An Efficient Parameterization of Dynamic Neural Networks for Nonlinear System Identification

Dynamic neural networks (DNNs), which are also known as recurrent neural networks, are often used for nonlinear system identification. The main contribution of this letter is the introduction of an efficient parameterization of a class of DNNs. Having to adjust less parameters simplifies the training problem and leads to more parsimonious models. The parameterization is based on approximation theory dealing with the ability of a class of DNNs to approximate finite trajectories of nonautonomous systems. The use of the proposed parameterization is illustrated through a numerical example, using data from a nonlinear model of a magnetic levitation system.

Design of a minimum variance multiple input-multiple output neuro self-tuning proportional-integral-derivative controller for non-linear dynamic systems

In this study a minimum variance neuro self-tuning proportional-integral-derivative (PID) controller is designed for complex multiple input-multiple output (MIMO) dynamic systems. An approximation model is constructed, which consists of two functional blocks. The first block uses a linear submodel to approximate dominant system dynamics around a selected number of operating points. The second block is used as an error agent, implemented by a neural network, to accommodate the inaccuracy possibly introduced by the linear submodel approximation, various complexities/uncertainties, and complicated coupling effects frequently exhibited in non-linear MIMO dynamic systems. With the proposed model structure, controller design of an MIMO plant with n inputs and n outputs could be, for example, decomposed into n independent single input-single output (SISO) subsystem designs. The effectiveness of the controller design procedure is initially verified through simulations of industrial examples.

Dynamic modulation of human motor activity when observing actions

Previous studies have demonstrated that when we observe somebody else executing an action many areas of our own motor systems are active. It has been argued that these motor activations are evidence that we motorically simulate observed actions; this motoric simulation may support various functions such as imitation and action understanding. However, whether motoric simulation is indeed the function of motor activations during action observation is controversial, due to inconsistency in findings. Previous studies have demonstrated dynamic modulations in motor activity when we execute actions. Therefore, if we do motorically simulate observed actions, our motor systems should also be modulated dynamically, and in a corresponding fashion, during action observation. Using magnetoencephalography (MEG), we recorded the cortical activity of human participants while they observed actions performed by another person. Here, we show that activity in the human motor system is indeed modulated dynamically during action observation. The finding that activity in the motor system is modulated dynamically when observing actions can explain why studies of action observation using functional magnetic resonance imaging (fMRI) have reported conflicting results, and is consistent with the hypothesis that we motorically simulate observed actions.

Enantiospecific adsorption of alanine on the chiral Cu{531} surface

We have studied enantiospecific differences in the adsorption of (S)- and (R)-alanine on Cu{531}R using low-energy electron diffraction (LEED), X-ray photoelectron spectroscopy, and near edge X-ray absorption fine structure (NEXAFS) spectroscopy. At saturation coverage, alanine adsorbs as alaninate forming a p(1 4) superstructure. LEED shows a significantly higher degree of long-range order for the S than for the R enantiomer. Also carbon K-edge NEXAFS spectra show differences between (S)- and (R)-alanine in the variations of the ð resonance when the linear polarization vector is rotated within the surface plane. This indicates differences in the local adsorption geometries of the molecules, most likely caused by the interaction between the methyl group and the metal surface and/or intermolecular hydrogen bonds. Comparison with model calculations and additional information from LEED and photoelectron spectroscopy suggest that both enantiomers of alaninate adsorb in two different orientations associated with triangular adsorption sites on {110} and {311} microfacets of the Cu{531} surface. The experimental data are ambiguous as to the exact difference between the local geometries of the two enantiomers. In one of two models that fit the data equally well, significantly more (R)-alaninate molecules are adsorbed on {110} sites than on {311} sites whereas for (S)-alaninate the numbers are equal. The enantiospecific differences found in these experiments are much more pronounced than those reported from other ultrahigh vacuum techniques applied to similar systems.

Water adsorption on O-covered Ru{0001}: coverage-dependent change from dissociation to molecular adsorption

When water is coadsorbed with oxygen at coverages above 0.25ML an intact water species is observed in high resolution X-ray photoelectron spectroscopy up to 220 K, which is significantly more stable than intact water on the clean surface. The presence of this species causes a shift in the O 1s binding energy of the pre-adsorbed oxygen, which indicates the formation of hydrogen bonds between the two adsorbates. Low coverages of oxygen induce partial dissociation and recombinative desorption in the same temperature range, which illustrates that desorption temperatures alone cannot be used to determine whether water is molecularly intact or not.

The exclusive use of integer-order spots for LEED-IV structure analysis of adsorption systems: p(2×2)-O on Ni{111}

Two different ways of performing low-energy electron diffraction (LEED) structure determinations for the p(2 x 2) structure of oxygen on Ni {111} are compared: a conventional LEED-IV structure analysis using integer and fractional-order IV-curves collected at normal incidence and an analysis using only integer-order IV-curves collected at three different angles of incidence. A clear discrimination between different adsorption sites can be achieved by the latter approach as well as the first and the best fit structures of both analyses are within each other's error bars (all less than 0.1 angstrom). The conventional analysis is more sensitive to the adsorbate coordinates and lateral parameters of the substrate atoms whereas the integer-order-based analysis is more sensitive to the vertical coordinates of substrate atoms. Adsorbate-related contributions to the intensities of integer-order diffraction spots are independent of the state of long-range order in the adsorbate layer. These results show, therefore, that for lattice-gas disordered adsorbate layers, for which only integer-order spots are observed, similar accuracy and reliability can be achieved as for ordered adsorbate layers, provided the data set is large enough.

Effect of oxygen adsorption on the chiral pt{531} surface

The adsorption of oxygen on the chiral Pt{531} surface was studied by high-resolution X-ray photoelectron spectroscopy (HRXPS) and low energy electron diffraction (LEED). After the surface is annealed in oxygen (3 x 10(-7) mbar), three O 1s peaks are observed in XPS. One peak, at 529.5 eV, is assigned to chemisorbed oxygen; it disappears after annealing in vacuo to temperatures above 900 K. The other two peaks at 530.8 and 532.3 eV are stable up to at least 1250 K. They are associated with oxide clusters on the surface. These clusters readily react with coadsorbed carbon monoxide at temperatures between 315 and 620 K.

Adsorption and dissociation of benzene on bimetallic surfaces - the influence of surface geometry and electronic structure

This topical review discusses the influence of the surface geometry (e.g. lattice parameters and termination) and electronic structure of well-defined bimetallic surfaces on the adsorption and dissociation of benzene. The available data can be divided into two categories with combinations of non-transition metals and transition metals on the one side and combinations of two transition metals on the other. The main effect of non-transition metals in surface alloys is site blocking which can suppress chemisorption and dissociation of the molecules completely. When two transition metals are combined, the effects are less dramatic. They mainly affect the strength of the chemisorption bond and the degree of dissociation due to electronic and template effects.

Charge transfer in Cr adsorption and reaction at the rutile TiO2(110) surface

The rutile TiO2(110) surface has been doped with sub-monolayer metallic Cr, which oxidises and donates charge to specific surface Ti ions. X-Ray and ultra violet photoemission spectroscopy and first principles density functional theory with Hubbard U are used to assign the oxidation states of Cr and surface Ti and we find that Cr2+ forms on bridging oxygen ions and a 5-fold coordinated surface Ti atom is reduced to Ti3+ and the Cr ions readily react with oxygen (to Cr3+), which leads to depletion of surface Ti3+ 3d electrons.

Dynamic shear modulus of isotropic elastomers

We have investigated the dynamic mechanical behavior of two cross-linked polymer networks with very different topologies: one made of backbones randomly linked along their length; the other with fixed-length strands uniformly cross-linked at their ends. The samples were analyzed using oscillatory shear, at very small strains corresponding to the linear regime. This was carried out at a range of frequencies, and at temperatures ranging from the glass plateau, through the glass transition, and well into the rubbery region. Through the glass transition, the data obeyed the time-temperature superposition principle, and could be analyzed using WLF treatment. At higher temperatures, in the rubbery region, the storage modulus was found to deviate from this, taking a value that is independent of frequency. This value increased linearly with temperature, as expected for the entropic rubber elasticity, but with a substantial negative offset inconsistent with straightforward enthalpic effects. Conversely, the loss modulus continued to follow time-temperature superposition, decreasing with increasing temperature, and showing a power-law dependence on frequency.

Flow-induced dynamic surface tension effects at nanoscale

The aim of this study is to investigate flow-induced dynamic surface tension effects, similar to the well-known Marangoni phenomena, but solely generated by the nanoscale topography of the substrates. The flow-induced surface tension effects are examined on the basis of a sharp interface theory. It is demonstrated how nanoscale objects placed at the boundary of the flow domain result in the generation of substantial surface forces acting on the bulk flow.

A neural network enhanced generalized minimum variance self-tuning proportional, integral and derivative control algorithm for complex dynamic systems

A neural network enhanced proportional, integral and derivative (PID) controller is presented that combines the attributes of neural network learning with a generalized minimum-variance self-tuning control (STC) strategy. The neuro PID controller is structured with plant model identification and PID parameter tuning. The plants to be controlled are approximated by an equivalent model composed of a simple linear submodel to approximate plant dynamics around operating points, plus an error agent to accommodate the errors induced by linear submodel inaccuracy due to non-linearities and other complexities. A generalized recursive least-squares algorithm is used to identify the linear submodel, and a layered neural network is used to detect the error agent in which the weights are updated on the basis of the error between the plant output and the output from the linear submodel. The procedure for controller design is based on the equivalent model, and therefore the error agent is naturally functioned within the control law. In this way the controller can deal not only with a wide range of linear dynamic plants but also with those complex plants characterized by severe non-linearity, uncertainties and non-minimum phase behaviours. Two simulation studies are provided to demonstrate the effectiveness of the controller design procedure.