribed motion of the biped is completely characterised in terms of five locomotion variables: step length, hip height, maximum hip ripple, maximum foot clearance and link lengths. In this work, we propose three methods to quantitatively measure the performance of the walking robot: locomobility measure, perturbation analysis and low-pass frequency response. These performance measures are discussed and compared in determining the robustness and effectiveness of the resulting locomotion.

This paper investigates the control of robots with nonlinear friction and dynamic backlash in the joints. The study is based on the describing function (DF) of nonlinear systems. The controllers studied are the first order model and the second order model variable structure controllers (FOM-VSC and SOM-VSC). The authors start by studying nonlinear plants consisting of a mass subjected to Coulomb plus viscous friction or two masses subjected to dynamic backlash. The worst case for the limit cycle generation is found to be the closed-loop system having two masses with backlash. On the other hand, the closed-loop system of a mass with nonlinear friction is found to be amenable to control without limit cycles. By decoupling the joints of the robot the authors find similar results within a good accuracy range.

A statistical analysis of biomechanical manipulators is presented. The approach presented stems from studies of the properties of joint-actuated manipulators. Motivated by the kinesiological aspects of the human arm, it is demonstrated that biomechanical structures have better performances than standard manipulators. In fact, joint-actuated robotic structures are non-optimal because they have to support the direct impact of the operational requirements, while muscle-actuated arms are superior because they have anatomic levers and actuators more adapted to the transients required by the operational tasks. Therefore, these results are a step towards the design of a new generation of better mechanical manipulators.>