This letter studies if and to which extent COVID-19 epidemics can be controlled by authorities taking decisions on public health measures on the basis of daily reports of swab test results, active ...cases and total cases. A suitably simplified process model is derived to support the controllability analysis, highlighting the presence of very significant time delay; the model is validated with data from several outbreaks. The analysis shows that suppression strategies can be effective if strong enough and enacted early on. It also shows how mitigation strategies can fail because of the combination of delay, unstable dynamics, and uncertainty in the feedback loop; approximate conditions based on the theory of limitation of linear control are given for feedback control to be feasible.
Reference and command governors are add-on control schemes which enforce state and control constraints on pre-stabilized systems by modifying, whenever necessary, the reference. This paper surveys ...the extensive literature concerning the development of such schemes for linear and nonlinear systems. The treatment of unmeasured disturbances and parametric uncertainties is also detailed. Generalizations, including extended command governors, feedforward reference governors, reduced order reference governors, parameter governors, networked reference governors, and decentralized/distributed reference governors, are discussed. Practical applications of these techniques are presented and surveyed as well. A comprehensive list of references is included. Connections with related approaches, including model predictive control and input shaping, are discussed. Opportunities and directions for future research are highlighted.
Urban noise pollution is an omnipresent but often neglected threat to public health that must be addressed urgently. Passive noise control measures, which are less effective at reducing low-frequency ...noise and are often bulky and may impede airflow. As evidenced in automobiles, active control of cabin noise has resulted in lighter cars due to reduced passive insulation. Despite its long history and recent popularisation by consumer headphones, the implementation of active noise control in the built environment is still rare. To date, active noise control (ANC) has been demonstrated, at source, in construction machines and, in the transmission path, in noise barriers. Recent demand for naturally-ventilated buildings has also spurred the development of active control solutions at the receiving end, such as on windows. The ten questions aim to demystify the principles of ANC and highlight areas in which environmental noise can be actively mitigated. Since the implementation of active control in the built environment usually involves multiple stakeholders, operational concerns are addressed. To conclude, research gaps are identified that would enable increased adoption of ANC in the built environment. There is also renewed interest in applying intelligent ANC to tackle environmentally complex applications, such as varying noise levels in the earcup of ANC headphones, particularly with the advent of the low-cost, low-power, highly-efficient embedded electronics; advancing speaker technology; and new impetus from digital signal processing and artificial intelligence Algorithms.
•How can we implement active noise control in the built environment?•How to implement active noise control on noise barriers?•How feasible is active noise control for façade elements?•Is it possible to actively control noise in a large open space?•Is there a synergy between active noise control and the soundscape approach?
We study a variation of the classical Pandora’s problem in which a decision maker (DM) sequentially explores alternatives from a given set and learns their values while trying to acquire the best ...alternative. The variations in the model we study are (i) alternatives randomly become unavailable during exploration and (ii) the DM’s ability to acquire a remaining alternative is uncertain and depends on a chosen offer price. Such acquisition uncertainties arise in many applications, including housing search, hiring problems, and e-commerce, but greatly complicate the search problem in that optimal policies retain all previously explored alternative values as part of the problem state, as opposed to only the highest explored value as in Pandora’s rule. Our central insight is that despite the complexity that these acquisition uncertainties create, simple greedy policies based on static sequencing and a single threshold value enjoy strong performance guarantees. We develop such a class of policies and show how to compute them using a greedy algorithm whose worst-case run-time scales linearly (up to logarithmic factors) in the number of alternative types. We show that our policies (a) are asymptotically optimal in high multiplicity regimes with many alternatives and (b) obtain at least Formula: see text of the optimal value under a broad set of conditions. Extensive numerical examples support this theory: We illustrate our policies on a variation of Pandora’s problem with disappearing alternatives and housing search on models calibrated on data from the online brokerage Redfin. In these examples, our policies significantly outperform policies based on Pandora’s rule.
This paper was accepted by Omar Besbes, revenue management and market analytics.
Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2022.00203 .
In this paper, we consider a frequency-dependent portfolio optimization problem with multiple assets using a control-theoretic approach. The expected logarithmic growth (ELG) rate of wealth is used ...as the objective performance metric. It is known that if the portfolio contains a special asset, the so-called dominant asset, then the optimal ELG level is achieved by investing all available funds in that asset. However, this “all-in” strategy is arguably too risky to implement. As a result, we study the case where the portfolio weights are chosen in a rather ad-hoc manner, and a linear buy-and-hold strategy is subsequently used. We show that if the underlying portfolio contains a dominant asset, buy and hold on that specific asset is asymptotically log-optimal with a logarithmic convergence rate. This result also extends to the scenario when a trader does not have a probabilistic model for returns or does not trust a model based on historical data. Specifically, we prove a version of the one fund theorem, which states that if a market contains a dominant asset, buying and holding a market portfolio with nonzero weights for each asset is asymptotically log-optimal. Additionally, we extend an existing result regarding the property called high-frequency maximality of an ELG-based portfolio from a single asset to a multi-asset portfolio case. This means that, in the absence of transaction costs, high-frequency rebalancing is unbeatable in terms of ELG. This result enables us to further improve the log-optimality obtained previously. Finally, we provide a result on the issue of how often a portfolio should be rebalanced, if needed. Examples using simulations with high-frequency historical trading data are included throughout to illustrate the theory.
This paper describes various regulatory and advanced control schemes which can be applied to industrial gas headers. The intention is to exploit the buffering capacity for pollution control as well ...as improve flow stability for consumers. The control schemes are compared using a Monte Carlo simulation on a simulated case study and a sensitivity analysis is done to evaluate the impact of variations in the gas properties on the cost functions. A compensated linear model predictive controller (CLMPC) is implemented on a real industrial header and compared with standard proportional–integral (PI) control. It is found that gas emissions and consumer stability can be substantially improved by intelligently utilising the available pressure buffering capacity in industrial gas headers.
This paper develops and assesses the performance of a short-term demand response (DR) model for utility load control with applications to resource planning and control design. Long term response ...models tend to underestimate short-term demand response when induced by prices. This has two important consequences. First, planning studies tend to undervalue DR and often overlook its benefits in utility demand management program development. Second, when DR is not overlooked, the open-loop DR control gain estimate may be too low. This can result in overuse of load resources, control instability and excessive price volatility. Our objective is therefore to develop a more accurate and better performing short-term demand response model. We construct the model from first principles about the nature of thermostatic load control and show that the resulting formulation corresponds exactly to the Random Utility Model employed in economics to study consumer choice. The model is tested against empirical data collected from field demonstration projects and is shown to perform better than alternative models commonly used to forecast demand in normal operating conditions. The results suggest that (1) existing utility tariffs appear to be inadequate to incentivize demand response, particularly in the presence of high renewables, and (2) existing load control systems run the risk of becoming unstable if utilities close the loop on real-time prices.
The evolution of manufacturing systems into a smart factory brings advantages but also increased cyber-risks. This paper investigates the problem of intrusion detection and autonomous response to ...cyber-attacks targeting the control logic of industrial control applications for the smart factory. Specifically, we propose ASiMOV (Asynchronous Modular Verification), a self-protecting architecture for cyber–physical systems realizing a verifiable control application. ASiMOV is inspired by modular redundancy and leverages virtualization technologies to respond and to prevent cyber-attacks to the control logic. Using simulation experiments, we evaluate: the effects of an attack on an industrial control application enhanced by ASiMOV; the delay introduced by ASiMOV within a control loop; and the cyber-attack detection delay. Results show that, in the simulated scenario, the controller can work with a sampling rate of up to 200 Hertz. Any tampering with the control logic is detected without false positives/negatives in a time equal to the latency between the proposed control application and the proposed IDS (e.g., tens to hundreds of milliseconds).
•A Verifiable Controller (VC) to detect attacks to a control system’s logic.•A microservices implementation of VC (microservice-VC).•A microservice-VC can be distributed among asynchronous devices.•Dynamic orchestration of a microservice-VC to mitigate cyber-attacks.•A microservice VC can detect cyberattacks to the control logic in an estimable time.
•Modified GADRC is formulated for microgrid system with communication delay.•Generalized controller design formulae for hybrid microgrid are derived.•Robustness of the proposed controller is verified ...via extensive case study.•Real time wind and solar data is used to verify efficacy of modified GADRC method.
In this paper, generalized active disturbance rejection control (GADRC) technique in the presence of communication delay is proposed for load frequency control of a hybrid microgrid system, which is composed of renewable energy sources such as solar and wind input, energy storage devices such as battery energy storage system and flywheel energy storage system as well as fuel cell and diesel generator which are controllable sources of energy. The presence of communication delay involved in transmission of control signals is also considered for controller design. Further, the robustness of proposed scheme is investigated via an elaborate study comprising of varying communication delay, parametric uncertainty, nonlinearities such as generation rate constraint and governor deadband, as well as mismatch in communication delay between the inputs of observer. Finally, the performance indices of the proposed scheme are compared with conventional and fractional order based controller design approaches. The simulation results are a testimony to the efficacy of proposed scheme.
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