Actuator and sensor delays are among the most common dynamic phenomena in engineering practice, and when disregarded, they render controlled systems unstable. Over the past sixty years, predictor ...feedback has been a key tool for compensating such delays, but conventional predictor feedback algorithms assume that the delays and other parameters of a given system are known. When incorrect parameter values are used in the predictor, the resulting controller may be as destabilizing as without the delay compensation. Delay-Adaptive Linear Control develops adaptive predictor feedback algorithms equipped with online estimators of unknown delays and other parameters. Such estimators are designed as nonlinear differential equations, which dynamically adjust the parameters of the predictor. The design and analysis of the adaptive predictors involves a Lyapunov stability study of systems whose dimension is infinite, because of the delays, and nonlinear, because of the parameter estimators. This comprehensive book solves adaptive delay compensation problems for systems with single and multiple inputs/outputs, unknown and distinct delays in different input channels, unknown delay kernels, unknown plant parameters, unmeasurable finite-dimensional plant states, and unmeasurable infinite-dimensional actuator states.Presenting breakthroughs in adaptive control and control of delay systems, Delay-Adaptive Linear Control offers powerful new tools for the control engineer and the mathematician.
Summary
In this paper, we provide a new nonconservative upper bound for the settling time of a class of fixed‐time stable systems. To expose the value and the applicability of this result, we present ...four main contributions. First, we revisit the well‐known class of fixed‐time stable systems, to show the conservatism of the classical upper estimate of its settling time. Second, we provide the smallest constant that the uniformly upper bounds the settling time of any trajectory of the system under consideration. Third, introducing a slight modification of the previous class of fixed‐time systems, we propose a new predefined‐time convergent algorithm where the least upper bound of the settling time is set a priori as a parameter of the system. At last, we design a class of predefined‐time controllers for first‐ and second‐order systems based on the exposed stability analysis. Simulation results highlight the performance of the proposed scheme regarding settling time estimation compared to existing methods.
A nonconformal hybrid finite difference time domain (FDTD)/finite element time domain (FETD) method was previously introduced, which implemented the hybridization through a buffer zone. Although this ...method has been demonstrated to be accurate and long-time stable, further efforts are still desirable to remove the buffer zone and to implement an implicit-explicit time integration from the perspective of practical applications. In this paper, a novel hybrid method is proposed, which not only successfully eliminates the necessity of the buffer zone without compromising the featured advantage (e.g., nonconformal mesh) but also effectively applies an implicit-explicit time integration scheme to improve the computational efficiency. Furthermore, the new method extends the hybridization to a broader level by incorporating the spectral element time domain (SETD) method based on the discontinuous Galerkin and domain decomposition techniques, resulting in a more general hybrid FDTD/SETD/FETD framework. The framework employs the explicit leapfrog time integration for the FDTD region while it employs the implicit Crank-Nicolson time integration for the FETD region. For the SETD region, either the implicit or explicit time integration can be employed, depending on the mesh sizes in it. When the implicit region becomes large, it can be further split into multiple subdomains to reduce computational complexity. Numerical examples are included to demonstrate the performance of the proposed hybrid method, which is accurate, long-time stable and more efficient than the hybrid method with a buffer zone.
highlights•We present algorithms to determine the most reliable strategy and path on stochastic and time-dependent networks.•The measure of reliability chosen is the on-time arrival probability at ...the destination.•We present a decreasing order-of-time algorithm for optimal time-adaptive strategy and a pruning algorithm for optimal path.•We derive the correctness of the proposed procedures and show their efficacy on large-scale transportation networks.
This study presents algorithms to determine the most reliable routes on stochastic and time-dependent networks. The measure of reliability adopted is the probability of on-time arrival at the destination, given a threshold arrival-time. We propose two distinct algorithms to determine optimal time-adaptive strategy and optimal apriori path on stochastic and time-dependent networks. First, a decreasing order-of-time algorithm is proposed to determine the optimal strategy to the sink from all node and departure-time combinations. Second, a label-correcting, network pruning algorithm is proposed to determine the optimal path between the source and the sink for a given departure-time. The correctness of both the proposed algorithms is proved and their computational complexity expressions are derived. The efficacy of the proposed procedures is demonstrated on large-scale transportation networks. This work has the potential to facilitate wider application of stochastic and time-dependent networks in reliability-based modeling and analysis.
Single-channel, speaker-independent speech separation methods have recently seen great progress. However, the accuracy, latency, and computational cost of such methods remain insufficient. The ...majority of the previous methods have formulated the separation problem through the time-frequency representation of the mixed signal, which has several drawbacks, including the decoupling of the phase and magnitude of the signal, the suboptimality of time-frequency representation for speech separation, and the long latency in calculating the spectrograms. To address these shortcomings, we propose a fully convolutional time-domain audio separation network (Conv-TasNet), a deep learning framework for end-to-end time-domain speech separation. Conv-TasNet uses a linear encoder to generate a representation of the speech waveform optimized for separating individual speakers. Speaker separation is achieved by applying a set of weighting functions (masks) to the encoder output. The modified encoder representations are then inverted back to the waveforms using a linear decoder. The masks are found using a temporal convolutional network consisting of stacked one-dimensional dilated convolutional blocks, which allows the network to model the long-term dependencies of the speech signal while maintaining a small model size. The proposed Conv-TasNet system significantly outperforms previous time-frequency masking methods in separating two- and three-speaker mixtures. Additionally, Conv-TasNet surpasses several ideal time-frequency magnitude masks in two-speaker speech separation as evaluated by both objective distortion measures and subjective quality assessment by human listeners. Finally, Conv-TasNet has a significantly smaller model size and a shorter minimum latency, making it a suitable solution for both offline and real-time speech separation applications. This study, therefore, represents a major step toward the realization of speech separation systems for real-world speech processing technologies.
This book is for graduate students--and others--who want to become more productive writers. It's especially written for those who want to: •increase their motivation, focus, and persistence to move a ...project to completion •overcome procrastination and perfectionistic tendencies •reduce (or write in spite of) their anxiety and fear of writing •manage their time, work, energy (and advisor) for greater productivityWhile Jan Allen recognizes that writing is not an innate talent for most of us, she demonstrates that it is a process based on skills which we can identify, learn, practice and refine. She focuses both on the process and habits of writing as well as on helping you uncover what kind of writeryou are, and reflect on your challenges and successes. With a light touch and an engaging sense of humor, she proposes strategies to overcome procrastination and distractions, and build a writing practice to enable you to become a more productive and prolific writer.
This paper studies finite-time stability analysis and finite-time stabilization of linear systems by bounded linear time-varying feedback. On the one hand, (both local and global) finite-time ...stability of general nonlinear time-varying systems is investigated by the comparison principle and the notion of finite-time escaping functions. Some Lyapunov-like stability theorems are established. On the other hand, finite-time and prescribed-time stabilization of linear systems by bounded linear time-varying feedback are revisited based on the proposed finite-time stability theorems. Two classes of new time-varying high-gain functions are proposed to reduce the regulation time. Some connections of the proposed results to existing results on Lyapunov-inequality based finite-time stability analysis and nonlinear feedback based finite-time stabilization are revealed. The effectiveness of the proposed methods is illustrated by a numerical example.
Planktonic foraminifera are widely utilized for the biostratigraphy of Cretaceous and Cenozoic marine sediments and are a fundamental component of Cenozoic chronostratigraphy. The recent enhancements ...in deep sea drilling recovery, multiple coring and high resolution sampling both offshore and onshore, has improved the planktonic foraminiferal calibrations to magnetostratigraphy and/or modified species ranges. This accumulated new information has allowed many of the planktonic foraminiferal bioevents of the Cenozoic to be revised and the planktonic foraminiferal calibrations to be reassessed. We incorporate these developments and amendments into the existing biostratigraphic zonal scheme.
In this paper we present an amended low-latitude (tropical and subtropical) Cenozoic planktonic foraminiferal zonation. We compile 187 revised calibrations of planktonic foraminiferal bioevents from multiple sources for the Cenozoic and have incorporated these recalibrations into a revised Cenozoic planktonic foraminiferal biochronology. We review and synthesize these calibrations to both the geomagnetic polarity time scale (GPTS) of the Cenozoic and astronomical time scale (ATS) of the Neogene and late Paleogene. On the whole, these recalibrations are consistent with the previous work; however, in some cases, they have led to major adjustments to the duration of biochrons. Recalibrations of the early–middle Eocene first appearance datums of
Globigerinatheka kugleri,
Hantkenina singanoae, Guembelitrioides nuttalli and
Turborotalia frontosa have resulted in large changes in the durations of Biochrons E7, E8 and E9. We have introduced (upper Oligocene) Zone O7 utilizing the biostratigraphic utility of ‘
Paragloborotalia’ pseudokugleri. For the Neogene Period, major revisions are applied to the fohsellid lineage of the middle Miocene and we have modified the criteria for recognition of Zones M7, M8 and M9, with additional adjustments regarding the
Globigerinatella lineage to Zones M2 and M3. The revised and recalibrated datums provide a major advance in biochronologic resolution and a template for future progress of the Cenozoic time scale.
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