A nonlinear disturbance observer for robotic manipulators

A new nonlinear disturbance observer (NDO) for robotic manipulators is derived in this paper. The global exponential stability of the proposed disturbance observer (DO) is guaranteed by selecting design parameters, which depend on the maximum velocity and physical parameters of robotic manipulators. This new observer overcomes the disadvantages of existing DOs, which are designed or analyzed by linear system techniques. It can be applied in robotic manipulators for various purposes such as friction compensation, independent joint control, sensorless torque control and fault diagnosis. The performance of the proposed observer is demonstrated by the friction estimation and compensation for a two-link robotic manipulator. Both simulation and experimental results show the NDO works well

Automated Wind Turbine Pitch Fault Prognosis using ANFIS

Many current wind turbine (WT) studies focus on improving their reliability and reducing the cost of energy, particularly when WTs are operated offshore. WT Supervisory Control and Data Acquisition (SCADA) systems contain alarms and signals that provide significant important information. A possible WT fault can be detected through a rigorous analysis of the SCADA data. This paper proposes a new method for analysing WT SCADA data by using Adaptive Neuro-Fuzzy Inference System (ANFIS) with the aim to achieve automated detection of significant pitch faults. Two existing statistical analysis approaches were applied to detect common pitch fault symptoms. Based on the findings, an ANFIS Diagnosis Procedure was proposed and trained. The trained system was then applied in a wind farm containing 26 WTs to show its prognosis ability for pitch faults. The result was compared to a SCADA Alarms approach and the comparison has demonstrated that the ANFIS approach gives prognostic warning of pitch faults ahead of pitch alarms. Finally, a Confusion Matrix analysis was made to show the accuracy of the proposed approach

A volume-preserving sharpening approach for the propagation of sharp phase boundaries in multiphase lattice Boltzmann simulations

Lattice Boltzmann models that recover a macroscopic description of multiphase flow of immiscible liquids typically represent the boundaries between phases using a scalar function, the phase field, that varies smoothly over several grid points. Attempts to tune the model parameters to minimise the thicknesses of these interfaces typically lead to the interfaces becoming fixed to the underlying grid instead of advecting with the fluid velocity. This phenomenon, known as lattice pinning, is strikingly similar to that associated with the numerical simulation of conservation laws coupled to stiff algebraic source terms. We present a lattice Boltzmann formulation of the model problem proposed by LeVeque and Yee [J. Comput. Phys. 86, 187] to study the latter phenomenon in the context of computational combustion, and offer a volume-conserving extension in multiple space dimensions. Inspired by the random projection method of Bao and Jin [J. Comput. Phys. 163, 216] we further generalise this formulation by introducing a uniformly distributed quasi-random variable into the term responsible for the sharpening of phase boundaries. This method is mass conserving and the statistical average of this method is shown to significantly delay the onset of pinning

Proteomic analysis of the rat ovary following chronic low-dose exposure to 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD)

2,3,7,8-Tetrachlorodibenzo-p-dioxin (TCDD) is a ubiquitously distributed endocrine-disrupting chemical and reproductive toxicant. In order to elucidate low-dose TCDD-mediated effects on reproductive or endocrine functions, female Sprague-Dawley rats were orally administered various concentrations (20, 50, or 125 ng/kg once weekly) TCDD for 29 wk. A proteomic analysis of the ovaries by two-dimensional gel electrophoresis and matrix-assisted laser desorption/ionization (MALDI) tandem mass spectrometry showed distinct changes in the levels of several proteins that are relevant markers of TCDD toxicity. Serum estradiol (E2) levels of TCDD-treated animals were markedly lower than control. There were no significant differences in bone mineral density (BMD) of femurs. The body weight of the 125-ng/kg TCDD group was significantly decreased relative to control and there was also a significant reduction in absolute and relative ovarian weights. Expressions of selenium binding protein 2, glutathione S-transferase mu type 3, Lrpap1 protein, NADPH, and peptidylprolyl isomerase D were upregulated, while prohibitin and N-ethylmaleimide-sensitive factor expression levels were downregulated. Data provide further insight into the mechanisms by which TCDD disrupts ovarian function by indicating which differential protein expressions following low-dose TCDD exposure

Viewing the efficiency of chaos control

This paper aims to cast some new light on controlling chaos using the OGY- and the Zero-Spectral-Radius methods. In deriving those methods we use a generalized procedure differing from the usual ones. This procedure allows us to conveniently treat maps to be controlled bringing the orbit to both various saddles and to sources with both real and complex eigenvalues. We demonstrate the procedure and the subsequent control on a variety of maps. We evaluate the control by examining the basins of attraction of the relevant controlled systems graphically and in some cases analytically

Physical motivations of the constitutive relations for ferroelectric ceramics and the existence of butterfly and hysteresis loops

The responses of ferroelectric ceramics can be quite complex depending on the physical processes to which they are subjected. Their mechanical, electromechanical and dielectric properties depend on domain switching, dipole dynamics and phase transformation which can be caused by external stimuli such as mechanical and electrical loadings, and temperature variations. A theory, taking into account the effects of domain switching and dipole dynamics, has been formulated, and in its present stage of development is sufficient to characterize various observable resonses. Specifically, a special case of the theory predicts the nature of the butterfly and hysteresis loops. The butterfly and hysteresis loops are manifestations of the mechanical, electro-mechanical and dielectric responses due to domain switching produced by cyclic electric fields. Comparisons of the predictions of the theory with experimental results are made in a pseudo one dimensional context

Green functions of the spectral ball and symmetrized polydisk

The Green function of the spectral ball is constant over the isospectral varieties, is never less than the pullback of its counterpart on the symmetrized polydisk, and is equal to it in the generic case where the pole is a cyclic (non-derogatory) matrix. When the pole is derogatory, the inequality is always strict, and the difference between the two functions depends on the order of nilpotence of the strictly upper triangular blocks that appear in the Jordan decomposition of the pole. In particular, the Green function of the spectral ball is not symmetric in its arguments. Additionally, some estimates are given for invariant functions in the symmetrized polydisc, e.g. (infinitesimal versions of) the Carath\'eodory distance and the Green function, that show that they are distinct in dimension greater or equal to $3$.Comment: 12 page

Cell nuclei detection using globally optimal active contours with shape prior

Cell nuclei detection in fluorescent microscopic images is an important and time consuming task for a wide range of biological applications. Blur, clutter, bleed through and partial occlusion of nuclei make this a challenging task for automated detection of individual nuclei using image analysis. This paper proposes a novel and robust detection method based on the active contour framework. The method exploits prior knowledge of the nucleus shape in order to better detect individual nuclei. The method is formulated as the optimization of a convex energy function. The proposed method shows accurate detection results even for clusters of nuclei where state of the art methods fail

A novel hybrid teaching learning based multi-objective particle swarm optimization

How to obtain a good convergence and well-spread optimal Pareto front is still a major challenge for most meta-heuristic multi-objective optimization (MOO) methods. In this paper, a novel hybrid teaching learning based particle swarm optimization (HTL-PSO) with circular crowded sorting (CCS), named HTL-MOPSO, is proposed for solving MOO problems. Specifically, the new HTL-MOPSO combines the canonical PSO search with a teaching-learning-based optimization (TLBO) algorithm in order to promote the diversity and improve search ability. Also, CCS technique is developed to improve the diversity and spread of solutions when truncating the external elitism archive. The performance of HTL-MOPSO algorithm was tested on several well-known benchmarks problems and compared with other state-of-the-art MOO algorithms in respect of convergence and spread of final solutions to the true Pareto front. Also, the individual contributions made by the strategies of HTL-PSO and CCS are analyzed. Experimental results validate the effectiveness of HTL-MOPSO and demonstrate its superior ability to find solutions of better spread and diversity, while assuring a good convergence

Synthesis of a pentacyclic precursor to the Strychnos alkaloids

An advanced intermediate for the synthesis of the Strychnos alkaloids was constructed by a sequence involving an intramolecular Diels-Alder reaction, alkylation of an enol silyl ether, and conversion of the alkylation product into a pentacyclic lactam