Design of discrete time controllers and estimators.

This thesis considers optimal linear least-squares filtering smoothing prediction and regulation for discrete-time processes. A finite interval smoothing filter is derived in the z domain giving a transfer function solution. The resulting time-invariant smoother can be applied to problems where, a time varying solution using matrix Riccati equations would diverge if the process is modelled inaccurately. A self-tuning algorithm is given for the filtering and fixed lag smoothing problems as applied to square multi-variable ARMA processes when only the order of the process is assumed known. The dynamics of the process can also be slowly time varying. If the dynamics remain constant and unknown, it is shown how the self-tuning filter or smoother algorithm converges asymptotically to the optimal Wiener solutions. LQG self-tuning regulation is considered. The LQG algorithms rely on input-output data rather than from the conventional state-space approach employing the Kalman filter. An explicit algorithm is given which is similar to certain pole placement self-tuning regulators, requiring the solution of a diophantine equation. Following this, an implicit algorithm is shown to overcome the problem of solving a diophantine equation by estimating the regulator parameters directly using recursive least squares. The LQG algorithms are shown to be able to cope with processes which are non-minimum phase, open loop unstable and with an unknown time delay

Multi-Loop-Ring-Oscillator Design and Analysis for Sub-Micron CMOS

Ring oscillators provide a central role in timing circuits for today?s mobile devices and desktop computers. Increased integration in these devices exacerbates switching noise on the supply, necessitating improved supply resilience. Furthermore, reduced voltage headroom in submicron technologies limits the number of stacked transistors available in a delay cell. Hence, conventional single-loop oscillators offer relatively few design options to achieve desired specifications, such as supply rejection. Existing state-of-the-art supply-rejection- enhancement methods include actively regulating the supply with an LDO, employing a fully differential or current-starved delay cell, using a hi-Z voltage-to-current converter, or compensating/calibrating the delay cell. Multiloop ring oscillators (MROs) offer an additional solution because by employing a more complex ring-connection structure and associated delay cell, the designer obtains an additional degree of freedom to meet the desired specifications. Designing these more complex multiloop structures to start reliably and achieve the desired performance requires a systematic analysis procedure, which we attack on two fronts: (1) a generalized delay-cell viewpoint of the MRO structure to assist in both analysis and circuit layout, and (2) a survey of phase-noise analysis to provide a bank of methods to analyze MRO phase noise. We distill the salient phase-noise-analysis concepts/key equations previously developed to facilitate MRO and other non-conventional oscillator analysis. Furthermore, our proposed analysis framework demonstrates that all these methods boil down to obtaining three things: (1) noise modulation function (NMF), (2) noise transfer function (NTF), and (3) current-controlled-oscillator gain (KICO). As a case study, we detail the design, analysis, and measurement of a proposed multiloop ring oscillator structure that provides improved power-supply isolation (more than 20dB increase in supply rejection over a conventional-oscillator control case fabricated on the same test chip). Applying our general multi-loop-oscillator framework to this proposed MRO circuit leads both to design-oriented expressions for the oscillation frequency and supply rejection as well as to an efficient layout technique facilitating cross-coupling for improved quadrature accuracy and systematic, substantially simplified layout effort

Song Practice Promotes Acute Vocal Variability at a Key Stage of Sensorimotor Learning

BACKGROUND: Trial by trial variability during motor learning is a feature encoded by the basal ganglia of both humans and songbirds, and is important for reinforcement of optimal motor patterns, including those that produce speech and birdsong. Given the many parallels between these behaviors, songbirds provide a useful model to investigate neural mechanisms underlying vocal learning. In juvenile and adult male zebra finches, endogenous levels of FoxP2, a molecule critical for language, decrease two hours after morning song onset within area X, part of the basal ganglia-forebrain pathway dedicated to song. In juveniles, experimental 'knockdown' of area X FoxP2 results in abnormally variable song in adulthood. These findings motivated our hypothesis that low FoxP2 levels increase vocal variability, enabling vocal motor exploration in normal birds. METHODOLOGY/PRINCIPAL FINDINGS: After two hours in either singing or non-singing conditions (previously shown to produce differential area X FoxP2 levels), phonological and sequential features of the subsequent songs were compared across conditions in the same bird. In line with our prediction, analysis of songs sung by 75 day (75d) birds revealed that syllable structure was more variable and sequence stereotypy was reduced following two hours of continuous practice compared to these features following two hours of non-singing. Similar trends in song were observed in these birds at 65d, despite higher overall within-condition variability at this age. CONCLUSIONS/SIGNIFICANCE: Together with previous work, these findings point to the importance of behaviorally-driven acute periods during song learning that allow for both refinement and reinforcement of motor patterns. Future work is aimed at testing the observation that not only does vocal practice influence expression of molecular networks, but that these networks then influence subsequent variability in these skills

System identification and adaptive current balancing ON/OFF control of DC-DC switch mode power converter

PhD ThesisReliability becomes more and more important in industrial application of Switch Mode Power Converters (SMPCs). A poorly performing power supply in a power system can influence its operation and potentially compromise the entire system performance in terms of efficiency. To maintain a high reliability, high performance SMPC effective control is necessary for regulating the output of the SMPC system. However, an uncertainty is a key factor in SMPC operation. For example, parameter variations can be caused by environmental effects such as temperature, pressure and humidity. Usually, fixed controllers cannot respond optimally and generate an effective signal to compensate the output error caused by time varying parameter changes. Therefore, the stability is potentially compromised in this case. To resolve this problem, increasing interest has been shown in employing online system identification techniques to estimate the parameter values in real time. Moreover, the control scheme applied after system identification is often called “adaptive control” due to the control signal selfadapting to the parameter variation by receiving the information from the system identification process. In system identification, the Recursive Least Square (RLS) algorithm has been widely used because it is well understood and easy to implement. However, despite the popularity of RLS, the high computational cost and slow convergence speed are the main restrictions for use in SMPC applications. For this reason, this research presents an alternative algorithm to RLS; Fast Affline Projection (FAP). Detailed mathematical analysis proves the superior computational efficiency of this algorithm. Moreover, simulation and experiment result verify this unique adaptive algorithm has improved performance in terms of computational cost and convergence speed compared with the conventional RLS methods. Finally, a novel adaptive control scheme is designed for optimal control of a DC-DC buck converter during transient periods. By applying the proposed adaptive algorithm, the control signal can be successfully employed to change the ON/OFF state of the power transistor in the DC-DC buck converter to improve the dynamic behaviour. Simulation and experiment result show the proposed adaptive control scheme significantly improves the transient response of the buck converter, particularly during an abrupt load change conditio

Multi-Loop-Ring-Oscillator Design and Analysis for Sub-Micron CMOS

Ring oscillators provide a central role in timing circuits for today?s mobile devices and desktop computers. Increased integration in these devices exacerbates switching noise on the supply, necessitating improved supply resilience. Furthermore, reduced voltage headroom in submicron technologies limits the number of stacked transistors available in a delay cell. Hence, conventional single-loop oscillators offer relatively few design options to achieve desired specifications, such as supply rejection. Existing state-of-the-art supply-rejection- enhancement methods include actively regulating the supply with an LDO, employing a fully differential or current-starved delay cell, using a hi-Z voltage-to-current converter, or compensating/calibrating the delay cell. Multiloop ring oscillators (MROs) offer an additional solution because by employing a more complex ring-connection structure and associated delay cell, the designer obtains an additional degree of freedom to meet the desired specifications. Designing these more complex multiloop structures to start reliably and achieve the desired performance requires a systematic analysis procedure, which we attack on two fronts: (1) a generalized delay-cell viewpoint of the MRO structure to assist in both analysis and circuit layout, and (2) a survey of phase-noise analysis to provide a bank of methods to analyze MRO phase noise. We distill the salient phase-noise-analysis concepts/key equations previously developed to facilitate MRO and other non-conventional oscillator analysis. Furthermore, our proposed analysis framework demonstrates that all these methods boil down to obtaining three things: (1) noise modulation function (NMF), (2) noise transfer function (NTF), and (3) current-controlled-oscillator gain (KICO). As a case study, we detail the design, analysis, and measurement of a proposed multiloop ring oscillator structure that provides improved power-supply isolation (more than 20dB increase in supply rejection over a conventional-oscillator control case fabricated on the same test chip). Applying our general multi-loop-oscillator framework to this proposed MRO circuit leads both to design-oriented expressions for the oscillation frequency and supply rejection as well as to an efficient layout technique facilitating cross-coupling for improved quadrature accuracy and systematic, substantially simplified layout effort

A strategy for short-term load forecasting in Ireland

Electric utilities require short-term forecasts of electricity demand (load) in order to schedule generating plant up to several days ahead on an hourly basis. Errors in the forecasts may lead to generation plant operation that is not required or sub-optimal scheduling of generation plants. In addition, with the introduction of the Electricity Regulation Act 1999, a deregulated market structure has been introduced, adding increased impetus to reducing forecast error and the associated costs. This thesis presents a strategy for reducing costs from electrical demand forecast error using models designed specifically for the Irish system. The differences in short-term load forecasting models are examined under three independent categories: how the data is segmented prior to modelling, the modelling technique and the approach taken to minimise the effect of weather forecast errors present in weather inputs to the load forecasting models. A novel approach is presented to determine whether the data should be segmented by hour of the day prior to modelling. Several segmentation strategies are analysed and the one appropriate for Irish data identified. Furthermore, both linear and nonlinear techniques are compared with a view to evaluating the optimal model type. The effect of weather forecast errors on load forecasting models, though significant, has largely been ignored in the literature. Thus, the underlying issues are examined and a novel method is presented which minimises the effect of weather forecast errors