Adaptive agent-based manufacturing control and its application to flow shop routing control

The manufacturing industry is currently facing unprecedented challenges from changes and disturbances. The sources of these changes and disturbances are of different scope and magnitude. They can be of a commercial nature, or linked to fast product development and design, or purely operational (e.g. rush order, machine breakdown, material shortage etc.). In order to meet these requirements it is increasingly important that a production operation be flexible and is able to adapt to new and more suitable ways of operating. This paper focuses on a new strategy for enabling manufacturing control systems to adapt to changing conditions both in terms of product variation and production system upgrades. The approach proposed is based on two key concepts: (1) An autonomous and distributed approach to manufacturing control based on multi-agent methods in which so called operational agents represent the key physical and logical elements in the production environment to be controlled - for example, products and machines and the control strategies that drive them and (2) An adaptation mechanism based around the evolutionary concept of replicator dynamics which updates the behaviour of newly formed operational agents based on historical performance records in order to be better suited to the production environment. An application of this approach for route selection of similar products in manufacturing flow shops is developed and is illustrated in this paper using an example based on the control of an automobile paint shop.

Bayesian adaptation and adaptively trained systems

As the use of found data increases, more systems are being built using adaptive training. Here transforms are used to represent unwanted acoustic variability, e.g. speaker and acoustic environment changes, allowing a canonical model that models only the "pure" variability of speech to be trained. Adaptive training may be described within a Bayesian framework. By using complexity control approaches to ensure robust parameter estimates, the standard point estimate adaptive training can be justified within this Bayesian framework. However during recognition there is usually no control over the amount of data available. It is therefore preferable to be able to use a full Bayesian approach to applying transforms during recognition rather than the standard point estimates. This paper discusses various approximations to Bayesian approaches including a new variational Bayes approximation. The application of these approaches to state-of-the-art adaptively trained systems using both CAT and MLLR transforms is then described and evaluated on a large vocabulary speech recognition task. © 2005 IEEE.

Adaptive control of combustion instabilities for unknown sign of the high frequency gain

A type of adaptive, closed-loop controllers known as self-tuning regulators present a robust method of eliminating thermoacoustic oscillations in modern gas turbines. These controllers are able to adapt to changes in operating conditions, and require very little pre-characterisation of the system. One piece of information that is required, however, is the sign of the system's high frequency gain (or its 'instantaneous gain'). This poses a problem: combustion systems are infinite-dimensional, and so this information is never known a priori. A possible solution is to use a Nussbaum gain, which guarantees closed-loop stability without knowledge of the sign of the high frequency gain. Despite the theory for such a controller having been developed in the 1980s, it has never, to the authors' knowledge, been demonstrated experimentally. In this paper, a Nussbaum gain is used to stabilise thermoacoustic instability in a Rijke tube. The sign of the high frequency gain of the system is not required, and the controller is robust to large changes in operating conditions - demonstrated by varying the length of the Rijke tube with time. Copyright © 2008 by Simon J. Illingworth & Aimee S. Morgans.

The unusual adaptive expansion of pancreatic ribonuclease gene in carnivora

Pancreatic ribonuclease (RNASE1) is a digestive enzyme that has been recognized to be one of the most attractive model systems for molecular evolutionary studies. The contribution of RNASE1 gene duplication to the functional adaptation of digestive physio

The role of adaptive thermal comfort in the prediction of the thermal performance of a modern mixed-mode office building in the UK under climate change

Climate change is becoming a serious issue for the construction industry, since the time scales at which climate change takes place can be expected to show a true impact on the thermal performance of buildings and HVAC systems. In predicting this future building performance by means of building simulation, the underlying assumptions regarding thermal comfort conditions and the related heating, ventilating and air conditioning (HVAC) control set points become important. This article studies the thermal performance of a reference office building with mixedmode ventilation in the UK, using static and adaptive thermal approaches, for a series of time horizons (2020, 2050 and 2080). Results demonstrate the importance of the implementation of adaptive thermal comfort models, and underpin the case for its use in climate change impact studies. Adaptive thermal comfort can also be used by building designers to make buildings more resilient towards change. © 2010 International Building Performance Simulation Association (IBPSA).

Aquatic agricultural systems in Cambodia: national situation analysis

The objective of the current report produced for the CGIAR Research Program on Aquatic Agricultural Systems (AAS) is to provide basic information on key constraints driving poverty and vulnerability in aquatic agricultural systems in the Tonle Sap region in Cambodia. Six objectives and corresponding research themes are included in the program: sustainable increases in productivity; equitable access to markets; resilience and adaptive capacity; empowering policies and institutions; reduced gender disparity; and expanded benefits for the resource-poor. In this report, the authors review the main aquatic agricultural systems (status, specific policies and strategies, interventions, challenges, and options), then review the main drivers of change. This leads to an identification of plans and strategies important to AAS, with a particular focus on perspectives, gaps and opportunities in national policies, community engagement, increased benefits, adaptive capacity, and gender. This review, of potential interest to decision makers and all development partners, leads to conclusions and recommendations aimed at policymakers and institutional as well as private investors in development.

Real-time experimental demonstration of low-cost VCSEL intensity-modulated 11.25 Gb/s optical OFDM signal transmission over 25 km PON systems.

The feasibility of utilising low-cost, un-cooled vertical cavity surface-emitting lasers (VCSELs) as intensity modulators in real-time optical OFDM (OOFDM) transceivers is experimentally explored, for the first time, in terms of achievable signal bit rates, physical mechanisms limiting the transceiver performance and performance robustness. End-to-end real-time transmission of 11.25 Gb/s 64-QAM-encoded OOFDM signals over simple intensity modulation and direct detection, 25 km SSMF PON systems is experimentally demonstrated with a power penalty of 0.5 dB. The low extinction ratio of the VCSEL intensity-modulated OOFDM signal is identified to be the dominant factor determining the maximum obtainable transmission performance. Experimental investigations indicate that, in addition to the enhanced transceiver performance, adaptive power loading can also significantly improve the system performance robustness to variations in VCSEL operating conditions. As a direct result, the aforementioned capacity versus reach performance is still retained over a wide VCSEL bias (driving) current (voltage) range of 4.5 mA to 9 mA (275 mVpp to 320 mVpp). This work is of great value as it demonstrates the possibility of future mass production of cost-effective OOFDM transceivers for PON applications.

Adaptive modulation induced WDM impairment reduction in optical OFDM PONs

The transmission performance of multi-channel adaptively modulated optical OFDM (AMOOFDM) signals is numerically investigated, for the first time, in optical amplification- and chromatic dispersion compensation-free, intensity-modulation and direct-detection systems incorporating directly modulated DFB lasers (DMLs). It is shown that adaptive modulation not only reduces significantly the nonlinear WDM impairments induced by the effects of cross-phase modulation and four-wave mixing, but also compensates effectively for the DML-induced frequency chirp effect. In comparison with identical modulation, adaptive modulation improves the maximum achievable signal transmission capacity of a central channel by a factor of 1.3 and 3.6 for 40km and 80km SMFs, respectively, with corresponding dynamic input optical power ranges being extended by approximately 5dB. In addition, adaptive modulation also enables cross-channel complementary modulation format mapping, leading to an improved transmission capacity of the entire WDM system. Copyright © 2010 The authors.

QM/MM simulation of liquid water with an adaptive quantum region.

The simulation of complex chemical systems often requires a multi-level description, in which a region of special interest is treated using a computationally expensive quantum mechanical (QM) model while its environment is described by a faster, simpler molecular mechanical (MM) model. Furthermore, studying dynamic effects in solvated systems or bio-molecules requires a variable definition of the two regions, so that atoms or molecules can be dynamically re-assigned between the QM and MM descriptions during the course of the simulation. Such reassignments pose a problem for traditional QM/MM schemes by exacerbating the errors that stem from switching the model at the boundary. Here we show that stable, long adaptive simulations can be carried out using density functional theory with the BLYP exchange-correlation functional for the QM model and a flexible TIP3P force field for the MM model without requiring adjustments of either. Using a primary benchmark system of pure water, we investigate the convergence of the liquid structure with the size of the QM region, and demonstrate that by using a sufficiently large QM region (with radius 6 Å) it is possible to obtain radial and angular distributions that, in the QM region, match the results of fully quantum mechanical calculations with periodic boundary conditions, and, after a smooth transition, also agree with fully MM calculations in the MM region. The key ingredient is the accurate evaluation of forces in the QM subsystem which we achieve by including an extended buffer region in the QM calculations. We also show that our buffered-force QM/MM scheme is transferable by simulating the solvated Cl(-) ion.

Tuneable planar integrated optical systems

Planar integrated free-space optical systems are well suited for a variety of applications, such as optical interconnects and security devices. Here, we demonstrate dynamic functionality of such microoptical systems by the integration of adaptive liquid-crystal-devices. © 2007 Optical Society of America.

Adaptive modally addressed liquid crystal lenses

An adaptive lens, which has variable focus and is rapidly controllable with simple low-power electronics, has numerous applications in optical telecommunications devices, 3D display systems, miniature cameras and adaptive optics. The University of Durham is developing a range of adaptive liquid crystal lenses, and here we describe work on construction of modal liquid crystal lenses. This type of lens was first described by Naumov [1] and further developed by others [24]. In this system, a spatially varying and circularly symmetric voltage profile can be generated across a liquid-crystal cell, generating a lens-like refractive index profile. Such devices are simple in design, and do not require a pixellated structure. The shape and focussing power of the lens can be controlled by the variation of applied electric field and frequency. Results show adaptive lenses operating at optical wavelengths with continuously variable focal lengths from infinity to 70 cm. Switching speeds are of the order of 1 second between focal positions. Manufacturing methods of our adaptive lenses are presented, together with the latest results to the performance of these devices.

Adaptive sequential Monte Carlo approach for real-time applications

This paper presents an adaptive Sequential Monte Carlo approach for real-time applications. Sequential Monte Carlo method is employed to estimate the states of dynamic systems using weighted particles. The proposed approach reduces the run-time computation complexity by adapting the size of the particle set. Multiple processing elements on FPGAs are dynamically allocated for improved energy efficiency without violating real-time constraints. A robot localisation application is developed based on the proposed approach. Compared to a non-adaptive implementation, the dynamic energy consumption is reduced by up to 70% without affecting the quality of solutions. © 2012 IEEE.

Adaptive regulation of vector-controlled induction motors

This paper addresses the speed and flux regulation of induction motors under the assumption that the motor parameters are poorly known. An adaptive passivity-based control is proposed that guarantees robust regulation as well as accurate estimation of the electrical parameters that govern the motor performance. This paper provides a local stability analysis of the adaptive scheme, which is illustrated by simulations and supported by a successful experimental validation on an industrial product. © 2009 IEEE.