A recursive rule base adjustment algorithm for a fuzzy logic controller

This paper introduces a recursive rule base adjustment to enhance the performance of fuzzy logic controllers. Here the fuzzy controller is constructed on the basis of a decision table (DT), relying on membership functions and fuzzy rules that incorporate heuristic knowledge and operator experience. If the controller performance is not satisfactory, it has previously been suggested that the rule base be altered by combined tuning of membership functions and controller scaling factors. The alternative approach proposed here entails alteration of the fuzzy rule base. The recursive rule base adjustment algorithm proposed in this paper has the benefit that it is computationally more efficient for the generation of a DT, and advantage for online realization. Simulation results are presented to support this thesis. (c) 2005 Elsevier B.V. All rights reserved.

Genetic algorithms for local controller network construction

Local Controller Networks (LCNs) provide nonlinear control by interpolating between a set of locally valid, subcontrollers covering the operating range of the plant. Constructing such networks typically requires knowledge of valid local models. This paper describes a new genetic learning approach to the construction of LCNs directly from the dynamic equations of the plant, or from modelling data. The advantage is that a priori knowledge about valid local models is not needed. In addition to allowing simultaneous optimisation of both the controller and validation function parameters, the approach aids transparency by ensuring that each local controller acts independently of the rest at its operating point. It thus is valuable for simultaneous design of the LCNs and identification of the operating regimes of an unknown plant. Application results from a highly nonlinear pH neutralisation process and its associated neural network representation are utilised to illustrate these issues.

Constructing networks of continuous-time velocity-based models

A conventional local model (LM) network consists of a set of affine local models blended together using appropriate weighting functions. Such networks have poor interpretability since the dynamics of the blended network are only weakly related to the underlying local models. In contrast, velocity-based LM networks employ strictly linear local models to provide a transparent framework for nonlinear modelling in which the global dynamics are a simple linear combination of the local model dynamics. A novel approach for constructing continuous-time velocity-based networks from plant data is presented. Key issues including continuous-time parameter estimation, correct realisation of the velocity-based local models and avoidance of the input derivative are all addressed. Application results are reported for the highly nonlinear simulated continuous stirred tank reactor process.

Numerical analysis of bodyworn UHF antenna systems

Bodyworn antennas are found in a wide range of medical, military and personal communication applications, yet reliable communication from the surface of the human body still presents a range of engineering challenges. At UHF and microwave frequencies, bodyworn antennas can suffer from reduced efficiency due to electromagnetic absorption in tissue, radiation pattern fragmentation and variations in feed-point impedance. The significance and nature of these effects are system specific and depend on the operating frequency, propagation environment and physical constraints on the antenna itself. This paper describes how numerical electromagnetic modelling techniques such as FDTD (finite-difference time-domain) can be used in the design of bodyworn antennas. Examples are presented for 418 MHz, 916 .5 MHz and 2 . 45 GHz, in the context of both biomedical signalling and wireless personal-area networking applications such as the Bluetooth(TM)* wireless technology.

Optimisation of trench isolated bipolar transistors on SOI substrates by 3D electro-thermal simulations

This paper provides a comprehensive analysis of thermal resistance of trench isolated bipolar transistors on SOI substrates based on 3D electro-thermal simulations calibrated to experimental data. The impact of emitter length, width, spacing and number of emitter fingers on thermal resistance is analysed in detail. The results are used to design and optimise transistors with minimum thermal resistance and minimum transistor area. (c) 2007 Elsevier Ltd. All rights reserved.

High tolerance to gate misalignment in low voltage gate-underlap double gate MOSFETs

.In this letter, we demonstrate for the first time that gate misalignment is not a critical limiting factor for low voltage operation in gate-underlap double gate (DG) devices. Our results show that underlap architecture significantly extends the tolerable limit of gate misalignment in 25 nm devices. DG MOSFETs with high degree of gate misalignment and optimal gate-underlap design can perform comparably or even better than self-aligned nonunderlap devices. Results show that spacer-to-straggle (s/sigma) ratio, a key design parameter for underlap devices, should be within the range of 2.3-3.0 to accommodate back gate misalignment. These results are very significant as the stringent process control requirements for achieving self-alignment in nanoscale planar DG MOSFETs are considerably relaxed

Scaling issues for analogue circuits using Double Gate SOI transistors

This work presents a systematic analysis on the impact of source-drain engineering using gate

Accurate substrate modelling of RF CMOS

The losses within the substrate of an RF IC can have significant effect on performance in a mixed signal application. in order to model substrate coupling accurately, it is represented by an RC network to account for both resistive and dielectric losses at high frequency (> 1 GHz). A small-signal equivalent circuit model of an RF IC inclusive of substrate parasitic effect is analysed in terms of its y-parameters and an extraction procedure for substrate parameters has been developed. By coupling the extracted substrate parameters along with extrinsic resistances associated with gate, source and drain, a standard BSIM3 model has been extended for RF applications. The new model exhibits a significant improvement in prediction of output reflection coefficient S-22 in the frequency range from 1 to 10 GHz in device mode of operation and for a low noise amplifier (LNA) at 2.4 GHz. Copyright (C) 2006 John Wiley & Sons, Ltd.

Analog performance of double gate SOI transistors

Double gate fully depleted silicon-on-insulator (DGSOI) is recognized as a possible solution when the physical gate length L-G reduces to 25nm for the 65nm node on the ITRS CMOS roadmap. In this paper, scaling guidelines are introduced to optimally design a nanoscale DGSOI. For this reason, the sensitivity of gain, f(T) and f(max) to each of the key geometric and technological parameters of the DGSOI are assessed and quantified using MixedMode simulation. The impact of the parasitic resistance and capacitance on analog device performance is systematically analysed. By comparing analog performance with a single gate (SG), it has been found that intrinsic gain in DGSOI is 4 times higher but its fT was found to be comparable to that of SGSOI at different regions of transistor operation. However, the extracted fmax in SG SOI was higher (similar to 40%) compared to DGSOI due to its lower capacitance.

Preparation of AgX (X = Cl, I) nanoparticles using ionic liquids

Nanoparticles of silver halides have been prepared by mixing silver halide powder with a single liquid phase consisting of an ionic liquid, isooctane, n-decanol and water. Much higher nanoparticle concentrations may be formed with ionic liquids using this new simple method than are found with conventionally applied surfactants. This method also emphasizes the applicability of ionic liquids as versatile components in microemulsions and as solvents for the synthesis of nanomaterials. The effect on the nanoparticles of changing the composition of the liquid mixtures and the nature of the ionic liquid is analysed. High nanoparticle concentrations were only found with chloride based ionic liquids, indicating the importance of the ionic liquid anion in the mechanism of the reaction.

External circuit system effects on chlorine plasma instabilities

The effects of the external circuit on plasma instabilities in all inductive plasma source are investigated. The instabilities are found to be asymmetric with respect to the circuit input impedance. A simplified model of the antenna-plasnia coupling provides an explanation of the asymetry.

Improved fault diagnosis in multivariate systems using regression-based reconstruction

Subspace monitoring has recently been proposed as a condition monitoring tool that requires considerably fewer variables to be analysed compared to dynamic principal component analysis (PCA). This paper analyses subspace monitoring in identifying and isolating fault conditions, which reveals that the existing work suffers from inherent limitations if complex fault senarios arise. Based on the assumption that the fault signature is deterministic while the monitored variables are stochastic, the paper introduces a regression-based reconstruction technique to overcome these limitations. The utility of the proposed fault identification and isolation method is shown using a simulation example and the analysis of experimental data from an industrial reactive distillation unit.

On the Sphere Decoder for Frequency-Selective MIMO channels

This paper compares the complexity of the sphere decoder (SD) and a previously proposed detection scheme, denoted here as block SD (BSD), when they are applied to the detection of multiple-input multiple-output (MIMO) systems in frequency-selective channels. The complexity of both algorithms depends on their preprocessing and tree search stages. Although the BSD was proposed as a means of greatly reducing the complexity of the preprocessing stage of the SD, no study was done on how the complexity of the tree search stage could be affected by that reduced preprocessing stage. This paper shows, both analytically and through simulation, that the reduction in preprocessing complexity provided by the BSD has the side effect of increasing the complexity of its tree search stage compared to that of the SD, independent of the signal-to-noise ratio (SNR). In addition, this paper shows how sorting the columns of the frequency-selective channel matrix in the SD does not reduce the complexity of the tree search stage, contrary to what occurs in frequency-flat channels.