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.

Feedback dew-point sensor utilising optimally cut plastic optical fibres

A plastic optical fibre reflectance sensor that makes full use of the critical angle of the fibres is implemented to monitor dew formation on a Peltier-cooled reflector surface. The optical configuration permits isolation of optoelectronic components from the sensing head and better light coupling between the reflector and the detecting fibre, giving a better signal of the onset of dew formation on the reflector. Continuous monitoring of the rate of change in reflectance as well as the absolute reflectance signals, the use of a novel polymethyl-methacrylate-coated hydrophobic film reflector on the Peltier element and the application of feedback around the point of dew formation, further reduces the possibility of contamination of the sensor head. Under closed-loop operation, the sensor is capable of cycling around the point of dew formation at a frequency of 2.5 Hz.

Automatic optical fibre feedback potometer for transpiration studies

A new automatic feedback potometer for physiological studies of water uptake by root systems is described. A dual-optical-fibre amplitude-modulating displacement transducer of improved sensitivity is employed to detect the changes in liquid level. The merits of optimal double-cut fibres, which make full use of the critical angle and improve coupling between the emitter and the receiver, have resulted in a sensor that is 64 times more responsive than the simple emitter - detector probe. Positioning the optical fibre transducer in a narrow capillary and using feedback to control the liquid level allows continuous measurement of volumes in the nanolitre range. The optical sensor used does not need re-calibration for the different salt solutions used in such studies.

A self-structured adaptive decision feedback equalizer

In a decision feedback equalizer (DFE), the structural parameters, including the decision delay, the feedforward filter (FFF), and feedback filter (FBF) lengths, must be carefully chosen, as they greatly influence the performance. Although the FBF length can be set as the channel memory, there is no closed-form expression for the FFF length and decision delay. In this letter, first we analytically show that the two-dimensional search for the optimum FFF length and decision delay can be simplified to a one-dimensional search and then describe a new adaptive DFE where the optimum structural parameters can be self-adapted.

A robust hybrid feedback active noise cancellation headset

This paper investigates the robustness of a hybrid analog/digital feedback active noise cancellation (ANC) headset system. The digital ANC systems with the filtered-x least-mean-square (FXLMS) algorithm require accurate estimation of the secondary path for the stability and convergence of the algorithm. This demands a great challenge for the ANC headset design because the secondary path may fluctuate dramatically such as when the user adjusts the position of the ear-cup. In this paper, we analytically show that adding an analog feedback loop into the digital ANC systems can effectively reduce the plant fluctuation, thus achieving a more robust system. The method for designing the analog controller is highlighted. A practical hybrid analog/digital feedback ANC headset has been built and used to conduct experiments, and the experimental results show that the hybrid headset system is more robust under large plant fluctuation, and has achieved satisfactory noise cancellation for both narrowband and broadband noises.

Implementation of robust hybrid feedback FxLMS active noise cancellation headset

Instability is a serious problem for acoustic Active Noise Cancellation (ANC) headsets as a result of large errors in estimating the transfer function of the plant. Typically this occurs when, for example, a wearer adjusts the headset. In this paper, the instability problem of adaptive ANC headset is addressed. To ensure stability of the whole system, we propose a hybrid solution consisting of an analog feedback loop parallel to the digital loop, and the role of the analog loop in stabilizing the headset is analyzed theoretically. Finally the methodology of implementing such a hybrid ANC headset is described in detail. The experiments carried out on the headset prototype show that the headset is robust under considerable fluctuations of the plant transfer characteristics, and has very good noise cancellation performance both for narrow-band and wide-band disturbances.

Moving feedback forward: theory to practice

There is substantial research interest in tutor feedback and students’ perception and use of such feedback. This paper considers some of the major issues raised in relation to tutor feedback and student learning. We explore some of the current feedback drivers, most notably the need for feedback to move away from simply a monologue from a tutor to a student to a valuable tutor–student dialogue. In relation to moving feedback forward the notions of self regulation, dialogue and social learning are explored and then considered in relation to how such theory can translate into practice. The paper proposes a framework (GOALS) as a tool through which tutors can move theory into practice with the aim of improving student learning from feedback.

Modeling building semantics: providing feedback and sustainability

Even minor changes in user activity can bring about significant energy savings within built space. Many building performance assessment methods have been developed, however these often disregard the impact of user behavior (i.e. the social, cultural and organizational aspects of the building). Building users currently have limited means of determining how sustainable they are, in context of the specific building structure and/or when compared to other users performing similar activities, it is therefore easy for users to dismiss their energy use. To support sustainability, buildings must be able to monitor energy use, identify areas of potential change in the context of user activity and provide contextually relevant information to facilitate persuasion management. If the building is able to provide users with detailed information about how specific user activity that is wasteful, this should provide considerable motivation to implement positive change. This paper proposes using a dynamic and temporal semantic model, to populate information within a model of persuasion, to manage user change. By semantically mapping a building, and linking this to persuasion management we suggest that: i) building energy use can be monitored and analyzed over time; ii) persuasive management can be facilitated to move user activity towards sustainability.

The role of atmosphere feedbacks during ENSO in the CMIP3 models. Part II: using AMIP runs to understand the heat flux feedback mechanisms

Several studies using ocean–atmosphere general circulation models (GCMs) suggest that the atmospheric component plays a dominant role in the modelled El Niño-Southern Oscillation (ENSO). To help elucidate these findings, the two main atmosphere feedbacks relevant to ENSO, the Bjerknes positive feedback (μ) and the heat flux negative feedback (α), are here analysed in nine AMIP runs of the CMIP3 multimodel dataset. We find that these models generally have improved feedbacks compared to the coupled runs which were analysed in part I of this study. The Bjerknes feedback, μ, is increased in most AMIP runs compared to the coupled run counterparts, and exhibits both positive and negative biases with respect to ERA40. As in the coupled runs, the shortwave and latent heat flux feedbacks are the two dominant components of α in the AMIP runs. We investigate the mechanisms behind these two important feedbacks, in particular focusing on the strong 1997–1998 El Niño. Biases in the shortwave flux feedback, α SW, are the main source of model uncertainty in α. Most models do not successfully represent the negative αSW in the East Pacific, primarily due to an overly strong low-cloud positive feedback in the far eastern Pacific. Biases in the cloud response to dynamical changes dominate the modelled α SW biases, though errors in the large-scale circulation response to sea surface temperature (SST) forcing also play a role. Analysis of the cloud radiative forcing in the East Pacific reveals model biases in low cloud amount and optical thickness which may affect α SW. We further show that the negative latent heat flux feedback, α LH, exhibits less diversity than α SW and is primarily driven by variations in the near-surface specific humidity difference. However, biases in both the near-surface wind speed and humidity response to SST forcing can explain the inter-model αLH differences.