The scope of the thesis is to estimate the parameters of continuous-time models used within control and communication from sampled data with high accuracy and in a computationally efficient way.In the thesis, continuous-time models of systems controlled in a networked environment, errors-in-variables systems, stochastic closed-loop systems, and wireless channels are considered. The parameters of a transfer function based model for the process in a networked control system are estimated by a covariance function based approach relying upon the second order statistical properties of input and output signals. Some other approaches for estimating the parameters of continuous-time models for processes in networked environments are also considered. The multiple input multiple output errors-in-variables problem is solved by means of a covariance matching algorithm. An analysis of a covariance matching method for single input single output errors-in-variables system identification is also presented. The parameters of continuous-time autoregressive exogenous models are estimated from closed-loop filtered data, where the controllers in the closed-loop are of proportional and proportional integral type, and where the closed-loop also contains a time-delay. A stochastic differential equation is derived for Jakes's wireless channel model, describing the dynamics of a scattered electric field with the moving receiver incorporating a Doppler shift. / <p>The thesis consists of five main parts, where the first part is an introduction- Parts II-IV are based on the following articles:</p><p><strong>Part II</strong> - Networked Control Systems</p><p>1. Y. Irshad, M. Mossberg and T. Söderström. <em>System identification in a networkedenvironment using second order statistical properties</em>.</p><p>A versionwithout all appendices is published as Y. Irshad, M. Mossberg and T. Söderström. <em>System identification in a networked environment using second order statistical properties</em>. Automatica, 49(2), pages 652–659, 2013.</p><p>Some preliminary results are also published as M. Mossberg, Y. Irshad and T. Söderström. <em>A covariance function based approachto networked system identification.</em> In Proc. 2nd IFAC Workshop on Distributed Estimation and Control in Networked Systems, pages 127–132, Annecy,France, September 13–14, 2010</p><p>2. Y. Irshad and M. Mossberg. <em>Some parameters estimation methods applied tonetworked control systems</em>.A journal submission is made. Some preliminary results are published as Y. Irshad and M. Mossberg.<em> A comparison of estimation concepts applied to networked control systems</em>. In Proc. 19th Int. Conf. on Systems, Signals andImage Processing, pages 120–123, Vienna, Austria, April 11–13, 2012.</p><p><strong>Part III</strong> - Errors-in-variables Identification</p><p>3. Y. Irshad and M. Mossberg. <em>Continuous-time covariance matching for MIMOEIV system identification</em>. A journal submission is made.</p><p>4. T. Söderström, Y. Irshad, M. Mossberg and W. X. Zheng. <em>On the accuracy of acovariance matching method for continuous-time EIV identification. </em>Provisionally accepted for publication in Automatica.</p><p>Some preliminary results are published as T. Söderström, Y. Irshad, M. Mossberg, and W. X. Zheng. <em>Accuracy analysis of a covariance matching method for continuous-time errors-in-variables system identification</em>. In Proc. 16th IFAC Symp. System Identification, pages 1383–1388, Brussels, Belgium, July 11–13, 2012.</p><p><strong>Part IV</strong> - Wireless Channel Modeling</p><p>5. Y. Irshad and M. Mossberg.<em> Wireless channel modeling based on stochasticdifferential equations .</em>Some results are published as M. Mossberg and Y. Irshad.<em> A stochastic differential equation forwireless channelsbased on Jakes’s model with time-varying phases,</em> In Proc. 13th IEEEDigitalSignal Processing Workshop, pages 602–605, Marco Island, FL, January4–7, 2009.</p><p><strong>Part V</strong> - Closed-loop Identification</p><p>6. Y. Irshad and M. Mossberg. Closed-loop identification of P- and PI-controlledtime-delayed stochastic systems.Some results are published as M. Mossberg and Y. Irshad. <em>Closed-loop identific ation of stochastic models from filtered data</em>, In Proc. IEEE Multi-conference on Systems and Control,San Antonio, TX, September 3–5, 2008</p>

Many important factors affect the spread of childhood infectious disease. To understand better the fundamental drivers of infectious disease spread, several researchers have estimated seasonal transmission coefficients using discrete-time models. This research addresses several shortcomings of the discrete-time approaches, including removing the need for the reporting interval to match the serial interval of the disease using infectious disease data from three major cities: New York City, London, and Bangkok. Using a simultaneous approach for optimization of differential equation systems with a Radau collocation discretization scheme and total variation regularization for the transmission parameter profile, this research demonstrates that seasonal transmission parameters can be effectively estimated using continuous-time models. This research further correlates school holiday schedules with the transmission parameter for New York City and London where previous work has already been done, and demonstrates similar results for a relatively unstudied city in childhood infectious disease research, Bangkok, Thailand.

This dissertation presents design and implementation of continuous time analog filters for two specific applications: wideband analog systems such as disk drive channel and low-power wireless applications. Specific focus has been techniques that reduce the power requirements of the overall system either through improvement in architecture or efficiency of the analog building blocks. The first problem that this dissertation addresses is the implementation of wideband filters with high equalization gain. An efficient architecture that realizes equalization zeros by combining available transfer functions associated with a biquadratic cell is proposed. A 330MHz, 5th order Gm-C lowpass Butterworth filter with 24dB boost is designed using the proposed architecture. The prototype fabricated in standard 0.35um CMOS process shows -41dB of IM3 for 250mV peak to peak swing with 8.6mW/pole of power dissipation. Also, an LC prototype implemented using similar architecture is discussed in brief. It is shown that, for practical range of frequency and SNR, LC based design is more power efficient than a Gm-C one, though at the cost of much larger area. Secondly, a complementary current mirror based building block is proposed, which pushes the limits imposed by conventional transconductors on the powerefficiency of Gm-C filters. Signal processing through complementary devices provides good linearity and Gm/Id efficiency and is shown to improve power efficiency by nearly 7 times. A current-mode 4th order Butterworth filter is designed, in 0.13um UMC technology, using the proposed building. It provides 54.2dB IM3 and 55dB SNR in 1.3GHz bandwidth while consuming as low as 24mW of power. All CMOS filter realization occupies a relatively small area and is well suited for integration in deep submicron technologies. Thirdly, a 20MHz, 68dB dynamic range active RC filter is presented. This filter is designed for a ten bit continuous time sigma delta ADC architecture developed specifically for fine-line CMOS technologies. Inverter based amplification and a common mode feedback for such amplifiers are discussed. The filter consumes 5mW of power and occupies an area of 0.07 mm2.

The most popular and fundamental portfolio optimization problem is Markowitz&#039 / s one period mean-variance portfolio selection problem. However, it is criticized because of its one period static nature. Further, the estimation of the stock price expected return is a particularly hard problem. For this purpose, there are a lot of studies solving the mean-variance portfolio optimization problem in continuous time. To solve the estimation problem of the stock price expected return, in 1992, Black and Litterman proposed the Bayesian asset allocation method in discrete time. Later on, Lindberg has introduced a new way of parameterizing the price dynamics in the standard Black-Scholes and solved the continuous time mean-variance portfolio optimization problem. In this thesis, firstly we take up the Lindberg&#039 / s approach, we generalize the results to a jump-diffusion market setting and we correct the proof of the main result. Further, we demonstrate the implications of the Lindberg parameterization for the stock price drift vector in different market settings, we analyze the dependence of the optimal portfolio from jump and diffusion risk, and we indicate how to use the method. Secondly, we present the Lagrangian function approach of Korn and Trautmann and we derive some new results for this approach, in particular explicit representations for the optimal portfolio process. In addition, we present the L2-projection approach of Schweizer for the continuous time mean-variance portfolio optimization problem and derive the optimal portfolio and the optimal wealth processes for this approach. While, deriving these results as the underlying model, the market parameterization of Lindberg is chosen. Lastly, we compare these three different optimization frameworks in detail and their attractive and not so attractive features are highlighted by numerical examples.

Over the past decade, there has been a growing interest in the devel- opment of integrated circuits (ICs) for wearable or implantable biosensors, aiming at providing personalized healthcare services and reducing the health-care expenses. In biosensor ICs, the analog-to-digital converter (ADC) is a key building block that acts as a bridge between analog signals and digital processors. Since most of the biosensors are attached to or implanted in hu- man bodies and powered by either portable batteries or harvested energy, ultra-low-power operation is often required. The stringent power budget im- poses challenges in designing power-efficient ADCs, especially when targeting high-resolution. Among different ADC architectures, the Sigma-Delta (Σ∆) ADC has emerged as the most suitable for low-power, high-resolution appli- cations. This thesis aims to enhance the power efficiency of continuous-time (CT) incremental Σ∆ (IΣ∆) ADCs by exploring design techniques at both architectural and circuit levels. The impact of feedback DACs in CT IΣ∆ ADCs is investigated, so as to provide power-efficient feedback DAC solutions, suitable for biosensor ap- plications. Different DAC schemes are examined analytically considering the trade-off between timing error sensitivity and power consumption. The an- alytical results are verified through behavioral simulations covering both the conventional and incremental Σ∆ modes. Additionally, by considering a typi- cal biosensor application, different feedback DACs are further compared, aim- ing to offer a reference for selecting a power-efficient DAC scheme. A two-step CT IΣ∆ ADC is proposed, analyzed, implemented and tested, with the objective of offering flexible and power-efficient A/D conversion in neural recording systems. By pipelining two CT IΣ∆ ADCs, the pro- posed ADC can achieve high-resolution without sacrificing the conversion rate. Power-efficient circuits are proposed to implement the active blocks of the proposed ADC. The feasibility and power efficiency of the two-step CT IΣ∆ ADC are validated by measurement results. Furthermore, enhancement techniques from both the architecture and circuit perspectives are discussed and implemented, which are validated by post-layout simulations. A comparative study of several CT IΣ∆ ADC architectures is presented, aiming to boost the power efficiency by reducing the number of cycles per con- version while benefiting from the advantage of CT implementation. Five CT IΣ∆ ADC architectures are analyzed and simulated to evaluate their effective- ness under ideal conditions. Based on the theoretical results, a second-order CT IΣ∆ ADC and an extended-range CT IΣ∆ ADC are selected as implemen- tation case studies together with the proposed two-step CT IΣ∆ ADC. The impact of critical circuit non-idealities is investigated. The three ADCs are then implemented and fabricated on a single chip. Experimental results reveal that the three prototype ADCs improve considerably the power efficiency of existing CT IΣ∆ ADCs while being very competitive when compared to all types of the state-of-the-art IΣ∆ ADCs. / <p>QC 20150422</p>

No description available.

Thesis (Ph. D.)--University of Texas at Austin, 2007. / Vita. Includes bibliographical references.

Autonomous vehicles is soon a reality in the every-day life. Though before it is used commercially the vehicles need to be proven safe. The current standard for functional safety on roads, ISO 26262, does not include autonomous vehicles at the moment, which is why in this project an approach using semi-Markov models is used to assess safety. A semi-Markov process is a stochastic process modelled by a state space model where the transitions between the states of the model can be arbitrarily distributed. The approach is realized as a MATLAB tool where the user can use a steady-state based analysis called a Loss and Risk based measure of safety to assess safety. The tool works and can assess safety of semi-Markov systems as long as they are irreducible and positive recurrent. For systems that fulfill these properties, it is possible to draw conclusions about the safety of the system through a risk analysis and also about which autonomous driving level the system is in through a sensitivity analysis. The developed tool, or the approach with the semi-Markov model, might be a good complement to ISO 26262.

Made available in DSpace on 2014-06-11T19:22:31Z (GMT). No. of bitstreams: 0 Previous issue date: 2009-02-20Bitstream added on 2014-06-13T18:49:28Z : No. of bitstreams: 1 silva_erp_me_ilha.pdf: 509609 bytes, checksum: 37c083ec485dbc3db2cf95730b404b40 (MD5) / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) / Uma técnica de projeto de controladores robustos para sistemas não-lineares contínuos no tempo é proposta neste trabalho. É suposto que a planta não-linear está sujeita a falhas estruturais, que podem ser consideradas como incertezas politópicas. Os sistemas não-lineares são representados por modelos fuzzy propostos por Takagi-Sugeno e uma formulação para o tratamento das incertezas politópicas é apresentado para o projeto dos controladores. Este trabalho aborda projetos de controle usando a realimentação dos estados e a realimentação da derivada dos estados. O projeto do controlador é realizado através de condições baseadas em Desigualdades Matriciais Lineares (em inglês, Linear Matrix Inequalities (LMI)), que podem ser resolvidas facilmente utilizando técnicas de programação convexa. Essa metodologia permite a inclusão de restrições de desempenho no projeto, tais como: taxa de decaimento e restrição na entrada. Ao final, exemplos numéricos e suas simulações ilustram a eficiência da técnica proposta. / A technique of robust controllers design for nonlinear continuous-time systems is proposed in this work. It is supposed that the nonlinear plant is subject to structural failures, which can be considered as polytope uncertainties. The nonlinear systems are represented through fuzzy models proposed by Takagi-Sugeno and a formulation for the treatment of polytope uncertain is presented for the controllers design. This work focuses control designs using state feedback and state-derivative feedback. The controllers design is made through conditions based in Linear Matrix Inequalities (LMIs), which can be easily solved using convex programming techniques. This methodology allows the inclusion of performance restrictions on design, such as: decay rate and input constraint. Finally, numeric examples and their simulations show the efficiency of the proposed method.

Submitted by Moisés Rodrigues Cirilo do Monte (moisesrcm@hotmail.com) on 2018-03-16T22:02:40Z No. of bitstreams: 1 Tese_Moises.pdf: 754268 bytes, checksum: e5d5247fc1d88dad53af04230ccf74dd (MD5) / Approved for entry into archive by Elza Mitiko Sato null (elzasato@ibilce.unesp.br) on 2018-03-20T17:08:48Z (GMT) No. of bitstreams: 1 monte_mrc_dr_sjrp.pdf: 754268 bytes, checksum: e5d5247fc1d88dad53af04230ccf74dd (MD5) / Made available in DSpace on 2018-03-20T17:08:48Z (GMT). No. of bitstreams: 1 monte_mrc_dr_sjrp.pdf: 754268 bytes, checksum: e5d5247fc1d88dad53af04230ccf74dd (MD5) Previous issue date: 2018-03-09 / O problema de otimização com tempo contínuo consiste em maximizar um funcional integral, sujeito a restrições de igualdade e desigualdade, onde as funções envolvidas pertencem a um espaço de Banach e variam num certo intervalo de tempo. Os resultados obtidos fornecem condições necessárias para que uma determinada função seja solução do problema. Qualificações de restrições são estabelecidas a m de se obter tais condições necessárias de otimalidade. Para problemas com restrições de desigualdade apenas, faz-se uso de um teorema de alternativa generalizado para se obter condições tipo Karush-Kuhn-Tucker. Para tratar problemas com restrições de igualdade e desigualdade, teoremas da função implícita uniforme e da aplicação inversa uniforme são necessários. / The continuous-time nonlinear programming problem consists in maximizing an integral functional, subject to equality and inequality constraints, where the involved functions belong to a Banach Space and vary over a certain period of time. The obtained results provide the necessary conditions for a given function to solve the problem. Constraints quali cation are established in order to achieve such necessary optimality conditions. For problems with inequality constraints only, a generalized alternative theorem is used to obtain Karush-Kuhn-Tucker-type conditions. To address problems with equality and inequality constraints, uniform implicit function and uniform inverse mapping theorems are necessary.