Neurofuzzy control using Kalman filtering state feedback with coloured noise for unknown non-linear processes

This paper presents a controller design scheme for a priori unknown non-linear dynamical processes that are identified via an operating point neurofuzzy system from process data. Based on a neurofuzzy design and model construction algorithm (NeuDec) for a non-linear dynamical process, a neurofuzzy state-space model of controllable form is initially constructed. The control scheme based on closed-loop pole assignment is then utilized to ensure the time invariance and linearization of the state equations so that the system stability can be guaranteed under some mild assumptions, even in the presence of modelling error. The proposed approach requires a known state vector for the application of pole assignment state feedback. For this purpose, a generalized Kalman filtering algorithm with coloured noise is developed on the basis of the neurofuzzy state-space model to obtain an optimal state vector estimation. The derived controller is applied in typical output tracking problems by minimizing the tracking error. Simulation examples are included to demonstrate the operation and effectiveness of the new approach.

Neural network control of a simple mobile robot

In recent years researchers in the Department of Cybernetics have been developing simple mobile robots capable of exploring their environment on the basis of the information obtained from a few simple sensors. These robots are used as the test bed for exploring various behaviours of single and multiple organisms: the work is inspired by considerations of natural systems. In this paper we concentrate on that part of the work which involves neural networks and related techniques. These neural networks are used both to process the sensor information and to develop the strategy used to control the robot. Here the robots, their sensors, and the neural networks used and all described. 1.

Enhancing model predictive control using dynamic data reconciliation

The use of data reconciliation techniques can considerably reduce the inaccuracy of process data due to measurement errors. This in turn results in improved control system performance and process knowledge. Dynamic data reconciliation techniques are applied to a model-based predictive control scheme. It is shown through simulations on a chemical reactor system that the overall performance of the model-based predictive controller is enhanced considerably when data reconciliation is applied. The dynamic data reconciliation techniques used include a combined strategy for the simultaneous identification of outliers and systematic bias.

Genetic algorithms for optimal control of beer fermentation

This paper uses genetic algorithms to optimise the mathematical model of a beer fermentation process that operates in batch mode. The optimisation is based in adjusting the temperature profile of the mixture during a fixed period of time in order to reach the required ethanol levels but considering certain operational and quality restrictions.

Integrating predictive control and economic optimisation

In most commercially available predictive control packages, there is a separation between economic optimisation and predictive control, although both algorithms may be part of the same software system. This method is compared in this article with two alternative approaches where the economic objectives are directly included in the predictive control algorithm. Simulations are carried out using the Tennessee Eastman process model.

Dynamic data reconciliation for sequential modular simulators: application to a mixing process

This paper describes a method for dynamic data reconciliation of nonlinear systems that are simulated using the sequential modular approach, and where individual modules are represented by a class of differential algebraic equations. The estimation technique consists of a bank of extended Kalman filters that are integrated with the modules. The paper reports a study based on experimental data obtained from a pilot scale mixing process.

New developments in batch process input profile optimisation

A novel algorithm for solving nonlinear discrete time optimal control problems with model-reality differences is presented. The technique uses dynamic integrated system optimisation and parameter estimation (DISOPE) which achieves the correct optimal solution in spite of deficiencies in the mathematical model employed in the optimisation procedure. A new method for approximating some Jacobian trajectories required by the algorithm is introduced. It is shown that the iterative procedure associated with the algorithm naturally suits applications to batch chemical processes.

Development and application of a novel algorithm for steady-state optimising control using dynamic information

A novel optimising controller is designed that leads a slow process from a sub-optimal operational condition to the steady-state optimum in a continuous way based on dynamic information. Using standard results from optimisation theory and discrete optimal control, the solution of a steady-state optimisation problem is achieved by solving a receding-horizon optimal control problem which uses derivative and state information from the plant via a shadow model and a state-space identifier. The paper analyzes the steady-state optimality of the procedure, develops algorithms with and without control rate constraints and applies the procedure to a high fidelity simulation study of a distillation column optimisation.

The control of dynamical systems by neural networks

In this paper the use of neural networks for the control of dynamical systems is considered. Both identification and feedback control aspects are discussed as well as the types of system for which neural networks can provide a useful technique. Multi-layer Perceptron and Radial Basis function neural network types are looked at, with an emphasis on the latter. It is shown how basis function centre selection is a critical part of the implementation process and that multivariate clustering algorithms can be an extremely useful tool for finding centres.

Improved process topology for membrane distillation

In membrane distillation in a conventional membrane module, the enthalpies of vaporisation and condensation are supplied and removed by changes in the temperatures of the feed and permeate streams, respectively. Less than 5% of the feed can be distilled in a single pass, because the potential changes in the enthalpies of the liquid streams are much smaller than the enthalpy of vaporisation. Furthermore, the driving force for mass transfer reduces as the feed stream temperature and vapour pressure fall during distillation. These restrictions can be avoided if the enthalpy of vaporisation is uncoupled from the heat capacities of the feed and permeate streams. A specified distillation can then be effected continuously in a single module. Calculations are presented which estimate the performance of a flat plate unit in which the enthalpy of distillation is supplied and removed by the condensing and boiling of thermal fluids in separate circuits, and the imposed temperature difference is independent of position. Because the mass flux through the membrane is dependent on vapour pressure, membrane distillation is suited to applications with a high membrane temperature. The maximum mass flux in the proposed module geometry is predicted to be 30 kg/m2 per h at atmospheric pressure when the membrane temperature is 65°C. Operation at higher membrane temperatures is predicted to raise the mass flux, for example to 85 kg/m2 per h at a membrane temperature of 100°C. This would require pressurisation to 20 bar to prevent boiling at the heating plate of the feed channel. Pre-pressurisation of the membrane pores and control of the dissolved gas concentrations in the feed and the recyled permeate should be investigated as a means to achieve high temperature membrane distillation without pore penetration and wetting.

The technocratic totalitarianism of construction process improvement: a critical perspective

The current research agenda for construction process improvement is heavily influenced by the rhetoric of business process re-engineering (BPR). In contrast to the wider literature on BPR, there is little evidence of critical thought within the construction management research community. A postmodernist interpretation is advocated whereby the reality of management practice is defined by the dominant management discourse. The persuasiveness of BPR rhetoric is analysed with particular reference to the way in which it plays on the insecurity of modern managers. Despite the lip service given to ‘empowerment’ and ‘teamwork’, the dominant theme of the re-engineering movement is that of technocratic totalitarianism. From a critical perspective, it is suggested that BPR is imposed on construction organizations to ensure continued control by the industry's dominant power groups. Whilst industry leaders are fond of calling for ‘attitudinal and cultural improvement’, the language of the accepted research agenda continually reinforces the industry's dominant culture of ‘control and command’. Therefore, current research directions in process improvement perpetuate existing attitudes rather than facilitating cultural change. The concept of lean construction is seen to be the latest manifestation of this phenomenon.

Dielectric properties of process cheese from 0.3 to 3 Ghz

Dielectric properties of 16 process cheeses were determined over the frequency range 0.3-3 GHz. The effect of temperature on the dielectric properties of process cheeses were investigated at temperature intervals of 10 degrees C between 5 and 85 degrees C. Results showed that the dielectric constant decreased gradually as frequency increased, for all cheeses. The dielectric loss factor (epsilon") decreased from above 125 to below 12 as frequency increased. epsilon' was highest at 5 degrees C and generally decreased up to a temperature between 55 and 75 degrees C. epsilon" generally increased with increasing temperature for high and medium moisture/fat ratio cheeses. epsilon" decreased with temperature between 5 and 55 degrees C and then increased, for low moisture/fat ratio cheese. Partial least square regression models indicated that epsilon' and epsilon" could be used as a quality control screening application to measure moisture content and inorganic salt content of process cheese, respectively. (c) 2005 Elsevier Ltd. All rights reserved..

Theorizing Literacy, Politics and Social Process: revisiting Maktab literacy in Rian in search of a paradigm

Literacy as a social practice is integrally linked with social, economic and political institutions and processes. As such, it has a material base which is fundamentally constituted in power relations. Literacy is therefore interwoven with the text and context of everyday living in which multi-levelled meanings are organically produced at both individual and societal level. This paper argues that if language thus mediates social reality, then it follows that literacy defined as a social practice cannot really be addressed as a reified, neutral activity but that it should take account of the social, cultural and political processes in which literacy practices are embedded. Drawing on the work of key writers within the field, the paper foregrounds the primary role of the state in defining the forms and levels of literacy required and made available at particular moments within society. In a case-study of the social construction of literacy meanings in pre-revolutionary Iran, it explores the view that the discourse about societal literacy levels has historically constituted a key terrain in which the struggle for control over meaning has taken place. This struggle, it is argued, sets the interests of the state to maintain ideological and political control over the production of knowledge within the culture and society over and against the needs identified by the individual for personal development, empowerment and liberation. In an overall sense, the paper examines existing theoretical perspectives on societal literacy programmes in terms of the scope that they provide for analyses that encompass the multi-levelled power relations that shape and influence dominant discourses on the relative value of literacy for both the individual and society

Chemical characterisation and determination of sensory attributes of hydrolysates produced by enzymatic hydrolysis of whey proteins following a novel integrative process

The overall aim of this work was to characterize the major angiotensin converting enzyme (ACE) inhibitory peptides produced by enzymatic hydrolysis of whey proteins, through the application of a novel integrative process. This process consisted of the combination of adsorption and microfiltration within a stirred cell unit for the selective immobilization of β-lactoglobulin and casein derived peptides (CDP) from whey. The adsorbed proteins were hydrolyzed in-situ which resulted in the separation of peptide products from the substrate and fractionation of peptides. Two different hydrolysates were produced: (i) from CDP (IC50 =287μg/mL) and (ii) from β-lactoglobulin (IC50=128μg/mL). IC50 is the concentration of inhibitor needed to inhibit ACE by half. The well known antihypertensive peptide IPP and several novel peptides that have structural similarities with reported ACE inhibitory peptides were identified and characterized in both hydrolysates. Furthermore, the hydrolysates were assessed for bitterness. No significant difference was found between the control (milk with no hydrolysate) and hydrolysate samples at different concentrations (at, below and above the IC50).

Endothelin-converting enzyme 1 degrades neuropeptides in endosomes to control receptor recycling

Neuropeptide signaling requires the presence of G protein-coupled receptors (GPCRs) at the cell surface. Activated GPCRs interact with beta-arrestins, which mediate receptor desensitization, endocytosis, and mitogenic signaling, and the peptide-receptor-arrestin complex is sequestered into endosomes. Although dissociation of beta-arrestins is required for receptor recycling and resensitization, the critical event that initiates this process is unknown. Here we report that the agonist availability in the endosomes, controlled by the membrane metalloendopeptidase endothelin-converting enzyme 1 (ECE-1), determines stability of the peptide-receptor-arrestin complex and regulates receptor recycling and resensitization. Substance P (SP) binding to the tachykinin neurokinin 1 receptor (NK1R) induced membrane translocation of beta-arrestins followed by trafficking of the SP-NK1R-beta-arrestin complex to early endosomes containing ECE-1a-d. ECE-1 degraded SP in acidified endosomes, disrupting the complex; beta-arrestins returned to the cytosol, and the NK1R, freed from beta-arrestins, recycled and resensitized. An ECE-1 inhibitor, by preventing NK1R recycling in endothelial cells, inhibited resensitization of SP-induced inflammation. This mechanism is a general one because ECE-1 similarly regulated NK3R resensitization. Thus, peptide availability in endosomes, here regulated by ECE-1, determines the stability of the peptide-receptor-arrestin complex. This mechanism regulates receptor recycling, which is necessary for sustained signaling, and it may also control beta-arrestin-dependent mitogenic signaling of endocytosed receptors. We propose that other endosomal enzymes and transporters may similarly control the availability of transmitters in endosomes to regulate trafficking and signaling of GPCRs. Antagonism of these endosomal processes represents a strategy for inhibiting sustained signaling of receptors, and defects may explain the tachyphylaxis of drugs that are receptor agonists.