SwePub - sökning: WFRF:(Nekouei Ehsan)

Numrering	Referens	Omslagsbild	Hitta
1.	Bassi, Germán, et al. (författare) Statistical Parameter Privacy 2020 Ingår i: Privacy in Dynamical Systems. - Singapore : Springer Nature. ; , s. 65-82 Bokkapitel (refereegranskat)abstract We investigate the problem of sharing the outcomes of a parametric source with an untrusted party while ensuring the privacy of the parameters. We propose privacy mechanisms which guarantee parameter privacy under both Bayesian statistical as well as information-theoretic privacy measures. The properties of the proposed mechanisms are investigated and the utility-privacy trade-off is analyzed.
2.	Johansson, Alexander, et al. (författare) Hub-Based Platoon Formation : Optimal Release Policies and Approximate Solutions 2024 Ingår i: IEEE transactions on intelligent transportation systems (Print). - : Institute of Electrical and Electronics Engineers (IEEE). - 1524-9050 .- 1558-0016. ; 25:6, s. 5755-5766 Tidskriftsartikel (refereegranskat)abstract This paper studies the optimal hub-based platoon formation at hubs along a highway under decentralized, distributed, and centralized policies. Hubs are locations along highways where trucks can wait for other trucks to form platoons. A coordinator at each hub decides the departure time of trucks, and the released trucks from the hub will form platoons. The problem is cast as an optimization problem where the objective is to maximize the platooning reward. We first show that the optimal release policy in the decentralized case, where the hubs do not exchange information, is to release all trucks at the hub when the number of trucks exceeds a threshold computed by dynamic programming. We develop efficient approximate release policies for the dependent arrival case using this result. To study the value of information exchange among hubs on platoon formation, we next study the distributed and centralized platoon formation policies which require information exchange among hubs. To this end, we develop receding horizon solutions for the distributed and centralized platoon formation at hubs using the dynamic programming technique. Finally, we perform a simulation study over three hubs in northern Sweden. The profits of the decentralized policies are shown to be approximately $3.5\%$ lower than the distributed policy and $8\%$ lower than the centralized release policy. This observation suggests that decentralized policies are prominent solutions for hub-based platooning as they do not require information exchange among hubs and can achieve a similar performance compared with distributed and centralized policies.
3.	Johansson, Alexander, et al. (författare) Multi-Fleet Platoon Matching : A Game-Theoretic Approach 2018 Ingår i: 2018 21ST INTERNATIONAL CONFERENCE ON INTELLIGENT TRANSPORTATION SYSTEMS (ITSC). - : IEEE. - 9781728103235 ; , s. 2980-2985 Konferensbidrag (refereegranskat)abstract We consider the platoon matching problem for a set of trucks with the same origin, but different destinations. It is assumed that the vehicles benefit from traveling in a platoon for instance through reduced fuel consumption. The vehicles belong to different fleet owners and their strategic interaction is modeled as a non-cooperative game where the vehicle actions are their departure times. Each truck has a preferred departure time and its utility function is defined as the difference between its benefit from platooning and the cost of deviating from its preferred departure time. We show that the platoon matching game is an exact potential game. An algorithm based on best response dynamics is proposed for finding a Nash equilibrium of the game. At a Nash equilibrium, vehicles with the same departure time are matched to form a platoon. Finally, the total fuel reduction at the Nash equilibrium is studied and compared with that of a cooperative matching solution where a common utility function for all vehicles is optimized.
4.	Johansson, Alexander, et al. (författare) Platoon Coordination in Large-Scale Networks : A Game Theoretic Approach 2023 Ingår i: Systems and Control. - : Springer Nature. ; , s. 79-100 Bokkapitel (övrigt vetenskapligt/konstnärligt)abstract The emerging commercial rollout of heavy-duty vehicle platooning necessitates the development of efficient platoon coordination solutions. The commercial vehicle fleet consists of vehicles owned by different transportation companies with different objectives. To capture their strategic behavior, we study platoon coordination that aims to maximize profits for individual vehicles. The interaction among vehicles is modeled as a non-cooperative game. In our cyber-physical system, we consider a large number of vehicles with fixed routes in a transportation network that can wait at hubs along their routes to form platoons. Each vehicle aims to maximize its utility function, which includes a reward for platooning and a cost for waiting. We propose open-loop coordination solutions when the vehicles decide on their waiting times at the beginning of their trips and do not update their decisions during their trips. It is shown that the corresponding game admits at least one Nash equilibrium. We also propose feedback solutions in which the vehicles are allowed to update their decisions along their routes. In a simulation study over the Swedish road network, we compare the proposed platoon coordination solutions and evaluate the benefits of non-cooperative platooning at a societal scale.
5.	Johansson, Alexander, et al. (författare) Truck Platoon Formation at Hubs : An Optimal Release Time Rule 2020 Ingår i: Ifac papersonline. - : Elsevier BV. - 2405-8963. ; , s. 15312-15318 Konferensbidrag (refereegranskat)abstract We consider a hub-based platoon coordination problem in which vehicles arrive at a hub according to an independent and identically distributed stochastic arrival process. The vehicles wait at the hub, and a platoon coordinator, at each time-step, decides whether to release the vehicles from the hub in the form of a platoon or wait for more vehicles to arrive. The platoon release time problem is modeled as a stopping rule problem wherein the objective is to maximize the average platooning benefit of the vehicles located at the hub and there is a cost of having vehicles waiting at the hub. We show that the stopping rule problem is monotone and the optimal platoon release time policy will therefore be in the form of a one time-step look-ahead rule. The performance of the optimal release rule is numerically compared with (i) a periodic release time rule and (ii) a non-causal release time rule where the coordinator knows all the future realizations of the arrival process. Our numerical results show that the optimal release time rule achieves a close performance to that of the non-causal rule and outperforms the periodic rule, especially when the arrival rate is low.
6.	Masoumzadeh, Amin, et al. (författare) Impact of Optimal Storage Allocation on Price Volatility in Energy-Only Electricity Markets 2018 Ingår i: IEEE Transactions on Power Systems. - : IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC. - 0885-8950 .- 1558-0679. ; 33:2, s. 1903-1914 Tidskriftsartikel (refereegranskat)abstract Recent studies show that the fast growing expansion of wind power generation may lead to extremely high levels of price volatility in wholesale electricity markets. Storage technologies, regardless of their specific forms, e.g., pump-storage hydro, large-scale, or distributed batteries, are capable of alleviating the extreme price volatility levels due to their energy usage time shifting, fast-ramping, and price arbitrage capabilities. In this paper, we propose a stochastic bilevel optimization model to find the optimal nodal storage capacities required to achieve a certain price volatility level in a highly volatile energy-only electricity market. The decision on storage capacities is made in the upper level problem and the operation of strategic/regulated generation, storage, and transmission players is modeled in the lower level problem using an extended stochastic (Bayesian) Cournot-based game. The South Australia (SA) electricity market, which has recently experienced high levels of price volatility, and a 30-bus IEEE system are considered as the case studies. Our numerical results indicate that 50% price volatility reduction in the SA electricity market can be achieved by installing either 430-MWh regulated storage or 530-MWh strategic storage. In other words, regulated storage firms are more efficient in reducing the price volatility than strategic storage firms.
7.	Masoumzadeh, Amin, et al. (författare) Wind Versus Storage Allocation for Price Management in Wholesale Electricity Markets 2020 Ingår i: IEEE Transactions on Sustainable Energy. - : IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC. - 1949-3029 .- 1949-3037. ; 11:2, s. 817-827 Tidskriftsartikel (refereegranskat)abstract This paper investigates the impacts of installing regulated wind and electricity storage on average price and price volatility in electricity markets. A stochastic bi-level optimization model is developed, which computes the optimal allocation of new wind and battery capacities, by minimizing a weighted sum of the average market price and price volatility. A fixed budget is allocated on wind and battery capacities in the upper-level problem. The operation of strategic/regulated generation, storage, and transmission players is simulated in the lower-level problem using a stochastic (Bayesian) Cournot-based game model. Australia's national electricity market, which is experiencing occasional price peaks, is considered as the case study. Our simulation results quantitatively illustrate that the regulated wind is more efficient than storage in reducing the average price, while the regulated storage more effectively reduces the price volatility. According to our numerical results, the storage-only solution reduces the average price at most by 9.4%, and the wind-only solution reduces the square root of price volatility at most by 39.3%. However, an optimal mixture of wind and storage can reduce the mean price by 17.6% and the square root of price volatility by 48.1%. It also increases the consumer surplus by 1.52%. Moreover, the optimal mixture of wind and storage is a profitable solution unlike the storage-only solution.
8.	Nekouei, Ehsan, et al. (författare) A Randomized Filtering Strategy Against Inference Attacks on Active Steering Control Systems 2022 Ingår i: IEEE Transactions on Information Forensics and Security. - : Institute of Electrical and Electronics Engineers (IEEE). - 1556-6013 .- 1556-6021. ; 17, s. 16-27 Tidskriftsartikel (refereegranskat)abstract In this paper, we develop a framework against inference attacks aimed at inferring the values of the controller gains of an active steering control system (ASCS). We first show that an adversary with access to the shared information by a vehicle, via a vehicular ad hoc network (VANET), can reliably infer the values of the controller gains of an ASCS. This vulnerability may expose the driver as well as the manufacturer of the ASCS to severe financial and safety risks. To protect controller gains of an ASCS against inference attacks, we propose a randomized filtering framework wherein the lateral velocity and yaw rate states of a vehicle are processed by a filter consisting of two components: a nonlinear mapping and a randomizer. The randomizer randomly generates a pair of pseudo gains which are different from the true gains of the ASCS. The nonlinear mapping performs a nonlinear transformation on the lateral velocity and yaw rate states. The nonlinear transformation is in the form of a dynamical system with a feedforward-feedback structure which allows real-time and causal implementation of the proposed privacy filter. The output of the filter is then shared via the VANET. The optimal design of randomizer is studied under a privacy constraint that determines the protection level of controller gains against inference attacks, and is in terms of mutual information. It is shown that the optimal randomizer is the solution of a convex optimization problem. By characterizing the distribution of the output of the filter, it is shown that the statistical distribution of the filter's output depends on the pseudo gains rather than the true gains. Using information-theoretic inequalities, we analyze the inference ability of an adversary in estimating the control gains based on the output of the filter. Our analysis shows that the performance of any estimator in recovering the controller gains of an ASCS based on the output of the filter is limited by the privacy constraint. The performance of the proposed privacy filter is compared with that of an additive noise privacy mechanism. Our numerical results show that the proposed privacy filter significantly outperforms the additive noise mechanism, especially in the low distortion regime.
9.	Nekouei, Ehsan, et al. (författare) Distributed cognitive multiple access networks : Power control, scheduling and multiuser diversity 2013 Konferensbidrag (refereegranskat)
10.	Nekouei, Ehsan, et al. (författare) Impact of quantized inter-agent communications on game-theoretic and distributed optimization algorithms 2018 Ingår i: Uncertainty in Complex Networked Systems. - Cham : Birkhauser. ; , s. 501-532 Bokkapitel (refereegranskat)abstract Quantized inter-agent communications in game-theoretic and distributed optimization algorithms generate uncertainty that affects the asymptotic and transient behavior of such algorithms. This chapter uses the information-theoretic notion of differential entropy power to establish universal bounds on the maximum exponential convergence rates of primal-dual and gradient-based Nash seeking algorithms under quantized communications. These bounds depend on the inter-agent data rate and the local behavior of the agents’ objective functions, and are independent of the quantizer structure. The presented results provide trade-offs between the speed of exponential convergence, the agents’ objective functions, the communication bit rates, and the number of agents and constraints. For the proposed Nash seeking algorithm, the transient performance is studied and an upper bound on the average time required to settle inside a specified ball around the Nash equilibrium is derived under uniform quantization. Furthermore, an upper bound on the probability that the agents’ actions lie outside this ball is established. This bound decays double exponentially with time.
11.	Nekouei, Ehsan, et al. (författare) Information-theoretic approaches to privacy in estimation and control 2019 Ingår i: Annual Reviews in Control. - : PERGAMON-ELSEVIER SCIENCE LTD. - 1367-5788 .- 1872-9088. ; 47, s. 412-422 Forskningsöversikt (refereegranskat)abstract Network control systems (NCSs) heavily rely on information and communication technologies for sharing information between sensors and controllers as well as controllers and actuators. When estimation, control or actuation tasks in a NCS are performed by an untrusted party, sharing information might result in the leakage of private information. The current paper reviews some of the recent results on the privacy-aware decision-making problems in NCSs. In particular, we focus on static and dynamic decision-making problems wherein privacy is measured using information-theoretic notions. We also review the applications of these problems in smart buildings and smart grids.
12.	Nekouei, Ehsan, et al. (författare) Nash Equilibrium Approximation under Communication and Computation Constraints in Large-Scale Non-cooperative Games 2017 Ingår i: 2017 Asian Control Conference, ASCC 2017. - : Institute of Electrical and Electronics Engineers (IEEE). - 9781509015733 ; , s. 2083-2088 Konferensbidrag (refereegranskat)abstract This paper studies the problem of Nash equilibrium approximation in large-scale heterogeneous (static) mean-field games under communication and computation constraints. A deterministic mean-field game is considered in which the utility function of each agent depends on its action, the average of other agents' actions (called the mean variable of that agent) and a deterministic parameter. It is shown that the equilibrium mean variables of all agents converge uniformly to a constant, called asymptotic equilibrium mean (AEM), as the number of agents tends to infinity. Next, the problem of approximating the AEM at a processing center under communication and computation constraints is studied. Three approximation methods are proposed to substantially reduce the communication and computation costs of approximating AEM at the processing center. In particular, a quantized communication scheme is considered which significantly reduces the cost of transmitting agents' parameters to the processing center while a certain accuracy level for approximating AEM at the processing center is guaranteed. The accuracy of the proposed approximation methods is analyzed and illustrated through numerical examples.
13.	Nekouei, Ehsan, et al. (författare) Optimal Decision Fusion Under Order Effects 2019 Ingår i: IFAC PAPERSONLINE. - : ELSEVIER SCIENCE BV. - 2405-8963. ; , s. 53-60 Konferensbidrag (refereegranskat)abstract This paper studies an optimal decision fusion problem with a group of human decision makers when an order effect is present. The order effect refers to situations wherein the process of decision making by a human is affected by the order of decisions. In our set-up, all human decision makers, called observers, receive the same data which is generated by a common but unknown hypothesis. Then, each observer independently generates a sequence of decisions which are modeled by employing non-commutative probabilistic models of the data and their relation to the unknown hypothesis. The use of non-commutative probability models is motivated by recent psychological studies which indicate that these non-commutative probability models are more suitable for capturing the order effect in human decision making, compared with the classical probability model. A central decision maker (CDM) receives (possibly a subset of) the observers' decisions and decides on the true hypothesis. The considered problem becomes an optimal decision fusion problem with observations modeled using a non-commutative (Von Neumann) probability model. The structure of the optimal decision rule at the CDM is studied under two scenarios. In the first scenario, the CDM receives the entire history of the observers' decisions whereas in the second scenario, the CDM receives only the last decision of each observer. The perfromance of the optimal fusion rule is numerically evaluated and compared with the optimal fusion rule derived when using a classical probability model.
14.	Nekouei, Ehsan, et al. (författare) Power control and asymptotic throughput analysis for the distributed cognitive uplink 2014 Ingår i: IEEE Transactions on Communications. - 0090-6778 .- 1558-0857. ; 64:1, s. 41-58 Tidskriftsartikel (refereegranskat)abstract This paper studies optimum power control and sum-rate scaling laws for the distributed cognitive uplink. It is first shown that the optimum distributed power control policy is in the form of a threshold based water-filling power control. Each secondary user executes the derived power control policy in a distributed fashion by using local knowledge of its direct and interference channel gains such that the resulting aggregate (average) interference does not disrupt primary's communication. Then, the tight sum-rate scaling laws are derived as a function of the number of secondary users N under the optimum distributed power control policy. The fading models considered to derive sum-rate scaling laws are general enough to include Rayleigh, Rician and Nakagami fading models as special cases. When transmissions of secondary users are limited by both transmission and interference power constraints, it is shown that the secondary network sum-rate scales according to 1/en(h) log log (N), where n(h) is a parameter obtained from the distribution of direct channel power gains. For the case of transmissions limited only by interference constraints, on the other hand, the secondary network sum-rate scales according to 1/e gamma(g) log (N), where gamma(g) is a parameter obtained from the distribution of interference channel power gains. These results indicate that the distributed cognitive uplink is able to achieve throughput scaling behavior similar to that of the centralized cognitive uplink up to a pre-log multiplier 1/e, whilst primary's quality-of-service requirements are met. The factor 1/e can be interpreted as the cost of distributed implementation of the cognitive uplink.
15.	Nekouei, Ehsan, et al. (författare) Privacy of Information Sharing Schemes in a Cloud-based Multi-sensor Estimation Problem 2018 Ingår i: 2018 Annual American Control Conference (ACC). - : Institute of Electrical and Electronics Engineers (IEEE). ; , s. 998-1002 Konferensbidrag (refereegranskat)abstract In this paper, we consider a multi-sensor estimation problem wherein each sensor collects noisy information about its local process, which is only observed by that sensor, and a common process, which is simultaneously observed by all sensors. The objective is to assess the privacy level of (the local process of) each sensor while the common process is estimated using cloud computing technology. The privacy level of a sensor is defined as the conditional entropy of its local process given the shared information with the cloud. Two information sharing schemes are considered: a local scheme, and a global scheme. Under the local scheme, each sensor estimates the common process based on its measurement and transmits its estimate to a cloud. Under the global scheme, the cloud receives the sum of the sensors' measurements. It is shown that, in the local scheme, the privacy level of each sensor is always above a certain level which is characterized using Shannon's mutual information. It is also proved that this result becomes tight as the number of sensors increases. We also show that the global scheme is asymptotically private, i.e., the privacy loss of the global scheme decreases to zero at the rate of O(1/M) where M is the number of sensors.
16.	Nekouei, Ehsan, et al. (författare) Throughput Analysis for the Cognitive Uplink Under Limited Primary Cooperation 2016 Ingår i: IEEE Transactions on Communications. - 0090-6778 .- 1558-0857. ; 64:7, s. 2780-2796 Tidskriftsartikel (refereegranskat)abstract This paper studies the achievable throughput performance of the cognitive uplink under a limited primary cooperation scenario wherein the primary base station cannot feed back all interference channel gains to the secondary base station. To cope with the limited primary cooperation, we propose a feedback protocol called K-out-of-N feedback protocol, in which the primary base station feeds back only the K-N smallest interference channel gains, out of N of them, to the secondary base station. We characterize the throughput performance under the K-out-of-N feedback protocol by analyzing the achievable multiuser diversity gains (MDGs) in cognitive uplinks for three different network types. Our results show that the proposed feedback mechanism is asymptotically optimum for interference-limited (IL) and individual-power-and-interference-limited (IPIL) networks for a fixed positive K-N. It is further shown that the secondary network throughput in the IL and IPIL networks (under both the full and limited cooperation scenarios) logarithmically scales with the number of users in the network. In total-power-and-interference-limited (TPIL) networks, on the other hand, the K-out-of-N feedback protocol is asymptotically optimum for K-N = N-delta, where delta is an element of (0, 1). We also show that, in TPIL networks, the secondary network throughput under both the limited and full cooperation scales logarithmically double with the number of users in the network. These results indicate that the cognitive uplink can achieve the optimum MDG even with limited cooperation from the primary network. They also establish the dependence of pre-log throughput scaling factors on the distribution of fading channel gains for different network types.
17.	Pirani, Mohammad, et al. (författare) A game-theoretic framework for security-aware sensor placement problem in networked control systems 2019 Ingår i: Proceedings of the American Control Conference. - : Institute of Electrical and Electronics Engineers (IEEE). - 9781538679265 ; , s. 114-119 Konferensbidrag (refereegranskat)abstract This paper studies the sensor placement problem in a networked control system for improving its security against cyber-physical attacks. The problem is formulated as a zero-sum game between an attacker and a detector. The attacker's decision is to select f nodes of the network to attack whereas the detector's decision is to place f sensors to detect the presence of the attack signals. In our formulation, the attacker minimizes its visibility, defined as the system L2 gain from the attack signals to the deployed sensors' outputs, and the detector maximizes the visibility of the attack signals. The equilibrium strategy of the game determines the optimal locations of the sensors. The existence of Nash equilibrium for the attacker-detector game is studied when the underlying connectivity graph is a directed or an undirected tree. When the game does not admit a Nash equilibrium, it is shown that the Stackelberg equilibrium of the game, with the detector as the game leader, can be computed efficiently. Our results show that, under the optimal sensor placement strategy, an undirected topology provides a higher security level for a networked control system compared with its corresponding directed topology.
18.	Pirani, Mohammad, et al. (författare) A Game-Theoretic Framework for Security-Aware Sensor Placement Problem in Networked Control Systems 2022 Ingår i: IEEE Transactions on Automatic Control. - : Institute of Electrical and Electronics Engineers (IEEE). - 0018-9286 .- 1558-2523. ; 67:7, s. 3699-3706 Tidskriftsartikel (refereegranskat)abstract This article studies the sensor placement problem in a leader-follower networked control system for improving its security against cyber-physical attacks. In a zero-sum game, the attacker selects f nodes of the network to attack, and the detector places f sensors to detect the presence of the attack signals. In our formulation, the attacker's objective is to have a large impact on a target node in the network while being as little visible as possible to the detector. The detector, however, seeks to maximize the visibility of the attack signals. The effects of the attack signals on both the target node and the detector node are captured via the system L-2 gain from the attack signals to the target node and deployed sensors' outputs, respectively. The equilibrium strategy of the game determines the optimal locations of the sensors. The existence of Nash equilibrium for the single-attack single-sensor case is studied when the underlying connectivity graph is a directed or an undirected tree. We show that, under the optimal sensor placement strategy, an undirected topology provides a higher security level for a networked control system compared to its corresponding directed topology. For the multiple-attack multiple-sensor case, we show that the game does not necessarily admit a Nash equilibrium and introduce a Stackelberg game approach, where the detector acts as the leader. Finally, these results are used to study the sensor placement problem in a vehicle platooning application in the presence of bias injection attacks.
19.	Pirani, Mohammad, et al. (författare) Design of Attack-Resilient Consensus Dynamics : A Game-Theoretic Approach 2019 Ingår i: Proceedings 2019 18th European Control Conference (ECC). - : IEEE. - 9783907144008 ; , s. 2227-2232 Konferensbidrag (refereegranskat)abstract We propose a game-theoretic framework for improving the resilience of multi-agent consensus dynamics in the presence of a strategic attacker. In this game, the attacker selects a set of network nodes to inject the attack signals. The attacker's objective is to minimize the required energy for steering the consensus towards its desired direction. This energy is captured by the trace of controllability Gramian of the system when the input is the attack signal. The defender improves the resilience of dynamics by adding self-feedback loops to certain nodes of the system and its objective is to maximize the trace of controllability Gramian. The Stackelberg equilibrium of the game is studied with the defender as the game leader. When the underlying network topology is a tree and the defender can select only one node, we show that the optimal strategy of the defender is determined by a specific distance-based network centrality measure, called network's f-center. In addition, we show that the degree-based centralities solutions may lead to undesirable payoffs for the defender. At the end, we discuss the case of multiple attack and defense nodes on general graphs.
20.	Stefansson, Elis, et al. (författare) Modeling the decision-making in human driver overtaking 2020 Ingår i: IFAC PAPERSONLINE. - : Elsevier BV. - 2405-8963. ; , s. 15338-15345 Konferensbidrag (refereegranskat)abstract We propose models for the decision-making process of human drivers in an overtaking scenario. First, we mathematically formalize the overtaking problem as a decision problem with perceptual uncertainty. Then, we propose and numerically analyze risk-agnostic and risk-aware decision models, which are able to judge whether an overtaking is desirable or not. We show how a driver's decision-making time and confidence level can be primarily characterized through two model parameters, which collectively represent human risk-taking behavior. We detail an experimental testbed for evaluating the decision-making process in the overtaking scenario. Finally, we present some preliminary experimental results from two human drivers.
21.	Tanaka, Takashi, et al. (författare) Linearly Solvable Mean-Field Road Traffic Games 2018 Ingår i: 56th Annual Allerton Conference on Communication, Control, and Computing. - : IEEE. - 9781538665961 ; , s. 283-289 Konferensbidrag (refereegranskat)abstract We analyze the behavior of a large number of strategic drivers traveling er an urban traffic network using the mean-field game framework. We sume an incentive mechanism for congestion mitigation under which each iver selecting a particular route is charged a tax penalty that is fine in the logarithm of the number of agents selecting the same ute. We show that the mean-field approximation of such a rge-population dynamic game leads to the so-called linearly solvable rkov decision process, implying that an open-loop epsilon-Nash uilibrium of the original game can be found simply by solving a nite-dimensional linear system.
22.	Tanaka, Takashi, et al. (författare) Linearly Solvable Mean-Field Traffic Routing Games 2021 Ingår i: IEEE Transactions on Automatic Control. - : Institute of Electrical and Electronics Engineers (IEEE). - 0018-9286 .- 1558-2523. ; 66:2, s. 880-887 Tidskriftsartikel (refereegranskat)abstract We consider a dynamic traffic routing game over an urban road network involving a large number of drivers in which each driver selecting a particular route is subject to a penalty that is affine in the logarithm of the number of drivers selecting the same route. We show that the mean-field approximation of such a game leads to the so-called linearly solvable Markov decision process, implying that its mean-field equilibrium (MFE) can be found simply by solving a finite-dimensional linear system backward in time. Based on this backward-only characterization, it is further shown that the obtained MFE has the notable property of strong time-consistency. A connection between the obtained MFE and a particular class of fictitious play is also discussed.
23.	Umsonst, David, et al. (författare) On the confidentiality of linear anomaly detector states 2019 Ingår i: Proceedings of the American Control Conference. - : Institute of Electrical and Electronics Engineers (IEEE). - 9781538679265 ; , s. 397-403 Konferensbidrag (refereegranskat)abstract A malicious attacker with access to the sensor channel in a feedback control system can severely affect the physical system under control, while simultaneously being hard to detect. A properly designed anomaly detector can restrict the impact of such attacks, however. Anomaly detectors with an internal state (stateful detectors) have gained popularity because they seem to be able to mitigate these attacks more than detectors without a state (stateless detectors). In the analysis of attacks against control systems with anomaly detectors, it has been assumed that the attacker has access to the detector's internal state, or designs its attack such that it is not detected regardless of the detector's state. In this paper, we show how an attacker can realize the first case by breaking the confidentiality of a stateful detector state evolving with linear dynamics, while remaining undetected and imitating the statistics of the detector under nominal conditions. The realization of the attack is posed in a convex optimization framework using the notion of Kullback-Leibler divergence. Further, the attack is designed such that the maximum mean estimation error of the Kalman filter is maximized at each time step by exploiting dual norms. A numerical example is given to illustrate the results.
24.	Umsonst, David, et al. (författare) On the confidentiality of linear anomaly detector states 2019 Ingår i: 2019 American Control Conference (ACC). - 9781538679265 - 9781538679272 - 9781538679289 - 9781538679012 ; , s. 397-403 Konferensbidrag (refereegranskat)abstract A malicious attacker with access to the sensor channel in a feedback control system can severely affect the physical system under control, while simultaneously being hard to detect. A properly designed anomaly detector can restrict the impact of such attacks, however. Anomaly detectors with an internal state (stateful detectors) have gained popularity because they seem to be able to mitigate these attacks more than detectors without a state (stateless detectors). In the analysis of attacks against control systems with anomaly detectors, it has been assumed that the attacker has access to the detector's internal state, or designs its attack such that it is not detected regardless of the detector's state. In this paper, we show how an attacker can realize the first case by breaking the confidentiality of a stateful detector state evolving with linear dynamics, while remaining undetected and imitating the statistics of the detector under nominal conditions. The realization of the attack is posed in a convex optimization framework using the notion of Kullback-Leibler divergence. Further, the attack is designed such that the maximum mean estimation error of the Kalman filter is maximized at each time step by exploiting dual norms. A numerical example is given to illustrate the results.
25.	Wei, Jieqiang, et al. (författare) Steady-state analysis of a human-social behavior model : A neural-cognition perspective 2019 Ingår i: Proceedings of the American Control Conference. - : Institute of Electrical and Electronics Engineers (IEEE). - 9781538679265 ; , s. 199-204 Konferensbidrag (refereegranskat)abstract We consider an extension of the Rescorla-Wagner model which bridges the gap between conditioning and learning on a neural-cognitive, individual psychological level, and the social population level. In this model, the interaction among individuals is captured by a Markov process. The resulting human-social behavior model is a recurrent iterated function system which behaves differently from the classical Rescorla-Wagner model due to randomness. A sufficient condition for the convergence of the forward process starting with arbitrary initial distribution is provided. Furthermore, the ergodicity properties of the internal states of agents in the proposed model are studied.
26.	Yoo, Jaehyun, et al. (författare) Event-based Observer and MPC with Disturbance Attenuation using ERM Learning 2018 Ingår i: 2018 European Control Conference, ECC 2018. - : Institute of Electrical and Electronics Engineers (IEEE). - 9783952426982 ; , s. 1894-1899 Konferensbidrag (refereegranskat)abstract This paper presents a learning-based approach for disturbance attenuation for a non-linear dynamical system with event-based observer and model predictive control (MPC). Using the empirical risk minimization (ERM) method, we can obtain a learning error bound which is function of the number of samples, learning parameters, and model complexity. It enables us to analyze the closed-loop stability in terms of the learning property, where the state estimation error by the ERM learning is guaranteed to be bounded. Simulation results underline the learning's capability, the control performance and the event-triggering efficiency in comparison to the conventional event-triggered control scheme.

Skapa referenser, mejla, bekava och länka

Länka till träfflistan

Träfflista för sökning "WFRF:(Nekouei Ehsan) "

Avgränsa träffmängd

År