Analysis of Automotive Cyber-Attacks on Highways using Partial Differential Equation Models

This is the author accepted manuscript.This paper considers scenarios wherein a group of malicious vehicles on a highway perform a cooperative attack with the motive of creating undesirable wave effects among other vehicles on the highway. The two species of vehicles - malicious vehicles and normal vehicles, and their associated interaction effects, are modeled using Partial Differential Equations (PDEs). The malicious vehicles, which may be arbitrarily distributed on the highway, perform a sequence of velocity changes with the objective of making the density/velocity profile on the highway, track a reference profile. This reference profile (chosen by the malicious vehicles) has the property that once generated, it spontaneously evolves into a shock wave that propagates along the highway. Analytical expressions governing the velocity inputs of the malicious vehicles with which they can generate such waves are determined, for perfect as well as imperfect information scenarios. Simulation results are presented to validate the theoryThe first two authors would like to acknowledge support from the National Science Foundation. This material is based upon work supported by the National Science Foundation under Grant IIS-1351677

Comparison of surrogate-based uncertainty quantification methods for computationally expensive simulators

This version: arXiv:1511.00926v4 [math.ST] Available from ArXiv.org via the link in this record.Polynomial chaos and Gaussian process emulation are methods for surrogate-based uncertainty quantification, and have been developed independently in their respective communities over the last 25 years. Despite tackling similar problems in the field, to our knowledge there has yet to be a critical comparison of the two approaches in the literature. We begin by providing a detailed description of polynomial chaos and Gaussian process approaches for building a surrogate model of a black-box function. The accuracy of each surrogate method is then tested and compared for two simulators used in industry: a land-surface model (adJULES) and a launch vehicle controller (VEGACONTROL). We analyse surrogates built on experimental designs of various size and type to investigate their performance in a range of modelling scenarios. Specifically, polynomial chaos and Gaussian process surrogates are built on Sobol sequence and tensor grid designs. Their accuracy is measured by their ability to estimate the mean, standard deviation, exceedance probabilities and probability density function of the simulator output, as well as a root mean square error metric, based on an independent validation design. We find that one method does not unanimously outperform the other, but advantages can be gained in some cases, such that the preferred method depends on the modelling goals of the practitioner. Our conclusions are likely to depend somewhat on the modelling choices for the surrogates as well as the design strategy. We hope that this work will spark future comparisons of the two methods in their more advanced formulations and for different sampling strategies

Design and Validation of a Distributed Observer-Based Estimation Scheme for Power Grids

This is the author accepted manuscript. The final version is available from IEEE via the DOI in this record.This paper presents a novel estimation scheme for power grids based on distributed observers. Assuming only the generator voltage phase angles are measured and the electrical load active power demands are specified, we design an observer for each bus of the power grid, exploiting only knowledge of local information about the power system. In particular, we propose a super-twisting-like sliding mode observer to estimate the frequency deviation for each generator bus, and a so-called algebraic observer to estimate the load voltage phase angle for each load bus based on distributed iterative algorithms. The observer-based estimation scheme is validated by considering the IEEE 39 bus SimPowerSystems model

Higher Order Sliding Mode Observers in Power Grids with Traditional and Renewable Sources

This is the author accepted manuscript. The final version is available from IEEE via the DOI in this recordThis letter considers the application of higher order sliding mode (SM) observers to robustly and dynamically estimate the unmeasured state variables in modern power grids, in which both traditional and renewable energy sources coexist. In particular, a power grid composed of traditional, wind and inverter-based sources connected with dynamical loads is considered. Assuming that only the voltage phase angles are locally measured, a dedicated higher order SM observer is designed for each component, which is able to estimate in finite time the unmeasured state variables. Numerical simulations demonstrate the accuracy of the proposed scheme, also when compared with well-established linear observers

Higher Order Sliding Mode Observers in Power Grids with Traditional and Renewable Sources

This is the author accepted manuscript. The final version is available from IEEE via the DOI in this recordThis letter considers the application of higher order sliding mode (SM) observers to robustly and dynamically estimate the unmeasured state variables in modern power grids, in which both traditional and renewable energy sources coexist. In particular, a power grid composed of traditional, wind and inverter-based sources connected with dynamical loads is considered. Assuming that only the voltage phase angles are locally measured, a dedicated higher order SM observer is designed for each component, which is able to estimate in finite time the unmeasured state variables. Numerical simulations demonstrate the accuracy of the proposed scheme, also when compared with well-established linear observers

Sliding Mode Based Dynamic State Estimation for Synchronous Generators in Power Systems

This is the author accepted manuscript. The final version is available from IEEE via the DOI in this record This letter deals with the design of a robust sliding mode observer for dynamic state estimation applied to synchronous generators in power systems. Assuming only the frequency deviation of the generator is measured via phasor measurement units, we use a robust sliding mode estimation technique to dynamically reconstruct the rotor angle and the transient voltage. The adopted estimation technique is insensitive to matched bounded uncertainties affecting the dynamics of the synchronous generator. A stability analysis and tuning rules for the observer are also provided. Numerical simulations confirm the validity of the approach

Optimal Observer-Based Power Imbalance Allocation forFrequency Regulation in Shipboard Microgrids

This is the final version. Available on open access from MDPI via the DOI in this recordData Availability Statement: The data presented in this study are available on request from the corresponding author.This paper proposes a two-level control strategy based on a super-twisting sliding-mode algorithm (STA) to optimally allocate power imbalances in shipboard microgrids (SMGs) while achieving frequency regulation. The strategy employs an STA observer to estimate the unknown power load demand imbalances in finite time. This estimate is then passed to an online high-level optimal control framework to periodically determine the optimal sequence of power reference values for each energy storage device (ESS), minimising the operational cost of the SMG. The online optimised power reference values are interpolated and passed to the low-level STA control strategy to control the output power of each ESS. The efficacy of the proposed methods is demonstrated through numerical simulations conducted on a prototypical model of an SMG equipped with two ESSs, namely batteries and fuel cells with associated hydrogen storage.Innovate U

Model based moving horizon optimal modes-switch schedule in hybrid powertrains for marine applications

This is the author accepted manuscriptData availability statement: The research data supporting this publication are provided within this paper.Nowadays, the hybridisation and the electrification of the powertrains for the marine sectors are of paramount importance to reduce their carbon footprints. In this paper, a novel method is proposed to schedule the modes-switch of an hybrid powertrain for marine applications. The considered system is composed of an Internal Combustion Engine mounted in parallel with a Lynch DC Brushed Electric Machine to deliver power at the propeller shaft. The two key-findings of this paper are: i) A compact mathematical representation of the powertrain to model the energy balances and switching of the different modes of operation. ii) A novel graph-inspired approach to determine the optimal operational mode sequence. The objective is to find the modes schedule over a fixed time horizon that minimises both the fuel consumed and the number of modes changes. The solution is motivated by both the moving horizon principle and the shortest path identification algorithm, and it also relies on a predictive information of the power cycle. Numerical simulations are undertaken, showing the benefits of the proposed scheme. The proposed method is convenient to scale up for the integration of additional energy storage components or new modes of operation.Innovative UK Project KTP with Lynch Motor

Design and Experimental Validation of an Embedded Sliding Mode Controller for Voltage Regulation With SEPIC Converters

This is the author accepted manuscript. The final version is available from IEEE via the DOI in this recordThis paper addresses the challenge of regulating the output voltage in single-end primary inductor converters (SEPICs) and introduces a practical solution based on the generation of second-order suboptimal sliding modes (2-SOSM). In contrast to the common assumption of a lossless SEPIC, in this paper, a lossy SEPIC is explored. A concise mathematical representation of its model is presented, and the equilibrium point is explicitly defined. Using only the output voltage as a measurement, it is proven that the proposed 2-SOSM strategy achieves finite-time convergence of the output voltage with its reference. The proposed method effectively handles saturation constraints on the control variable, ensuring that the SEPIC duty ratio remains between 0 and 1. Furthermore, the approach proves to be robust to variations in the load resistor. The experimental analysis validates the effectiveness of our proposal and highlights its practical benefits. A comparison with a standard proportional integral control (PI) on an embedded platform underscores the superiority of the adopted approach.Innovate U

Sliding Mode Observer-Based Finite Time Control Scheme for Frequency Regulation and Economic Dispatch in Power Grids

This is the author accepted manuscript. The final version is available from Institute of Electrical and Electronics Engineers via the DOI in this record.In this brief, a novel sliding mode (SM) observer-based scheme is proposed to achieve frequency regulation and economic dispatch (ED) in power grids composed of interconnection of generators and load buses. The ED problem is addressed in two steps. Assuming only the voltage phase angles are measured, in the first step a network of heterogeneous SM observers, suitably interconnected in a distributed fashion, is created to estimate both frequency deviations and unknown power levels associated with each bus. In the second step, the observer scheme is coupled with an SM control strategy which is able to reach the optimal value of the control input in each generator bus in finite time. The scheme is assessed via the IEEE 39 bus benchmark, and a comparison with existing control methods is provided