Controllable forms for stabilising pole assignment design of generalised bilinear systems

Bilinear structures are able to represent nonlinear phenomena more accurately than linear models, and thereby help to extend the range of satisfactory control performance. However, closed loop characteristics are typically designed by simulation and stability is not guaranteed. In this reported work, it is shown how bilinear systems are a special case of the more general state dependent parameter (SDP) model, which can subsequently be utilised to design stabilising feedback controllers using a special form of nonlinear pole assignment. To establish the link, however, an important generalisation of the SDP pole assignment method is developed

Preliminaries of orthogonal layered defence using functional and assurance controls in industrial control systems

Industrial Control Systems (ICSs) are responsible for the automation of different processes and the overall control of systems that include highly sensitive potential targets such as nuclear facilities, energy-distribution, water-supply, and mass-transit systems. Given the increased complexity and rapid evolvement of their threat landscape, and the fact that these systems form part of the Critical National infrastructure (CNI), makes them an emerging domain of conflict, terrorist attacks, and a playground for cyberexploitation. Existing layered-defence approaches are increasingly criticised for their inability to adequately protect against resourceful and persistent adversaries. It is therefore essential that emerging techniques, such as orthogonality, be combined with existing security strategies to leverage defence advantages against adaptive and often asymmetrical attack vectors. The concept of orthogonality is relatively new and unexplored in an ICS environment and consists of having assurance control as well as functional control at each layer. Our work seeks to partially articulate a framework where multiple functional and assurance controls are introduced at each layer of ICS architectural design to further enhance security while maintaining critical real-time transfer of command and control traffic

The Impact of Thermal Degradation on Properties of Electrical Machine Winding Insulation Material

Inter-turn stator short circuits can develop quickly leading to serious damage of an electric machine. However, degradation mechanisms of winding insulation material are not yet fully understood. Therefore, the main contribution of this article is analysis of the impact of thermal ageing on the electrical properties of the thin film winding insulation. The insulation samples have been aged thermally at 200–275 °C and for 100–1600 hours. After ageing, impedance spectroscopy measurements were undertaken on the samples and equivalent circuit model (ECM) parameters fitted for each measurement. This allows the impact of thermal ageing on ECM parameters to be analysed, giving insight into the changes of the electrical properties of the insulation. Finally, high voltage was applied to the samples aiming to identify the breakdown voltage characteristics of the insulation material

Parameter estimation of the fractional-order Hammerstein–Wiener model using simplified refined instrumental variable fractional-order continuous time

© 2017 The Authors. Published by IET. This is an open access article available under a Creative Commons licence. The published version can be accessed at the following link on the publisher’s website: https://doi.org/10.1049/iet-cta.2017.0284This study proposes a direct parameter estimation approach from observed input–output data of a stochastic single-input–single-output fractional-order continuous-time Hammerstein–Wiener model by extending a well known iterative simplified refined instrumental variable method. The method is an extension of the simplified refined instrumental variable method developed for the linear fractional-order continuous-time system, denoted. The advantage of this novel extension, compared with published methods, is that the static output non-linearity of the Wiener model part does not need to be invertible. The input and output static non-linear functions are represented by a sum of the known basis functions. The proposed approach estimates the parameters of the linear fractional-order continuous-time subsystem and the input and output static non-linear functions from the sampled input–output data by considering the system to be a multi-input–single-output linear fractional-order continuous-time model. These extra inputs represent the basis functions of the static input and output non-linearity, where the output basis functions are simulated according to the previous estimates of the fractional-order linear subsystem and the static input non-linear function at every iteration. It is also possible to estimate the classical integer-order model counterparts as a special case. Subsequently, the proposed extension to the simplified refined instrumental variable method is considered in the classical integer-order continuous-time Hammerstein–Wiener case. In this paper, a Monte Carlo simulation analysis is applied for demonstrating the performance of the proposed approach to estimate the parameters of a fractional-order Hammerstein–Wiener output model