Auto-weighted minimum-variance self-tuning controller

A self-tuning controller which automatically assigns weightings to control and set-point following is introduced. This discrete-time single-input single-output controller is based on a generalized minimum-variance control strategy. The automatic on-line selection of weightings is very convenient, especially when the system parameters are unknown or slowly varying with respect to time, which is generally considered to be the type of systems for which self-tuning control is useful. This feature also enables the controller to overcome difficulties with non-minimum phase systems.

Simplified parameter adaptive control

A simple parameter adaptive controller design methodology is introduced in which steady-state servo tracking properties provide the major control objective. This is achieved without cancellation of process zeros and hence the underlying design can be applied to non-minimum phase systems. As with other self-tuning algorithms, the design (user specified) polynomials of the proposed algorithm define the performance capabilities of the resulting controller. However, with the appropriate definition of these polynomials, the synthesis technique can be shown to admit different adaptive control strategies, e.g. self-tuning PID and self-tuning pole-placement controllers. The algorithm can therefore be thought of as an embodiment of other self-tuning design techniques. The performances of some of the resulting controllers are illustrated using simulation examples and the on-line application to an experimental apparatus.

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.

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.

Approximation of non-autonomous dynamic systems by continuous time recurrent neural networks

This work provides a framework for the approximation of a dynamic system of the form x˙=f(x)+g(x)u by dynamic recurrent neural network. This extends previous work in which approximate realisation of autonomous dynamic systems was proven. Given certain conditions, the first p output neural units of a dynamic n-dimensional neural model approximate at a desired proximity a p-dimensional dynamic system with n>p. The neural architecture studied is then successfully implemented in a nonlinear multivariable system identification case study.

(PDF, 406 KB) On L3 acquisition and phonological permeability: a new test case for debates on the mental representation of non-native phonological systems

The goal of this article is to make an epistemological and theoretical contribution to the nascent field of third language (L3) acquisition and show how examining L3 development can offer a unique view into longstanding debates within L2 acquisition theory. We offer the Phonological Permeability Hypothesis (PPH), which maintains that examining the development of an L3/Ln phonological system and its effects on a previously acquired L2 phonological system can inform contemporary debates regarding the mental constitution of postcritical period adult phonological acquisition. We discuss the predictions and functional significance of the PPH for adult SLA and multilingualism studies, detailing a methodology that examines the effects of acquiring Brazilian Portuguese on the Spanish phonological systems learned before and after the so-called critical period (i.e., comparing simultaneous versus successive adult English-Spanish bilinguals learning Brazilian Portuguese as an L3).

Fat and fatty acid composition of cooked meat from UK retail chickens labelled as from organic and non-organic production systems

This study compared fat and fatty acids in cooked retail chicken meat from conventional and organic systems. Fat contents were 1.7, 5.2, 7.1 and 12.9 g/100 g cooked weight in skinless breast, breast with skin, skinless leg and leg with skin respectively, with organic meat containing less fat overall (P < 0.01). Meat was rich in cis-monounsaturated fatty acids, although organic meat contained less than did conventional meat (1850 vs. 2538 mg/100 g; P < 0.001). Organic meat was also lower (P < 0.001) in 18:3 n−3 (115 vs. 180 mg/100 g) and, whilst it contained more (P < 0.001) docosahexaenoic acid (30.9 vs. 13.7 mg/100 g), this was due to the large effect of one supermarket. This system by supermarket interaction suggests that poultry meat labelled as organic is not a guarantee of higher long chain n−3 fatty acids. Overall there were few major differences in fatty acid contents/profiles between organic and conventional meat that were consistent across all supermarkets.

Robust blind deconvolution algorithm: variance approximation and series decoupling

An alternative blind deconvolution algorithm for white-noise driven minimum phase systems is presented and verified by computer simulation. This algorithm uses a cost function based on a novel idea: variance approximation and series decoupling (VASD), and suggests that not all autocorrelation function values are necessary to implement blind deconvolution.

Numerical modelling of two-way propagation of non-linear dispersive waves

We describe and implement a fully discrete spectral method for the numerical solution of a class of non-linear, dispersive systems of Boussinesq type, modelling two-way propagation of long water waves of small amplitude in a channel. For three particular systems, we investigate properties of the numerically computed solutions; in particular we study the generation and interaction of approximate solitary waves.

Estimating the direct aerosol radiative perturbation: impact of ocean surface representation and aerosol non-sphericity

Atmospheric aerosols are now actively studied, in particular because of their radiative and climate impacts. Estimations of the direct aerosol radiative perturbation, caused by extinction of incident solar radiation, usually rely on radiative transfer codes and involve simplifying hypotheses. This paper addresses two approximations which are widely used for the sake of simplicity and limiting the computational cost of the calculations. Firstly, it is shown that using a Lambertian albedo instead of the more rigorous bidirectional reflectance distribution function (BRDF) to model the ocean surface radiative properties leads to large relative errors in the instantaneous aerosol radiative perturbation. When averaging over the day, these errors cancel out to acceptable levels of less than 3% (except in the northern hemisphere winter). The other scope of this study is to address aerosol non-sphericity effects. Comparing an experimental phase function with an equivalent Mie-calculated phase function, we found acceptable relative errors if the aerosol radiative perturbation calculated for a given optical thickness is daily averaged. However, retrieval of the optical thickness of non-spherical aerosols assuming spherical particles can lead to significant errors. This is due to significant differences between the spherical and non-spherical phase functions. Discrepancies in aerosol radiative perturbation between the spherical and non-spherical cases are sometimes reduced and sometimes enhanced if the aerosol optical thickness for the spherical case is adjusted to fit the simulated radiance of the non-spherical case.

The effect of wheat straw residue on the emergence and early growth of sugar beet (Beta vulgaris) and oilseed rape (Brassica napus)

The management of straw residue can be a concern in non-inversion tillage systems where straw tends to be incorporated at shallow depths or left on the soil surface. This can lead to poor crop establishment because straw residue can impede or hinder crop emergence and growth. Small container-based experiments were undertaken using varying amounts of wheat straw residue either incorporated or placed oil the soil surface. The effects on (lays to seedling emergence, percentage emergence, seedling dry-weight and soil temperature using sugar beet and oilseed rape were investigated because these crops often follow wheat in a cropping sequence. The position of the straw residue was found to be the primary factor in reducing crop emergence and growth. Increasing the amount of straw residue (from 3.3 t ha(-1) to 6.7 t ha(-1)) did not show any consistent trends in reducing crop emergence or growth. However, in some instances, results indicated that an interaction between the position and the amount of straw residue Occurred particularly when the straw and seed was placed on the soil surface. Straw placed on the soil surface significantly reduced mean day-time soil temperature by approximately 2.5 degrees C compared to no residue. When the seed and straw was placed on the soil Surface a lack of seed-to-soil contact caused a reduction in emergence by approximately 30% because of the restriction in available moisture that limited the ability for seed imbibition. This trend was reversed when the seed was placed in the soil, but with straw residue still on the soil surface, because the surface straw was likely to reduce moisture evaporation and improved seed-to-soil contact that led to rapid emergence. In general, when straw was mixed in or placed on the soil surface along with the seed, sugar beet and oilseed rape emergence and early growth biomass was significantly restricted by approximately 50% compared to no residue. The consequences of placing seed with or near to straw residue have been shown to cause a restriction in crop establishment. In both oilseed tape and sugar beet, this could lead to a reduction in final crop densities, poor, uneven growth and potentially lower yields that could lower financial margins. Therefore, if farmers are planning to use non-inversion tillage methods for crop establishment, the management and removal of straw residue from near or above the seed is considered important for successful crop establishment. (C) 2008 Elsevier B.V. All rights reserved.

Cumulant-based deconvolution and identification: several new families of linear equations

This paper presents several new families of cumulant-based linear equations with respect to the inverse filter coefficients for deconvolution (equalisation) and identification of nonminimum phase systems. Based on noncausal autoregressive (AR) modeling of the output signals and three theorems, these equations are derived for the cases of 2nd-, 3rd and 4th-order cumulants, respectively, and can be expressed as identical or similar forms. The algorithms constructed from these equations are simpler in form, but can offer more accurate results than the existing methods. Since the inverse filter coefficients are simply the solution of a set of linear equations, their uniqueness can normally be guaranteed. Simulations are presented for the cases of skewed series, unskewed continuous series and unskewed discrete series. The results of these simulations confirm the feasibility and efficiency of the algorithms.

When long-range zero-lag synchronization is feasible in cortical networks

Many studies have reported long-range synchronization of neuronal activity between brain areas, in particular in the beta and gamma bands with frequencies in the range of 14–30 and 40–80 Hz, respectively. Several studies have reported synchrony with zero phase lag, which is remarkable considering the synaptic and conduction delays inherent in the connections between distant brain areas. This result has led to many speculations about the possible functional role of zero-lag synchrony, such as for neuronal communication, attention, memory, and feature binding. However, recent studies using recordings of single-unit activity and local field potentials report that neuronal synchronization may occur with non-zero phase lags. This raises the questions whether zero-lag synchrony can occur in the brain and, if so, under which conditions. We used analytical methods and computer simulations to investigate which connectivity between neuronal populations allows or prohibits zero-lag synchrony. We did so for a model where two oscillators interact via a relay oscillator. Analytical results and computer simulations were obtained for both type I Mirollo–Strogatz neurons and type II Hodgkin–Huxley neurons. We have investigated the dynamics of the model for various types of synaptic coupling and importantly considered the potential impact of Spike-Timing Dependent Plasticity (STDP) and its learning window. We confirm previous results that zero-lag synchrony can be achieved in this configuration. This is much easier to achieve with Hodgkin–Huxley neurons, which have a biphasic phase response curve, than for type I neurons. STDP facilitates zero-lag synchrony as it adjusts the synaptic strengths such that zero-lag synchrony is feasible for a much larger range of parameters than without STDP.

Fluorinated ionic surfactant microemulsions in hydrofluorocarbon 134a (HFC 134a)

The factors influencing the formation of water-in-134a-propellant microemulsions using the fluorinated ionic surfactants ammonium perfluorooctanoate, ammonium perfluoroheptanoate, and sodium perfluorooctanoate has been determined. None of the fluorinated ionic surfactants could be used to prepare clear, one-phase systems when used as sole surfactant, but they could be when combined with a short-chain fluoro- or hydrocarbon alcohol in surfactant:cosurfactant weight-mixing ratios (K(m)) in the range 1:2 to 2:1. When hydrocarbon alcohols were used this clear region extended over a wide range of compositions and was confirmed by means of photon correlation spectroscopy (PCS) to contain microemulsion droplets in the propellant-rich part of the phase diagram. PCS studies performed in the presence of the water-soluble drug terbutaline sulfate showed that it was possible to solubilize the drug within water-in-propellant microemulsion droplets. These studies confirm for the first time that it is possible to prepare water-in-propellant 134a microemulsions using fluorinated ionic surfactants and to solubilize water-soluble drugs within these systems.

Formation of fluorinated nonionic surfactant microemulsions in hydrofluorocarbon 134a (HFC 134a)

A structurally related series of fluorinated nonionic oxyethylene glycol surfactants of the type C(m)F(2m+1)(CH(2))(n)O[(CH(2)CH(2)O)(p)H], denoted C(m.n)E(p) (where m=4, 6, or 7, m=1 or 2, and p=4 or 6) were synthesized and their surface behavior in aqueous solution was characterized. The ability of these surfactants to form water-in-hydrofluorocarbon (HFC) propellant 134a microemulsions suitable for use in the aerosolized delivery of water-soluble drugs has been investigated. Phase studies showed that, regardless of the composition used, clear one-phase systems could not be prepared if a fluorinated nonionic surfactant was used alone, or in combination with a short or medium fluorocarbon alcohol cosurfactant. Clear one-phase systems could, however, be prepared if a short-chain hydrocarbon alcohol, such as ethanol, n-propanol, or n-pentanol, was used as cosurfactant, with the extent of the one-phase region increasing with decreased chain length of the alcohol cosurfactant. Light-scattering studies on a number of the hydrocarbon-alcoholcontaining systems in the propellant-rich part of the phase diagram showed that only systems prepared with C(4.2)E(6) and propanol contained microemulsion droplets (all other systems investigated were considered to be cosolvent systems).