| 1. |
- Chen, Jianqi, et al.
(författare)
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Geometrical Characterization Of Sensor Placement For Cone-Invariant And Multi-Agent Systems Against Undetectable Zero-Dynamics Attacks\Ast
- 2022
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Ingår i: SIAM Journal of Control and Optimization. - : Society for Industrial & Applied Mathematics (SIAM). - 0363-0129 .- 1095-7138. ; 60:2, s. 890-916
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Tidskriftsartikel (refereegranskat)abstract
- Undetectable attacks are an important class of malicious attacks threatening the security of cyber-physical systems, which can modify a system's state but leave the system output measurements unaffected and hence cannot be detected from the output. This paper studies undetectable attacks on cone-invariant systems and multi-agent systems. We first provide a general characterization of zero-dynamics attacks, which characterizes fully undetectable attacks targeting the nonminimum phase zeros of a system. This geometrical characterization makes it possible to develop a defense strategy seeking to place a minimal number of sensors to detect and counter the zero-dynamics attacks on the system's actuators. The detect and defense scheme amounts to computing a set containing potentially vulnerable actuator locations and nodes and a defense union for feasible placement of sensors based on the geometrical properties of the cones under consideration.
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| 2. |
- Chen, J., et al.
(författare)
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Protecting Positive and Second-Order Systems against Undetectable Attacks
- 2017
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Ingår i: IFAC-PapersOnLine. - : Elsevier. - 2405-8963. ; 50:1, s. 8373-8378
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Tidskriftsartikel (refereegranskat)abstract
- Undetectable attacks in security studies of cyber-physical systems render the measurements of the system equal to a possible physical response. In this paper, we investigate defense strategies against the undetectable single-attack for positive systems and second-order systems, which both can be reinterpreted in terms of graphs with nodes and edges, while the undetectable attack is added through one of the nodes. We show that an arbitrary placement of a sensor prevents undetectable single-attack for these classes of systems. It is worth emphasising that we do not need to measure at the corrupted node to prevent the undetectable single-attack, but can measure at any node. The defense strategy is of a low complexity and can be readily implemented.
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| 3. |
- Chen, Xiaochang, et al.
(författare)
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Automatic Overtaking on Two-way Roads with Vehicle Interactions Based on Proximal Policy Optimization
- 2021
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Ingår i: 2021 32nd IEEE Intelligent Vehicles Symposium (IV). - : Institute of Electrical and Electronics Engineers (IEEE). ; , s. 1057-1064
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Konferensbidrag (refereegranskat)abstract
- Overtaking the lead vehicle on two-way roads in the presence of several oncoming vehicles is a complex task for autonomous vehicles. In this paper, we formulate the overtaking behavior of an ego vehicle based on a deep reinforcement learning (DRL) method. First, a two-way urban road is created, wherein the ego vehicle aims to reach the destination safely and efficiently while considering multiple traffic participants. We use different intelligent driver model (IDM) parameters to account for different drivers' habits. Furthermore, we introduce different responses of other vehicles when the ego vehicle takes overtaking maneuver. Then, a hierarchical control framework is proposed to manage vehicles on the road, which supervises vehicle behaviors at the high layer and controls the motion at the lower layer. The DRL method named Proximal Policy Optimization is applied to derive the high-level decision-making policies. A self-attention mechanism is further introduced to improve the performance of our algorithm. Finally, the overtaking maneuvers of the ego vehicle in different training timesteps are analyzed and how the responses of other vehicles affect the ego one's overtaking behavior is investigated. Simulation results show that our approach can achieve good performance to deal with the two-way road autonomous overtaking task. Supplementary video is available at https://youtu.be/jPEGjM7cBuk.
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| 4. |
- Fonseca, Joana, et al.
(författare)
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Cooperative circumnavigation for a mobile target using adaptive estimation
- 2021
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Ingår i: Lecture Notes in Electrical Engineering. - Cham : Springer Science and Business Media Deutschland GmbH. ; , s. 33-48
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Konferensbidrag (refereegranskat)abstract
- In this paper we consider the problem of tracking a mobile target using adaptive estimation while circumnavigating it with a system of Unmanned Surface Vehicles (USVs). The mobile target considered is an irregular dynamic shape approximated by a circle with moving centre and varying radius. The USV system is composed of n USVs of which one is equipped with an Unmanned Aerial Vehicle (UAV) capable of measuring both the distance to the boundary of the target and to its centre. This USV equipped with the UAV uses adaptive estimation to calculate the location and size of the mobile target. The USV system must circumnavigate the boundary of the target while forming a regular polygon. We design two algorithms: One for the adaptive estimation of the target using the UAV’s measurements and another for the control protocol to be applied by all USVs in their navigation. The convergence of both algorithms to the desired state is proved up to a limit bound. Two simulated examples are provided to verify the performance of the algorithms designed in this paper.
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| 5. |
- Fonseca, Joana, et al.
(författare)
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Cooperative decentralised circumnavigation with application to algal bloom tracking
- 2019
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Ingår i: IEEE International Conference on Intelligent Robots and Systems. - : Institute of Electrical and Electronics Engineers Inc.. - 9781728140049 ; , s. 3276-3281
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Konferensbidrag (refereegranskat)abstract
- Harmful algal blooms occur frequently and deteriorate water quality. A reliable method is proposed in this paper to track algal blooms using a set of autonomous surface robots. A satellite image indicates the existence and initial location of the algal bloom for the deployment of the robot system. The algal bloom area is approximated by a circle with time varying location and size. This circle is estimated and circumnavigated by the robots which are able to locally sense its boundary. A multi-agent control algorithm is proposed for the continuous monitoring of the dynamic evolution of the algal bloom. Such algorithm comprises of a decentralised least squares estimation of the target and a controller for circumnavigation. We prove the convergence of the robots to the circle and in equally spaced positions around it. Simulation results with data provided by the SINMOD ocean model are used to illustrate the theoretical results.
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| 6. |
- Johansson, Alexander, et al.
(författare)
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Optimization of the H∞-norm of Dynamic Flow Networks
- 2018
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Ingår i: 2018 Annual American Control Conference (ACC). - : Institute of Electrical and Electronics Engineers (IEEE). ; , s. 1280-1285
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Konferensbidrag (refereegranskat)abstract
- In this paper, we study the H∞-norm of linear systems over graphs, which is used to model distribution networks. In particular, we aim to minimize the H∞-norm subject to allocation of the weights on the edges. The optimization problem is formulated with LMI (Linear-Matrix-Inequality) constraints. For distribution networks with one port, i.e., SISO systems, we show that the H∞-norm coincides with the effective resistance between the nodes in the port. Moreover, we derive an upper bound of the H∞-norm, which is in terms of the algebraic connectivity of the graph on which the distribution network is defined.
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| 7. |
- Nekouei, Ehsan, et al.
(författare)
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Optimal Decision Fusion Under Order Effects
- 2019
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Ingår i: IFAC PAPERSONLINE. - : ELSEVIER SCIENCE BV. - 2405-8963. ; , s. 53-60
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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.
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| 8. |
- Nimara, Doumitrou Daniil, et al.
(författare)
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Model-Based Reinforcement Learning for Cavity Filter Tuning
- 2023
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Ingår i: Proceedings of the 5th Annual Learning for Dynamics and Control Conference, L4DC 2023. - : ML Research Press. ; , s. 1297-1307
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Konferensbidrag (refereegranskat)abstract
- The ongoing development of telecommunication systems like 5G has led to an increase in demand of well calibrated base transceiver station (BTS) components. A pivotal component of every BTS is cavity filters, which provide a sharp frequency characteristic to select a particular band of interest and reject the rest. Unfortunately, their characteristics in combination with manufacturing tolerances make them difficult for mass production and often lead to costly manual post-production fine tuning. To address this, numerous approaches have been proposed to automate the tuning process. One particularly promising one, that has emerged in the past few years, is to use model free reinforcement learning (MFRL); however, the agents are not sample efficient. This poses a serious bottleneck, as utilising complex simulators or training with real filters is prohibitively time demanding. This work advocates for the usage of model based reinforcement learning (MBRL) and showcases how its utilisation can significantly decrease sample complexity, while maintaining similar levels of success rate. More specifically, we propose an improvement over a state-of-the-art (SoTA) MBRL algorithm, namely the Dreamer algorithm. This improvement can serve as a template for applications in other similar, high-dimensional non-image data problems. We carry experiments on two complex filter types, and show that our novel modification on the Dreamer architecture reduces sample complexity by a factor of 4 and 10, respectively. Our findings pioneer the usage of MBRL which paves the way for utilising more precise and accurate simulators which was previously prohibitively time demanding.
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| 9. |
- Raghavan, Aneesh, et al.
(författare)
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Stochastic Control Formulation of The Car Overtake Problem
- 2018
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Ingår i: IFAC-PapersOnLine. - : Elsevier. - 2405-8963. ; 51:9, s. 124-129
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Tidskriftsartikel (refereegranskat)abstract
- In this paper, we consider the classic car overtake problem. There are three cars, two moving along the same direction in the same lane while the third car moves in the direction opposite to that of the first two cars in the adjacent lane. The objective of the trailing car is to overtake the car in front of it avoiding collision with the other cars in the scenario. The information available to the trailing car is the relative position, relative velocities with respect to other cars and its position and past actions. The relative position and relative velocity information is corrupted by noise. Given this information, the car needs to make a decision as to whether it wants to overtake or not. We present a control algorithm for the car which minimizes the probability of collision with both the cars. We also present the results obtained by simulating the above scenario with the control algorithm. Through simulations, we study the effect of the variance of the measurement noise and the time at which the decision is made on the probability of collision.
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| 10. |
- Ringbäck, Rasmus, et al.
(författare)
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Multi-Agent Formation Tracking for Autonomous Surface Vehicles
- 2021
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Ingår i: IEEE Transactions on Control Systems Technology. - : Institute of Electrical and Electronics Engineers (IEEE). - 1063-6536 .- 1558-0865. ; 29:6, s. 2287-2298
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Tidskriftsartikel (refereegranskat)abstract
- In this article, the problem of collaborative tracking of an underwater target using autonomous surface vehicles (ASVs) is studied. Distance-based formation control with a collision-avoidance potential function is employed as a solution. A formation control protocol is devised and applied to the formation tracking problem. With the protocol, the vehicles form a desired formation around a moving target in order to continuously estimate its position, while the centroid of the formation tracks the target. Almost global stability is proved for the case with three tracking agents. A fully operational platform with four ASVs was built to implement the derived algorithms. One of the vehicles was used to simulate a target and the rest to form a triangular formation around it. Power usage of a naval vessel is highly affected by water resistance forces which increases significantly with the velocity. This was accounted for by adding an additional term to the formation tracking protocol, thereby increasing the overall system endurance. Experimental results are presented.
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