The system identification and control of Hammerstein system using non-uniform rational B-spline neural network and particle swarm optimization

In this paper a new system identification algorithm is introduced for Hammerstein systems based on observational input/output data. The nonlinear static function in the Hammerstein system is modelled using a non-uniform rational B-spline (NURB) neural network. The proposed system identification algorithm for this NURB network based Hammerstein system consists of two successive stages. First the shaping parameters in NURB network are estimated using a particle swarm optimization (PSO) procedure. Then the remaining parameters are estimated by the method of the singular value decomposition (SVD). Numerical examples including a model based controller are utilized to demonstrate the efficacy of the proposed approach. The controller consists of computing the inverse of the nonlinear static function approximated by NURB network, followed by a linear pole assignment controller.

Influencing energy efficient occupant behavior through improved building and control design

There is growing pressure on the construction industry to deliver energy efficient, sustainable buildings but there is evidence to suggest that, in practice, designs regularly fail to achieve the anticipated levels of in-use energy consumption. One of the key factors behind this discrepancy is the behavior of the building occupants. This paper explores how insights from experimental psychology could potentially be used to reduce the gap between the predicted and actual energy performance of buildings. It demonstrates why traditional methods to engage with the occupants are not always successful and proposes a model for a more holistic approach to this issue. The paper concludes that achieving energy efficiency in buildings is not solely a technological issue and that the construction industry needs to adopt a more user-centred approach.

Contested institutions? Traditional leaders and land access and control in communal areas of Eastern Cape Province, South Africa

The South African government has endeavoured to strengthen property rights in communal areas and develop civil society institutions for community-led development and natural resource management. However, the effectiveness of this remains unclear as the emergence and operation of civil society institutions in these areas is potentially constrained by the persistence of traditional authorities. Focusing on the former Transkei region of Eastern Cape Province, three case study communities are used examine the extent to which local institutions overlap in issues of land access and control. Within these communities, traditional leaders (chiefs and headmen) continue to exercise complete and sole authority over land allocation and use this to entrench their own positions. However, in the absence of effective state support, traditional authorities have only limited power over how land is used and in enforcing land rights, particularly over communal resources such as rangeland. This diminishes their local legitimacy and encourages some groups to contest their authority by cutting fences, ignoring collective grazing decisions and refusing to pay ‘fees’ levied on them. They are encouraged in such activities by the presence of democratically elected local civil society institutions such as ward councillors and farmers’ organisations, which have broad appeal and are increasingly responsible for much of the agrarian development that takes place, despite having no direct mandate over land. Where it occurs at all, interaction between these different institutions is generally restricted to approval being required from traditional leaders for land allocated to development projects. On this basis it is argued that a more radical approach to land reform in communal areas is required, which transfers all powers over land to elected and accountable local institutions and integrates land allocation, land management and agrarian development more effectively.

Power and control: managing agents for international student recruitment in higher education

This multiple case-based study investigates the relationship between recruiting agents and the UK universities who act as their principals. The current extensive use of agents in UK higher education may be seen as an indicator of the financial impact made by international students. The study analyses the practice of agent management and explores the manner in which power and control interact. The study employed semi-structured interviews and group discussions involving up to 6 respondents from each of the 20 UK case institutions. The qualitative data reveal a considerable variation in the manner in which the universities manage their agency relationships. Through the joint consideration of control measures and use of power, five distinctive approaches have been identified. The study also reveals that over-dependence on agents reduces the power of the principal, and consequently, the principal’s ability to exercise control, particularly in highly competitive global and national markets.

Arthur’s refusal to eat: ritual and control in the romance feast

Arthur's refusal to begin feasting before he has seen a marvel or heard a tale of adventure is a recurring motif in medieval romance. Previous comment on this ritual has suggested that the source for such a taboo on eating may be found in earlier narratives in the Celtic languages. This paper argues that, although the ritual almost certainly originates in pre-chivalric society, romance authors adapted and developed it to reflect the courtly-chivalric preoccupations of their own world. Arthur's ritual gesture may be seen as a means of containing and controlling both interior moral threats and exterior physical peril, and is intimately connected to the courtly conception of the feast. This study draws on the evidence of religious writing and courtesy manuals and explores some highly-developed treatments of the motif in romance in order to suggest that literary engagements with Arthur's refusal to eat have much to say about contemporary ideas of ritual and reality as mediated through the symbolically-charged arena of the medieval feast.

Mapping and controlling molecular processes: The application of control theory and system identification algorithms to ASOPS and other fast pulse spectroscopies

Asynchronous Optical Sampling (ASOPS) [1,2] and frequency comb spectrometry [3] based on dual Ti:saphire resonators operated in a master/slave mode have the potential to improve signal to noise ratio in THz transient and IR sperctrometry. The multimode Brownian oscillator time-domain response function described by state-space models is a mathematically robust framework that can be used to describe the dispersive phenomena governed by Lorentzian, Debye and Drude responses. In addition, the optical properties of an arbitrary medium can be expressed as a linear combination of simple multimode Brownian oscillator functions. The suitability of a range of signal processing schemes adopted from the Systems Identification and Control Theory community for further processing the recorded THz transients in the time or frequency domain will be outlined [4,5]. Since a femtosecond duration pulse is capable of persistent excitation of the medium within which it propagates, such approach is perfectly justifiable. Several de-noising routines based on system identification will be shown. Furthermore, specifically developed apodization structures will be discussed. These are necessary because due to dispersion issues, the time-domain background and sample interferograms are non-symmetrical [6-8]. These procedures can lead to a more precise estimation of the complex insertion loss function. The algorithms are applicable to femtosecond spectroscopies across the EM spectrum. Finally, a methodology for femtosecond pulse shaping using genetic algorithms aiming to map and control molecular relaxation processes will be mentioned.

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.