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Our efforts as a society to combat the ongoing COVID-19 pandemic are continuously challenged by the emergence of new variants. These variants can be more infectious than existing strains and many of them are also more resistant to available vaccines. The appearance of these new variants cause new surges of infections, exacerbated by infrastructural difficulties, such as shortages of medical personnel or test kits. In this work, a high-resolution computational framework for modeling the simultaneous spread of two COVID-19 variants: a widely spread base variant and a new one, is established. The computational framework consists of a detailed database of a representative U.S. town and a high-resolution agent-based model that uses the Omicron variant as the base variant and offers flexibility in the incorporation of new variants. The results suggest that the spread of new variants can be contained with highly efficacious tests and mild loss of vaccine protection. However, the aggressiveness of the ongoing Omicron variant and the current waning vaccine immunity point to an endemic phase of COVID-19, in which multiple variants will coexist and residents continue to suffer from infections.

This paper studies the adaptive optimal control problem for a class of linear time-delay systems described by delay differential equations (DDEs). A crucial strategy is to take advantage of recent developments in reinforcement learning and adaptive dynamic programming and develop novel methods to learn adaptive optimal controllers from finite samples of input and state data. In this paper, the data-driven policy iteration (PI) is proposed to solve the infinite-dimensional algebraic Riccati equation (ARE) iteratively in the absence of exact model knowledge. Interestingly, the proposed recursive PI algorithm is new in the present context of continuous-time time-delay systems, even when the model knowledge is assumed known. The efficacy of the proposed learning-based control methods is validated by means of practical applications arising from metal cutting and autonomous driving., 12 pages, 8 figures

International audience; We provide a new event-triggered output feedback control method for time-varying linear systems, using the notions of interval observers and positive systems. Our methods ensure uniform global exponential stability of the closed-loop system that is robust with respect to uncertainty in the coefficient matrices. Our illustrations include a curve tracking system from marine robotics.

The potential waning of the vaccination immunity to COVID-19 could pose threats to public health, as it is tenable that the timing of such waning would synchronize with the near-complete restoration of normalcy. Should also testing be relaxed, we might witness a resurgent COVID-19 wave in winter 2021/2022. In response to this risk, an additional vaccine dose, the booster shot, is being administered worldwide. In a projected study with an outlook of six months, we explore the interplay between the rate at which boosters are distributed and the extent to which testing practices are implemented, using a highly granular agent-based model tuned on a medium-sized U.S. town. Theoretical projections indicate that the administration of boosters at the rate at which the vaccine is currently administered could yield a severe resurgence of the pandemic. Projections suggest that the peak levels of mid spring 2021 in the vaccination rate may prevent such a scenario to occur, although exact agreement between observations and projections should not be expected due to continuously evolving nature of the pandemics. Our study highlights the importance of testing, especially to detect asymptomatic individuals in the near future, as the release of the booster reaches full speed., Comment: 56 pages; 15 figures; accepted for publication in Advanced Theory and Simulations

The ongoing pandemic is laying bare dramatic differences in the spread of COVID-19 across seemingly similar urban environments. Identifying the urban determinants that underlie these differences is an open research question, which can contribute to more epidemiologically resilient cities, optimized testing and detection strategies, and effective immunization efforts. Here, we perform a computational analysis of COVID-19 spread in three cities of similar size in New York State (Colonie, New Rochelle, and Utica) aiming to isolate urban determinants of infections and deaths. We develop detailed digital representations of the cities and simulate COVID-19 spread using a complex agent-based model, taking into account differences in spatial layout, mobility, demographics, and occupational structure of the population. By critically comparing pandemic outcomes across the three cities under equivalent initial conditions, we provide compelling evidence in favor of the central role of hospitals. Specifically, with highly efficacious testing and detection, the number and capacity of hospitals, as well as the extent of vaccination of hospital employees are key determinants of COVID-19 spread. The modulating role of these determinants is reduced at lower efficacy of testing and detection, so that the pandemic outcome becomes equivalent across the three cities.

We provide new reduced order observers for continuous-time nonlinear systems, first in the case where there are continuous output measurements and next in the case where there are only discrete output measurements. When continuous measurements are available, we provide observers that converge in finite time. When only discrete measurements are available, we provide observers that do not converge in finite time, but which do converge asymptotically with a rate of convergence that is proportional to the negative of the logarithm of the size of the sampling interval. We illustrate our results in a pendulum example.

As COVID‐19 vaccine is being rolled out in the US, public health authorities are gradually reopening the economy. To date, there is no consensus on a common approach among local authorities. Here, a high‐resolution agent‐based model is proposed to examine the interplay between the increased immunity afforded by the vaccine roll‐out and the transmission risks associated with reopening efforts. The model faithfully reproduces the demographics, spatial layout, and mobility patterns of the town of New Rochelle, NY — representative of the urban fabric of the US. Model predictions warrant caution in the reopening under the current rate at which people are being vaccinated, whereby increasing access to social gatherings in leisure locations and households at a 1% daily rate can lead to a 28% increase in the fatality rate within the next three months. The vaccine roll‐out plays a crucial role on the safety of reopening: doubling the current vaccination rate is predicted to be sufficient for safe, rapid reopening., As COVID‐19 vaccine is rolling out, the economy is gradually reopening. This study offers scientific backing for the ongoing debate regarding the safety of reopening efforts via a high‐resolution computational model of a US town. Computational results suggest that the current vaccination rate can only support careful reopening. A swift return to normalcy would require at least doubling the vaccination speed.

International audience; We provide novel reduced-order observer designs for continuous-time nonlinear systems with measurement error. Our first result applies to systems with continuous output measurements, and provides observers that converge in a fixed finite time that is independent of the initial state when the measurement error is zero. Our second result applies under discrete measurements, and provides observers that converge asymptotically with a rate of convergence that is proportional to the negative of the logarithm of the size of a sampling interval. Our observers satisfy an enhanced input-to-state stability property with respect to the measurement error, in which an overshoot term only depends on a recent history of the measurement error. We illustrate our observers using a model of a single-link robotic manipulator coupled to a DC motor with a nonrigid joint, and in a pendulum example.

High-speed signal-free intersections are a novel urban traffic operations enabled by connected and autonomous vehicles. However, the impact of communication latency on intersection performance has not been well understood. In this paper, we consider vehicle coordination at signal-free intersections with latency. We focus on two questions: (i) how to ensure latency-resiliency of the coordination algorithm, and (ii) how latency affects the intersection's capacity. We consider a trajectory-based model with bounded speed uncertainties. Latency leads to uncertain state observation. We propose a piecewise-linear control law that ensures safety (avoidance of interference) as long as the initial condition is safe. We also analytically quantify the throughput that the proposed control can attain in the face of latency.

Considering the presence of time-delay in actuators and nonvanishing disturbance, a data-driven control technique is developed based on adaptive dynamic programming (ADP) to solve the reagents control problem for flotation processes. First, the reagents control problem is converted into an optimal regulator control problem. Second, a policy iteration (PI) algorithm has been adopted to find desirable adaptive suboptimal controllers. Unlike conventional controllers (PID, MPC) design, the proposed method can achieve the desired control performance by only employing online production data without the complete knowledge of the underlying flotation process dynamics. Specifically, the flotation indexes (tailing grade and concentrate grade) are forced to track the desired values with disturbance rejection and keep reagents consumption to a minimum. The convergence and stability of the proposed data-driven optimal control method are given, and the efficacy is validated in the simulation environment with industrial data.

Objective: To study the correlation of urodynamic characteristics with insulin resistance and serum damage media in patients with diabetes and benign prostatic hyperplasia (BPH). Methods: 45 patients with type 2 diabetes mellitus and BPH treated in our hospital between May 2014 and August 2016 were selected as DM+BPH group, 58 patients with BPH alone were selected as BPH group, and 50 healthy volunteers were selected as control group. Urodynamic tester was used to measure the maximum flow rate (MFR), postvoid residual (PVR) and detrusor pressure at maximum flow rate (Pdet), and serum was collected to determine insulin resistance indexes and oxidative stress indexes. Results: MFR and Pdet of DM+BPH group were significantly lower than those of control group (P

In this paper, we consider active trailer steering control as a means to improve the maneuverability of (long) truck-trailer combinations during cornering. Hereto, we formulate the problem of reducing the so-called swept path width during cornering and that of eliminating unsafe tail swing of the trailer as a tracking control problem. We present a kinematic tractor-trailer model including off-axle hitching, on the basis of which we design nonlinear control strategies solving this tracking problem. The effectiveness of the proposed approach is evidenced experimentally on a robotic tractor-trailer platform.

Ten new triterpenoid compounds with structure diversity of the C-17 side-chain, including nine tirucallanes, named xylocarpols A&ndash, E (1&ndash, 5) and agallochols A&ndash, D (6&ndash, 9), and an apotirucallane, named 25-dehydroxy protoxylogranatin B (10), were isolated from the mangrove plants Xylocarpus granatum, Xylocarpus moluccensis, and Excoecaria agallocha. The structures of these compounds were established by HR-ESIMS and extensive one-dimensional (1D) and two-dimensional (2D) NMR investigations. The absolute configurations of 1 and 2 were unequivocally determined by single-crystal X-ray diffraction analyses, conducted with Cu K&alpha, radiation, whereas those of 4, 6&ndash, 8 were assigned by a modified Mosher&rsquo, s method and the comparison of experimental electronic circular dichroism (ECD) spectra. Most notably, 5, 6, 7, and 9 displayed potent activation effects on farnesoid&ndash, X&ndash, receptor (FXR) at the concentration of 10.0 &mu, M, 10 exhibited very significant agonistic effects on pregnane&ndash, receptor (PXR) at the concentration of 10.0 nM.

This paper presents a new theory, known as robust dynamic pro- gramming, for a class of continuous-time dynamical systems. Different from traditional dynamic programming (DP) methods, this new theory serves as a fundamental tool to analyze the robustness of DP algorithms, and in par- ticular, to develop novel adaptive optimal control and reinforcement learning methods. In order to demonstrate the potential of this new framework, four illustrative applications in the fields of stochastic optimal control and adaptive DP are presented. Three numerical examples arising from both finance and engineering industries are also given, along with several possible extensions of the proposed framework.

This paper proposes relaxed suffient conditions for the consensus of multi-agent systems by the averaging protocols with time-varying system topology. Bidirectional information exchange between neighboring agents is considered and both the discrete-time and continuous-time consensus protocols are studied. It is shown that the consensus is reached if there exists an unbounded time sequence such that two agents who own the maximum and minimum states at each time instant in the sequence will be jointly connected at some future time. Further, this result is applied to the original nonlinear Vicsek model, and a sufficient condition for the heading consensus of the group with restricted initial conditions is obtained.

Recently, some researchers investigated the topology identification for complex networks via LaSalle’s invariance principle. The principle cannot be directly applied to time-varying systems since the positive limit sets are generally not invariant. In this paper, we study the topology identification problem for a class of weighted complex networks with time-varying node systems. Adaptive identification laws are proposed to estimate the coupling parameters of the networks with and without communication delays. We prove that the asymptotic identification is ensured by a persistently exciting condition. Numerical simulations are given to demonstrate the effectiveness of the proposed approach.

The authors address the tracking problem for a class of nonholonomic chained form control systems. A recursive technique is proposed which appears to be an extension of the currently popular integrator backstepping idea to the tracking of nonholonomic control systems. Conditions are given under which the problems of semiglobal tracking and global path-following are solved for a nonholonomic system in chained form and its dynamic extension. Results on local exponential tracking are also obtained. Two physical examples of an articulated vehicle and a knife edge are provided to demonstrate the effectiveness of our algorithm through simulations.

In this paper we deal with the state-feedback tracking control problem for a class of nonholonomic dynamic systems in chained form. By means of the recursive technique proposed in our recent work, we first show that the semiglobal exponential tracking can be easily obtained for systems in chained form. Then, we show that, whenever the control inputs are subject to saturation constraints, a semiglobal asymptotic tracking controller can be found on the basis of Lyapunov redesign and backstepping techniques.

In this paper, we provide a constructive methodology for the design of decentralized control laws for a class of interconnected retarded systems subject to actuator disturbances. We consider Control Lyapunov-Krasovskii functionals for only subsystems, thus reducing the difficulty with respect to finding an overall functional, and then provide a controller which, by means of a small-gain condition, guarantees practical input-to-state stability with respect to disturbances. If the disturbances are bounded, the controller allows to drive the system variables to any small neighborhood of the origin, by suitably tuning a control parameter.

This article deals with interconnected systems described by retarded nonlinear equations with discontinuous right-hand side. The problem of feedback control redesign to achieve ISS (input-to-state stability) and iISS (integral input-to-state stability) with respect to additive disturbances acting on each subsystem is solved. It is shown that it is possible to design a decentralized controller accomplishing the robustification whenever a small-gain condition is satisfied.

Optimization models explain many aspects of biological goal-directed movements. However, most such models use a finite-horizon formulation, which requires a prefixed movement duration to define a cost function and solve the optimization problem. To predict movement duration, these models have to be run multiple times with different prefixed durations until an appropriate duration is found by trial and error. The constrained minimum time model directly predicts movement duration; however, it does not consider sensory feedback and is thus applicable only to open-loop movements. To address these problems, we analyzed and simulated an infinite-horizon optimal feedback control model, with linear plants, that contains both control-dependent and control-independent noise and optimizes steady-state accuracy and energetic costs per unit time. The model applies the steady-state estimator and controller continuously to guide an effector to, and keep it at, target position. As such, it integrates movement control and posture maintenance without artificially dividing them with a precise, prefixed time boundary. Movement pace is determined by the model parameters, and the duration is an emergent property with trial-to-trial variability. By considering the mean duration, we derived both the log and power forms of Fitts's law as different approximations of the model. Moreover, the model reproduces typically observed velocity profiles and occasional transient overshoots. For unbiased sensory feedback, the effector reaches the target without bias, in contrast to finite-horizon models that systematically undershoot target when energetic cost is considered. Finally, the model does not involve backward and forward sweeps in time, its stability is easily checked, and the same solution applies to movements of different initial conditions and distances. We argue that biological systems could use steady-state solutions as default control mechanisms and might seek additional optimization of transient costs when justified or demanded by task or context.

In this paper we consider the ISS (input-to-state stability) and iISS (integral input-to-state stability) feedback control redesign for interconnected systems described by retarded nonlinear equations with discontinuous right-hand side. We show that it is possible to design a decentralized controller by which the overall closed-loop system is iISS (ISS) with respect to additive disturbances acting on each subsystem whenever the disturbance-free closed-loop system satisfies a small-gain condition.

In this paper, we deal with the problem of global tracking and stabilization control of internally damped mobile robots with unknown parameters, and subject to input torque saturation and external disturbances. To overcome the difficulties due to these factors, a new adaptive scheme is proposed to ensure the bounds of the control torques as functions of only design parameters and reference trajectories and thus computable in advance. Then suitable design parameters are determined so that such bounds are within the given saturation limits. To compensate for the disturbances, we estimate their unknown bounds and employ the estimates in controller design. System stability, perfect tracking and stabilization to the origin are established. Simulation studies conducted also verify the effectiveness of the proposed scheme.

This paper considers interconnected retarded nonlinear systems. Integral input-to-state stable subsystems and the construction of Lyapunov-Krasovskii functionals for their interconnections are focused on. Both discrete and distributed time-delays in the subsystems and the communication channels are covered. This paper provides a sufficient small-gain type condition for the stability of the interconnected systems with respect to external inputs in the framework of Lyapunov-Krasovskii functionals. Global asymptotic stability is addressed as a special case which deals with time-varying delays in communication channels effectively.

This technical note studies the global output feedback stabilization problem for a chemostat with an arbitrary number of species competing for a single nutrient source. It is shown that coexistence can be achieved by means of a feedback control of the substrate input concentration and an appropriate choice of a constant dilution rate. The input substrate feedback controller proposed is a dynamic time-varying output feedback, with the substrate concentration considered as the output. The result relies on the construction of a novel nonlinear observer and is established via a Lyapunov-based proof.

This paper extends the nonlinear ISS small-gain theorem to a large-scale time delay system composed of three or more subsystems. En route to proving this small-gain theorem for systems of differential equations with delays, a small-gain theorem for operators is examined. The result developed for operators allows applications to a wide class of systems, including state space systems with delays., 6 pages

In this technical note, under widely used joint connectivity assumptions, some necessary and/or sufficient conditions for the heading consensus of autonomous multi-agent systems described by Vicsek's model are proposed. Further, more general nonaveraging protocols are studied for which necessary and/or sufficient conditions for the consensus are also given. © 2009 IEEE.

This paper presents further results on the problem of establishing stability of retarded nonlinear interconnected systems comprising integral input-to-state stable subsystems. It is shown that the stability of the interconnected systems with respect to external signals can be verified by constructing Lyapunov-Krasovskii functionals explicitly whenever small-gain type conditions are satisfied. The primary result [12] is generalized in two aspects. One is to introduce a new flexibility in constructing Lyapunov-Krasovskii functionals to deal with distributed delays more effectively. The other is to cover systems involving time-varying delays in interconnecting channels.

In this work, we propose a methodology for the expression of necessary and sufficient Lyapunov-like conditions for the existence of stabilizing feedback laws. The methodology is an extension of the well-known Control Lyapunov Function (CLF) method and can be applied to very general nonlinear time-varying systems with disturbance and control inputs, including both finite- and infinite-dimensional systems. The generality of the proposed methodology is also reflected upon by the fact that partial stability with respect to output variables is addressed. In addition, it is shown that the generalized CLF method can lead to a novel tool for the explicit design of robust nonlinear controllers for a class of time-delay nonlinear systems with a triangular structure., 44 pages

In this work characterizations of external notions of output stability for uncertain time-varying systems described by retarded functional differential equations are provided. Particularly, characterizations by means of Lyapunov and Razumikhin functions of (uniform) Weighted Input-to-Output Stability are given. The results of this work have been developed for systems with outputs in abstract normed linear spaces in order to allow outputs with no delay, with discrete or distributed delay or functional outputs with memory.

Inspired by Vicsek's model, in this paper we propose two decentralized heading consensus algorithms for nonlinear multi-agent systems. The first algorithm, called WHCA, can be seen as a weighted Vicsek's model. The second algorithm, named LBHCA, is a leader-follower strategy based on the WHCA. It is proved that, under a well-known connectivity assumption, the algorithm WHCA can ensure almost global consensus of the headings, except for the situation where they are initially balanced. For the LBHCA, the global heading consensus is guaranteed under the same connectivity assumption. Simulation results are provided to justify the proposed algorithms. Copyright © 2008 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society

In this paper a new Lyapunov-Krasovskii methodology for nonlinear coupled delay differential difference equations is proposed. This methodology is based on the concept of input-to-state stability applied to the difference equation, for which a sufficient Lyapunov criterion is given, and on previous methodologies developed in the literature for linear delay descriptor systems.