Kernel-based local order estimation of nonlinear nonparametric systems

We consider the local order estimation of nonlinear autoregressive systems with exogenous inputs (NARX), which may have different local dimensions at different points. By minimizing the kernel-based local information criterion introduced in this paper, the strongly consistent estimates for the local orders of the NARX system at points of interest are obtained. The modification of the criterion and a simple procedure of searching the minimum of the criterion, are also discussed. The theoretical results derived here are tested by simulation examples.

Out-of-equilibrium thermodynamics of quantum optomechanical systems

We address the out-of-equilibrium thermodynamics of an isolated quantum system consisting of a cavity optomechanical device. We explore the dynamical response of the system when driven out of equilibrium by a sudden quench of the coupling parameter and compute analytically the full distribution of the work generated by the process. We consider linear and quadratic optomechanical coupling, where the cavity field is parametrically coupled to either the position or the square of the position of a mechanical oscillator, respectively. In the former case we find that the average work generated by the quench is zero, whilst the latter leads to a non-zero average value. Through fluctuations theorems we access the most relevant thermodynamical figures of merit, such as the free energy difference and the amount of irreversible work generated. We thus provide a full charac- terization of the out-of-equilibrium thermodynamics in the quantum regime for nonlinearly coupled bosonic modes. Our study is the first due step towards the construction and full quantum analysis of an optomechanical machine working fully out of equilibrium.

Computational scheduling methods for integrating plug-in electric vehicles with power systems: a review

Traditional internal combustion engine vehicles are a major contributor to global greenhouse gas emissions and other air pollutants, such as particulate matter and nitrogen oxides. If the tail pipe point emissions could be managed centrally without reducing the commercial and personal user functionalities, then one of the most attractive solutions for achieving a significant reduction of emissions in the transport sector would be the mass deployment of electric vehicles. Though electric vehicle sales are still hindered by battery performance, cost and a few other technological bottlenecks, focused commercialisation and support from government policies are encouraging large scale electric vehicle adoptions. The mass proliferation of plug-in electric vehicles is likely to bring a significant additional electric load onto the grid creating a highly complex operational problem for power system operators. Electric vehicle batteries also have the ability to act as energy storage points on the distribution system. This double charge and storage impact of many uncontrollable small kW loads, as consumers will want maximum flexibility, on a distribution system which was originally not designed for such operations has the potential to be detrimental to grid balancing. Intelligent scheduling methods if established correctly could smoothly integrate electric vehicles onto the grid. Intelligent scheduling methods will help to avoid cycling of large combustion plants, using expensive fossil fuel peaking plant, match renewable generation to electric vehicle charging and not overload the distribution system causing a reduction in power quality. In this paper, a state-of-the-art review of scheduling methods to integrate plug-in electric vehicles are reviewed, examined and categorised based on their computational techniques. Thus, in addition to various existing approaches covering analytical scheduling, conventional optimisation methods (e.g. linear, non-linear mixed integer programming and dynamic programming), and game theory, meta-heuristic algorithms including genetic algorithm and particle swarm optimisation, are all comprehensively surveyed, offering a systematic reference for grid scheduling considering intelligent electric vehicle integration.

Linear-to-Circular Polarization Reflector With Transmission Band

A new class of polarizing surface is proposed that in a given frequency band can reflect incident linearly polarized waves with circular polarization (CP) while at other frequencies is transparent allowing incident waves to transmit unaffected. The proposed structure consists of two parallel anisotropic frequency selective surfaces (FSSs) that independently interact with TE or TM waves, respectively. The FSSs are designed to, respectively, transmit TE and TM waves within the same transmission frequency range, so that the combined structure is transparent to all polarizations in this band. Likewise, the two arrays are designed to, respectively, reflect TE and TM incident waves in a common reflection band, so that all polarizations are fully reflected in this range; if the separation of the two arrays is such that the TE and TM components of an incident wave polarized at slant 45° experience a 90° phase shift, reflection will occur in CP. The concept and performance limitations are theoretically investigated using transmission line theory as well as full wave results. The predicted performance is validated by means of experimental results on a fabricated prototype. The proposed structure is pertinent for employment as a quasi-optical diplexer in CP dual-band systems such as reflector antennas.

Synchrophasor-Based Islanding Detection for Distributed Generation Systems Using Systematic Principal Component Analysis Approaches

Systematic principal component analysis (PCA) methods are presented in this paper for reliable islanding detection for power systems with significant penetration of distributed generations (DGs), where synchrophasors recorded by Phasor Measurement Units (PMUs) are used for system monitoring. Existing islanding detection methods such as Rate-of-change-of frequency (ROCOF) and Vector Shift are fast for processing local information, however with the growth in installed capacity of DGs, they suffer from several drawbacks. Incumbent genset islanding detection cannot distinguish a system wide disturbance from an islanding event, leading to mal-operation. The problem is even more significant when the grid does not have sufficient inertia to limit frequency divergences in the system fault/stress due to the high penetration of DGs. To tackle such problems, this paper introduces PCA methods for islanding detection. Simple control chart is established for intuitive visualization of the transients. A Recursive PCA (RPCA) scheme is proposed as a reliable extension of the PCA method to reduce the false alarms for time-varying process. To further reduce the computational burden, the approximate linear dependence condition (ALDC) errors are calculated to update the associated PCA model. The proposed PCA and RPCA methods are verified by detecting abnormal transients occurring in the UK utility network.

Identification and output tracking control of Hammerstein systems through wireless networks

his paper investigates the identification and output tracking control of a class of Hammerstein systems through a wireless network within an integrated framework and the statistic characteristics of the wireless network are modelled using the inverse Gaussian cumulative distribution function. In the proposed framework, a new networked identification algorithm is proposed to compensate for the influence of the wireless network delays so as to acquire the more precise Hammerstein system model. Then, the identified model together with the model-based approach is used to design an output tracking controller. Mean square stability conditions are given using linear matrix inequalities (LMIs) and the optimal controller gains can be obtained by solving the corresponding optimization problem expressed using LMIs. Illustrative numerical simulation examples are given to demonstrate the effectiveness of our proposed method.

Impact of Residual Transmit RF Impairments on Training-Based MIMO Systems

Radio-frequency (RF) impairments, which intimately exist in wireless communication systems, can severely limit the performance of multiple-input-multiple-output (MIMO) systems. Although we can resort to compensation schemes to mitigate some of these impairments, a certain amount of residual impairments always persists. In this paper, we consider a training-based point-to-point MIMO system with residual transmit RF impairments (RTRI) using spatial multiplexing transmission. Specifically, we derive a new linear channel estimator for the proposed model, and show that RTRI create an estimation error floor in the high signal-to-noise ratio (SNR) regime. Moreover, we derive closed-form expressions for the signal-to-noise-plus-interference ratio (SINR) distributions, along with analytical expressions for the ergodic achievable rates of zero-forcing, maximum ratio combining, and minimum mean-squared error receivers, respectively. In addition, we optimize the ergodic achievable rates with respect to the training sequence length and demonstrate that finite dimensional systems with RTRI generally require more training at high SNRs than those with ideal hardware. Finally, we extend our analysis to large-scale MIMO configurations, and derive deterministic equivalents of the ergodic achievable rates. It is shown that, by deploying large receive antenna arrays, the extra training requirements due to RTRI can be eliminated. In fact, with a sufficiently large number of receive antennas, systems with RTRI may even need less training than systems with ideal hardware.

Can Leakage Models Be More Efficient? Non-Linear Models in Side Channel Attacks

In the last decade, many side channel attacks have been published in academic literature detailing how to efficiently extract secret keys by mounting various attacks, such as differential or correlation power analysis, on cryptosystems. Among the most efficient and widely utilized leakage models involved in these attacks are the Hamming weight and distance models which give a simple, yet effective, approximation of the power consumption for many real-world systems. These leakage models reflect the number of bits switching, which is assumed proportional to the power consumption. However, the actual power consumption changing in the circuits is unlikely to be directly of that form. We, therefore, propose a non-linear leakage model by mapping the existing leakage model via a transform function, by which the changing power consumption is depicted more precisely, hence the attack efficiency can be improved considerably. This has the advantage of utilising a non-linear power model while retaining the simplicity of the Hamming weight or distance models. A modified attack architecture is then suggested to yield the correct key efficiently in practice. Finally, an empirical comparison of the attack results is presented.

Generation of cluster states in optomechanical quantum systems

We consider an optomechanical quantum system composed of a single cavity mode interacting with N mechanical resonators. We propose a scheme for generating continuous-variable graph states of arbitrary size and shape, including the so-called cluster states for universal quantum computation. The main feature of this scheme is that, differently from previous approaches, the graph states are hosted in the mechanical degrees of freedom rather than in the radiative ones. Specifically, via a 2N-tone drive, we engineer a linear Hamiltonian which is instrumental to dissipatively drive the system to the desired target state. The robustness of this scheme is assessed against finite interaction times and mechanical noise, confirming it as a valuable approach towards quantum state engineering for continuous-variable computation in a solid-state platform.

Control of uncertain compartmental systems

Os sistemas compartimentais são frequentemente usados na modelação de diversos processos em várias áreas, tais como a biomedicina, ecologia, farmacocinética, entre outras. Na maioria das aplicações práticas, nomeadamente, aquelas que dizem respeito à administração de drogas a pacientes sujeitos a cirurgia, por exemplo, a presença de incertezas nos parâmetros do sistema ou no estado do sistema é muito comum. Ao longo dos últimos anos, a análise de sistemas compartimentais tem sido bastante desenvolvida na literatura. No entanto, a análise da sensibilidade da estabilidade destes sistemas na presença de incertezas tem recebido muito menos atenção. Nesta tese, consideramos uma lei de controlo por realimentação do estado com restrições de positividade e analisamos a sua robustez quando aplicada a sistemas compartimentais lineares e invariantes no tempo com incertezas nos parâmetros. Além disso, para sistemas lineares e invariantes no tempo com estado inicial desconhecido, combinamos esta lei de controlo com um observador do estado e a robustez da lei de controlo resultante também é analisada. O controlo do bloqueio neuromuscular por meio da infusão contínua de um relaxante muscular pode ser modelado como um sistema compartimental de três compartimentos e tem sido objecto de estudo por diversos grupos de investigação. Nesta tese, os nossos resultados são aplicados a este problema de controlo e são fornecidas estratégias para melhorar os resultados obtidos.

All-optical processing systems based on semiconductor optical amplifiers

Nesta tese investigam-se e desenvolvem-se dispositivos para processamento integralmente óptico em redes com multiplexagem densa por divisão no comprimento de onda (DWDM). O principal objectivo das redes DWDM é transportar e distribuir um espectro óptico densamente multiplexado com sinais de débito binário ultra elevado, ao longo de centenas ou milhares de quilómetros de fibra óptica. Estes sinais devem ser transportados e encaminhados no domínio óptico de forma transparente, sem conversões óptico-eléctrico-ópticas (OEO), evitando as suas limitações e custos. A tecnologia baseada em amplificadores ópticos de semicondutor (SOA) é promissora graças aos seus efeitos não-lineares ultra-rápidos e eficientes, ao potencial para integração, reduzido consumo de potência e custos. Conversores de comprimento de onda são o elemento óptico básico para aumentar a capacidade da rede e evitar o bloqueio de comprimentos de onda. Neste trabalho, são estudados e analisados experimentalmente métodos para aumentar a largura de banda operacional de conversores de modulação cruzada de ganho (XGM), a fim de permitir a operação do SOA para além das suas limitações físicas. Conversão de um comprimento de onda, e conversão simultânea de múltiplos comprimentos de onda são testadas, usando interferómetros de Mach-Zehnder com SOA. As redes DWDM de alto débito binário requerem formatos de modulação optimizados, com elevada tolerância aos efeitos nefastos da fibra, e reduzida ocupação espectral. Para esse efeito, é vital desenvolver conversores integramente ópticos de formatos de modulação, a fim de permitir a interligação entre as redes já instaladas, que operam com modulação de intensidade, e as redes modernas, que utilizam formatos de modulação avançados. No âmbito deste trabalho é proposto um conversor integralmente óptico de formato entre modulação óptica de banda lateral dupla e modulação óptica de banda lateral residual; este é caracterizado através de simulação e experimentalmente. Adicionalmente, é proposto um conversor para formato de portadora suprimida, através de XGM e modulação cruzada de fase. A interligação entre as redes de transporte com débito binário ultra-elevado e as redes de acesso com débito binário reduzido requer conversão óptica de formato de impulso entre retorno-a-zero (RZ) e não-RZ. São aqui propostas e investigadas duas estruturas distintas: uma baseada em filtragem desalinhada do sinal convertido por XGM; uma segunda utiliza as dinâmicas do laser interno de um SOA com ganho limitado (GC-SOA). Regeneração integralmente óptica é essencial para reduzir os custos das redes. Dois esquemas distintos são utilizados para regeneração: uma estrutura baseada em MZI-SOA, e um método no qual o laser interno de um GC-SOA é modulado com o sinal distorcido a regenerar. A maioria dos esquemas referidos é testada experimentalmente a 40 Gb/s, com potencial para aplicação a débitos binários superiores, demonstrado que os SOA são uma tecnologia basilar para as redes ópticas do futuro.

Interference cancellation for distributed wireless systems

O tema principal desta tese é o problema de cancelamento de interferência para sistemas multi-utilizador, com antenas distribuídas. Como tal, ao iniciar, uma visão geral das principais propriedades de um sistema de antenas distribuídas é apresentada. Esta descrição inclui o estudo analítico do impacto da ligação, dos utilizadores do sistema, a mais antenas distribuídas. Durante essa análise é demonstrado que a propriedade mais importante do sistema para obtenção do ganho máximo, através da ligação de mais antenas de transmissão, é a simetria espacial e que os utilizadores nas fronteiras das células são os mais bene ciados. Tais resultados são comprovados através de simulação. O problema de cancelamento de interferência multi-utilizador é considerado tanto para o caso unidimensional (i.e. sem codi cação) como para o multidimensional (i.e. com codi cação). Para o caso unidimensional um algoritmo de pré-codi cação não-linear é proposto e avaliado, tendo como objectivo a minimização da taxa de erro de bit. Tanto o caso de portadora única como o de multipla-portadora são abordados, bem como o cenário de antenas colocadas e distribuidas. É demonstrado que o esquema proposto pode ser visto como uma extensão do bem conhecido esquema de zeros forçados, cuja desempenho é provado ser um limite inferior para o esquema generalizado. O algoritmo é avaliado, para diferentes cenários, através de simulação, a qual indica desempenho perto do óptimo, com baixa complexidade. Para o caso multi-dimensional um esquema para efectuar "dirty paper coding" binário, tendo como base códigos de dupla camada é proposto. No desenvolvimento deste esquema, a compressão com perdas de informação, é considerada como um subproblema. Resultados de simulação indicam transmissão dedigna proxima do limite de Shannon.

Optimal alarms systems and its application to financial time series

This thesis focuses on the application of optimal alarm systems to non linear time series models. The most common classes of models in the analysis of real-valued and integer-valued time series are described. The construction of optimal alarm systems is covered and its applications explored. Considering models with conditional heteroscedasticity, particular attention is given to the Fractionally Integrated Asymmetric Power ARCH, FIAPARCH(p; d; q) model and an optimal alarm system is implemented, following both classical and Bayesian methodologies. Taking into consideration the particular characteristics of the APARCH(p; q) representation for financial time series, the introduction of a possible counterpart for modelling time series of counts is proposed: the INteger-valued Asymmetric Power ARCH, INAPARCH(p; q). The probabilistic properties of the INAPARCH(1; 1) model are comprehensively studied, the conditional maximum likelihood (ML) estimation method is applied and the asymptotic properties of the conditional ML estimator are obtained. The final part of the work consists on the implementation of an optimal alarm system to the INAPARCH(1; 1) model. An application is presented to real data series.

Completely supervised training algorithms for B-spline neural networks and neuro-fuzzy systems

Complete supervised training algorithms for B-spline neural networks and fuzzy rule-based systems are discussed. By interducing the relationship between B-spline neural networks and certain types of fuzzy models, training algorithms developed initially for neural networks can be adapted by fuzzy systems.

A scalable and open source linear positioning system controller

This paper is on the implementation of a dual axis positioning system controller. The system was designed to be used for space-dependent ultrasound signal acquisition problems, such as pressure field mapping. The work developed can be grouped in two main subjects: hardware and software. Each axis includes one stepper motor connected to a driver circuit, which is then connected to a processing unit. The graphical user interface is simple and clear for the user. The system resolution was computed as 127 mu m with an accuracy of 2.44 mu m. Although the target application is ultrasound signal acquisition, the controller can be applied to other devices that has up to four stepper motors. The application was developed as an open source software, thus it can be used or changed to fit different purposes.