Faglige interesser
 CyberPhysical systems
 Networked control
 Connected and intelligent transportation systems
 Hybrid systems: modelling, simulation, design and validation
Undervisning
ITD25018 Teknologiprosjekt
<Lenke til studieprogram/emne>
...
Google scholar page
https://scholar.google.com/citations?user=VrWL7wAAAAJ&hl=no&oi=ao
Prosjekter
CriSp (Forsknigsrådet): Finding a CRItical SPeed function ahead of a road section for vehicles in motion
SafeSmart (KK stiftelsen)
Programvare
MATLAB code for simulating a class of switched affine systems
Samarbeid
Forskergrupper
Emneord:
CyberPhysical Systems,
Networked control,
Hybrid systems
Publikasjoner

Bochaova, Irina; Kudryashov, Boris D.; Rabi, Maben; Lyamin, Nikita; Dankers, Wouter; Erik, Frick & Vinel, Alexey (2019). Characterizing Packet Losses in Vehicular Networks. IEEE Transactions on Vehicular Technology.
ISSN 00189545.
68(9), s 8347 8358 . doi:
10.1109/TVT.2019.2930689
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To enable testing and performance evaluation of new connected and autonomous driving functions, it is important to characterize packet losses caused by degradation in vehicular (V2X) communication channels. In this paper we suggest an approach to constructing packet loss models based on the socalled PseudoMarkov chains (PMC). The PMCbased model needs only short training sequences, has low computational complexity, and yet provides more precise approximations than known techniques. We show how to learn PMC models from either empirical records of packet receptions, or from analytical models of fluctuations in the received signal strength. In particular, we validate our approach by applying it on: 1) V2X packet reception data collected from an active safety test run, which used the LTE network of the AstaZero automotive testing site in Sweden, and 2) variants of the Rician fading channel models corresponding to two models of correlations of packet losses. We also show that initializing the BaumWelch algorithm with a second order PMC model leads to a high accuracy model.

Bocharova, Irina E.; Kudryashov, Boris D.; Lyamin, Nikita; Frick, Erik; Rabi, Maben & Vinel, Alexey (2019). Low Delay InterPacket Coding in Vehicular Networks. Future Internet.
ISSN 19995903.
11(10) . doi:
10.3390/fi11100212
Fulltekst i vitenarkiv.
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In Cooperative Intelligent Transportation Systems (CITSs), vehicles need to wirelessly connect with Roadside units (RSUs) over limited durations when such pointtopoint connections are possible. One example of such communications is the downloading of maps to the CITS vehicles. Another example occurs in the testing of CITS vehicles, where the tested vehicles upload trajectory records to the roadside units. Because of realtime requirements, and limited bandwidths, data are sent as User Datagram Protocol (UDP) packets. We propose an interpacket error control coding scheme that improves the recovery of data when some of these packets are lost; we argue that the coding scheme has to be one of convolutional coding. We measure performance through the session averaged probability of successfully delivering groups of packets. We analyze two classes of convolution codes and propose a lowcomplexity decoding procedure suitable for network applications. We conclude that Reed–Solomon convolutional codes perform better than Wyner–Ash codes at the cost of higher complexity. We show this by simulation on the memoryless binary erasure channel (BEC) and channels with memory, and through simulations of the IEEE 802.11p DSRC/ITSG5 network at the CITS test track AstaZero.

Bocharova, Irina E.; Kudryashov, Boris D.; Rabi, Maben; Lyamin, Nikita; Dankers, Wouter; Frick, Erik & Vinel, Alexey (2019). Modeling Packet Losses in Communication Networks. IEEE International Symposium on Information Theory. Proceedings.
ISSN 21578095.
s 1012 1016 . doi:
10.1109/ISIT.2019.8849400
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An approach to constructing discrete models of packet losses suitable for a wide variety of communication network applications is studied. It is based on estimating parameters of probabilistic automata described via socalled pseudoMarkov chains. The new technique is applied both to approximating a discrete time analog process at the output of known channel models and to the experimental data stream. Comparison of models is performed by computing probabilities of more than m losses out of n transmitted packets (P (≥ m, n)). It is shown that for the Rician fading channel with exponential correlation and correlation determined by a Bessel filter, the obtained ranktwo and rankthree discrete modes, respectively, provide high accuracy coincidence of P (≥ m, n) performances. The rankthree discrete model computed on the experimental data stream obtained from the LTE network provides significantly better approximation of P (≥ m, n) performance than that obtained by the BaumWelch algorithm.

Rabi, Maben; Ramesh, Chithrupa & Karl, Johansson (2016). Separated Design of Encoder and Controller for Networked Linear Quadratic Optimal Control. SIAM Journal of Control and Optimization.
ISSN 03630129.
54(2), s 662 689 . doi:
10.1137/14M0970987
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For a networked control system, we consider the problem of encoder and controller design. We study a discretetime linear plant with a finite horizon performance cost, comprising a quadratic function of the states and controls, and an additive communication cost. We study separation in design of the encoder and controller, along with related closedloop properties such as the dual effect and certainty equivalence. The encoder outputs are quantized samples, but our results also apply to two other formats for encoder outputs: realvalued samples at eventtriggered times, and realvalued samples over additive noise channels. If the controller and encoder are dynamic, then we show that the performance cost is minimized by a separated design: the controls are updated at each time instant as per a certainty equivalence law, and the encoder is chosen to minimize an aggregate quadratic distortion of the estimation error. This separation is shown to hold even though a dual effect is present in the closedloop system. We also show that this separated design need not be optimal when the controller or encoder are to be chosen from within restricted classes.

Rabi, Maben; George, Moustakides & Baras, John (2012). Adaptive Sampling for Linear State Estimation. SIAM Journal of Control and Optimization.
ISSN 03630129.
50(2), s 672 702 . doi:
10.1137/090757125
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When a sensor has continuous measurements but sends occasional messages over a data network to a supervisor which estimates the state, the available packet rate fixes the achievable quality of state estimation. When such rate limits turn stringent, the sensor's messaging policy should be designed anew. What are good causal messaging policies? What should message packets contain? What is the lowest possible distortion in a causal estimate at the supervisor? Is Delta sampling better than periodic sampling? We answer these questions for a Markov state process under an idealized model of the network and the assumption of perfect state measurements at the sensor. If the state is a scalar, or a vector of low dimension, then we can ignore sample quantization. If in addition we can ignore jitter in the transmission delays over the network, then our search for efficient messaging policies simplifies. First, each message packet should contain the value of the state at that time. Thus a bound on the number of data packets becomes a bound on the number of state samples. Second, the remaining choice in messaging is entirely about the times when samples are taken. For a scalar, linear diffusion process, we study the problem of choosing the causal sampling times that will give the lowest aggregate squared error distortion. We stick to finite horizons and impose a hard upper bound N on the number of allowed samples. We cast the design as a problem of choosing an optimal sequence of stopping times. We reduce this to a nested sequence of problems, each asking for a single optimal stopping time. Under an unproven but natural assumption about the leastsquare estimate at the supervisor, each of these single stopping problems are of standard form. The optimal stopping times are random times when the estimation error exceeds designed envelopes. For the case where the state is a Brownian motion, we give analytically: the shape of the optimal sampling envelopes, the shape of the envelopes under optimal Delta sampling, and their performances. Surprisingly, we find that Delta sampling performs badly. Hence, when the rate constraint is a hard limit on the number of samples over a finite horizon, we should not use Delta sampling.

Rabi, Maben; Stabellini, Luca; Proutiere, Alexandre & Johansson, Mikael (2010). Networked estimation under contention‐based medium access. International Journal of Robust and Nonlinear Control.
ISSN 10498923.
20(2), s 140 155 . doi:
10.1002/rnc.1459
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This paper studies networked estimation over a communication channel shared by a contention‐based medium access protocol. A collection of N identical and physically decoupled scalar systems are sampled without sensor noise and transmitted over a common channel, using a contention‐based medium access mechanism. We first carry out a calculation of the average distortion in estimation with irregular samples. Given the rate of packet generation at sensors, we characterize the traffic characteristics of the some contention‐based MAC schemes. This lets us derive the statistics of inter‐arrival times which in turn allows us to compute the packet loss rates and also the statistics of delay within a sample period. Using these results, we track the estimation performance as the sample generation rate and the number of contending nodes are varied. We provide a heuristic rule‐of‐thumb for choosing the sampling interval which minimizes the average distortion. By combining the network traffic characterization with that of the estimation performance, we show this rule performs pretty well. Carrying along the same lines, we are able to compute the scaling limits of estimation performance with respect to the number of contending nodes.

Johansson, Björn; Rabi, Maben & Johansson, Mikael (2009). A Randomized Incremental Subgradient Method for Distributed Optimization in Networked Systems. SIAM Journal on Optimization.
ISSN 10526234.
20(3), s 1157 1170 . doi:
10.1137/08073038X
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We present an algorithm that generalizes the randomized incremental subgradient method with fixed stepsize due to Nedić and Bertsekas [SIAM J. Optim., 12 (2001), pp. 109–138]. Our novel algorithm is particularly suitable for distributed implementation and execution, and possible applications include distributed optimization, e.g., parameter estimation in networks of tiny wireless sensors. The stochastic component in the algorithm is described by a Markov chain, which can be constructed in a distributed fashion using only local information. We provide a detailed convergence analysis of the proposed algorithm and compare it with existing, both deterministic and randomized, incremental subgradient methods.
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Rabi, Maben (2020). Piecewise analytic trajectory computation for polyhedral switching between stable affine systems.
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Our problem is to compute trajectories of a hybrid system that switches between stable affine ODEs, with switching triggered by hyperplane crossings. Instead of integrating over relatively short time steps, we propose to analytically calculate the affine ODE trajectories between switching times. Our algorithm computes the switching times themselves by Chebyshev interpolation of the analytic trajectory pieces, and polynomial root finding. We shrink the interpolation time intervals using bounds on the times needed by the affine ODE trajectories to enter Lyapunov sublevel sets. Based on the Chebfun package, we give a MATLAB implementation of our algorithm. We find that this implementation simulates Relay feedback systems as accurately and sometimes faster than conventional algorithms.

Bocharova, Irina E.; Kudryashov, Boris D.; Rabi, Maben; Lyamin, Nikita; Dankers, Wouter; Frick, Erik & Vinel, Alexey (2019). Modeling Packet Losses in Communication Networks.
Vis sammendrag
An approach to constructing discrete models of packet losses suitable for a wide variety of communication network applications is studied. It is based on estimating parameters of probabilistic automata described via socalled pseudoMarkov chains. The new technique is applied both to approximating a discrete time analog process at the output of known channel models and to the experimental data stream. Comparison of models is performed by computing probabilities of more than m losses out of n transmitted packets (P (≥ m, n)). It is shown that for the Rician fading channel with exponential correlation and correlation determined by a Bessel filter, the obtained ranktwo and rankthree discrete modes, respectively, provide high accuracy coincidence of P (≥ m, n) performances. The rankthree discrete model computed on the experimental data stream obtained from the LTE network provides significantly better approximation of P (≥ m, n) performance than that obtained by the BaumWelch algorithm.

Haugen, Øystein & Rabi, Maben (2019). Internet of Things.
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Publisert 13. juni 2019 14:52
 Sist endret 8. feb. 2020 09:34