| 1. |
- Alanwar, Amr, et al.
(författare)
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Privacy-preserving set-based estimation using partially homomorphic encryption
- 2023
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Ingår i: European Journal of Control. - : Elsevier BV. - 0947-3580 .- 1435-5671. ; 71, s. 100786-
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Tidskriftsartikel (refereegranskat)abstract
- The set-based estimation has gained a lot of attention due to its ability to guarantee state enclosures for safety-critical systems. However, collecting measurements from distributed sensors often requires out-sourcing the set-based operations to an aggregator node, raising many privacy concerns. To address this problem, we present set-based estimation protocols using partially homomorphic encryption that pre-serve the privacy of the measurements and sets bounding the estimates. We consider a linear discrete-time dynamical system with bounded modeling and measurement uncertainties. Sets are represented by zonotopes and constrained zonotopes as they can compactly represent high-dimensional sets and are closed under linear maps and Minkowski addition. By selectively encrypting parameters of the set repre-sentations, we establish the notion of encrypted sets and intersect sets in the encrypted domain, which enables guaranteed state estimation while ensuring privacy. In particular, we show that our protocols achieve computational privacy using the cryptographic notion of computational indistinguishability. We demonstrate the efficiency of our approach by localizing a real mobile quadcopter using ultra-wideband wireless devices.
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| 2. |
- Hashemi, Ehsan, et al.
(författare)
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A Dynamical Game Approach for Integrated Stabilization and Path Tracking for Autonomous Vehicles
- 2020
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Ingår i: 2020 American control conference (ACC). - : IEEE. ; , s. 4108-4113
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Konferensbidrag (refereegranskat)abstract
- A new game theory based framework is proposed for path tracking and stabilization of autonomous vehicles. In the developed framework, vehicle body and corner traction control strategies are formulated in terms of players in a differential game. An integrated stability and path tracking control based on a non-cooperative differential game is developed. It includes bidirectional slip effect and wheel dynamics, which reflect more accurate longitudinal and lateral dynamics in harsh maneuvers and scenarios with sudden changes in the path planners trajectories. The open-loop and closed-loop Nash equilibrium control strategies are obtained by solving a two-player linear-quadratic differential game for the dynamical system of the overall tracking error. The performance of the proposed control strategy is validated with software simulations in various driving conditions.
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| 3. |
- Hashemi, Ehsan, et al.
(författare)
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Robust Slip-Aware Fusion for Mobile Robots State Estimation
- 2022
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Ingår i: IEEE Robotics and Automation Letters. - : Institute of Electrical and Electronics Engineers (IEEE). - 2377-3766. ; 7:3, s. 7896-7903
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Tidskriftsartikel (refereegranskat)abstract
- A novel robust and slip-aware speed estimation framework is developed and experimentally verified for mobile robot navigation by designing proprioceptive robust observers at each wheel. The observer for each corner is proved to be consistent, in the sense that it can provide an upper bound of the mean square estimation error (MSE) timely. Under proper conditions, the MSE is proved to be uniformly bounded. A covariance intersection fusion method is used to fuse the wheel-level estimates, such that the updated estimate remains consistent. The estimated slips at each wheel are then used for a robust consensus to improve the reliability of speed estimation in harsh and combined-slip scenarios. As confirmed by indoor and outdoor experiments under different surface conditions, the developed framework addresses state estimation challenges for mobile robots that experience uneven torque distribution or large slip. The novel proprioceptive observer can also be integrated with existing tightly-coupled visual-inertial navigation systems.
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| 4. |
- He, Xingkang, et al.
(författare)
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Asymptotic Analysis of Federated Learning Under Event-Triggered Communication
- 2023
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Ingår i: IEEE Transactions on Signal Processing. - : Institute of Electrical and Electronics Engineers (IEEE). - 1053-587X .- 1941-0476. ; 71, s. 2654-2667
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Tidskriftsartikel (refereegranskat)abstract
- Federated learning (FL) is a collaborative machine learning (ML) paradigm based on persistent communication between a central server and multiple edge devices. However, frequent communication of large ML models can incur considerable communication resources, especially costly for wireless network nodes. In this paper, we develop a communication-efficient protocol to reduce the number of communication instances in each round while maintaining convergence rate and asymptotic distribution properties. First, we propose a novel communication-efficient FL algorithm that utilizes an event-triggered communication mechanism, where each edge device updates the model by using stochastic gradient descent with local sampling data and the central server aggregates all local models from the devices by using model averaging. Communication can be reduced since each edge device and the central server transmits its updated model only when the difference between the current model and the last communicated model is larger than a threshold. Thresholds of the devices and server are not necessarily coordinated, and the thresholds and step sizes are not constrained to be of specific forms. Under mild conditions on loss functions, step sizes and thresholds, for the proposed algorithm, we establish asymptotic analysis results in three ways, respectively: convergence in expectation, almost-sure convergence, and asymptotic distribution of the estimation error. In addition, we show that by fine-tunning the parameters, the proposed event-triggered FL algorithm can reach the same convergence rate as state-of-the-art results from existing time-driven FL. We also establish asymptotic efficiency in the sense of Central Limit Theorem of the estimation error. Numerical simulations for linear regression and image classification problems in the literature are provided to show the effectiveness of the developed results.
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| 5. |
- He, Xingkang, et al.
(författare)
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Consistent Kalman filters for nonlinear uncertain systems over sensor networks
- 2020
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Ingår i: Control Theory and Technology. - : Springer Nature. - 2095-6983 .- 2198-0942. ; 18:4, s. 399-408
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Tidskriftsartikel (refereegranskat)abstract
- In this paper, we study how to design filters for nonlinear uncertain systems over sensor networks. We introduce two Kalman-type nonlinear filters in centralized and distributed frameworks. Moreover, the tuning method for the parameters of the filters is established to ensure the consistency, i.e., the mean square error is upper bounded by a known parameter matrix at each time. We apply the consistent filters to the track-to-track association analysis of multi-targets with uncertain dynamics. A novel track-to-track association algorithm is proposed to identify whether two tracks are from the same target. It is proven that the resulting probability of mis-association is lower than the desired threshold. Numerical simulations on track-to-track association are given to show the effectiveness of the methods.
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| 6. |
- He, Xingkang, et al.
(författare)
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Distributed control under compromised measurements : Resilient estimation, attack detection, and vehicle platooning
- 2021
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Ingår i: Automatica. - : Elsevier BV. - 0005-1098 .- 1873-2836. ; 134, s. 109953-
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Tidskriftsartikel (refereegranskat)abstract
- We study how to design a secure observer-based distributed controller such that a group of vehicles can achieve accurate state estimates and formation control even if the measurements of a subset of vehicle sensors are compromised by a malicious attacker. We propose an architecture consisting of a resilient observer, an attack detector, and an observer-based distributed controller. The distributed detector is able to update three sets of vehicle sensors: the ones surely under attack, surely attack free, and suspected to be under attack. The adaptive observer saturates the measurement innovation through a preset static or time-varying threshold, such that the potentially compromised measurements have limited influence on the estimation. Essential properties of the proposed architecture include: (1) The detector is fault-free, and the attacked and attack-free vehicle sensors can be identified in finite time; (2) The observer guarantees both real-time error bounds and asymptotic error bounds, with tighter bounds when more attacked or attack-free vehicle sensors are identified by the detector; (3) The distributed controller ensures closed-loop stability. The effectiveness of the proposed methods is evaluated through simulations by an application to vehicle platooning.
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| 7. |
- He, Xingkang, et al.
(författare)
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Distributed Design of Robust Kalman Filters Over Corrupted Channels
- 2021
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Ingår i: IEEE Transactions on Signal Processing. - : Institute of Electrical and Electronics Engineers (IEEE). - 1053-587X .- 1941-0476. ; 69, s. 2422-2434
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Tidskriftsartikel (refereegranskat)abstract
- We study distributed filtering for a class of uncertain systems over corrupted communication channels. We propose a distributed robust Kalman filter with stochastic gains, through which upper bounds of the conditional mean square estimation errors are calculated online. We present a robust collective observability condition, under which the mean square error of the distributed filter is proved to be uniformly upper bounded if the network is strongly connected. For better performance, we modify the filer by introducing a switching fusion scheme based on a sliding window. It provides a smaller upper bound of the conditional mean square error. Numerical simulations are provided to validate the theoretical results and show that the filter scales to large networks.
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| 8. |
- He, Xingkang, et al.
(författare)
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Distributed filtering for uncertain systems under switching sensor networks and quantized communications
- 2020
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Ingår i: Automatica. - : Elsevier Ltd. - 0005-1098 .- 1873-2836. ; 114
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Tidskriftsartikel (refereegranskat)abstract
- This paper considers the distributed filtering problem for a class of stochastic uncertain systems under quantized data flowing over switching sensor networks. Employing the biased noisy observations of the local sensor and interval-quantized messages from neighboring sensors successively, an extended state based distributed Kalman filter (DKF) is proposed for simultaneously estimating both system state and uncertain dynamics. To alleviate the effect of observation biases, an event-triggered update based DKF is presented with a tighter mean square error (MSE) bound than that of the time-driven one by designing a proper threshold. Both the two DKFs are shown to provide the upper bounds of MSE online for each sensor. Under mild conditions on systems and networks, the MSE boundedness and asymptotic unbiasedness for the proposed two DKFs are proved. Finally, numerical simulations demonstrate the effectiveness of the developed filters.
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| 9. |
- He, Xingkang, et al.
(författare)
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Distributed Kalman Filters With State Equality Constraints : Time-Based and Event-Triggered Communications
- 2020
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Ingår i: IEEE Transactions on Automatic Control. - : IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC. - 0018-9286 .- 1558-2523. ; 65:1, s. 28-43
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Tidskriftsartikel (refereegranskat)abstract
- In this paper, we investigate a distributed estimation problem for multiagent systems with state equality constraints (SEC). First, under a time-based consensus communication protocol, applying a modified projection operator and the covariance intersection fusion method, we propose a distributed Kalman filter with guaranteed consistency and satisfied SEC. Furthermore, we establish the relationship between consensus step, SEC, and estimation error covariance in dynamic and steady processes, respectively. Employing a space decomposition method, we show that the error covariance in the constraint set can be arbitrarily small by setting a sufficiently large consensus step. Besides, we propose an extended collective observability (ECO) condition based on SEC, which is milder than existing observability conditions. Under the ECO condition, through utilizing a technique of matrix approximation, we prove the boundedness of error covariance and the exponentially asymptotic unbiasedness of state estimate, respectively. Moreover, under the ECO condition for linear time-invariant systems with SEC, we provide a novel event-triggered communication protocol by employing the consistency, and give an offline design principle of triggering thresholds with guaranteed boundedness of error covariance. More importantly, we quantify and analyze the communication rate for the proposed event-triggered distributed Kalman filter, and provide optimization based methods to obtain the minimal (maximal) successive nontriggering (triggering) times. Two simulations are provided to demonstrate the developed theoretical results and the effectiveness of the filters.
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| 10. |
- He, Xingkang, et al.
(författare)
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Distributed parameter estimation under event-triggered communications
- 2019
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Ingår i: Proceedings of the 2019 Chinese Control Conference (CCC). ; , s. 5888-5893
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Konferensbidrag (refereegranskat)abstract
- In this paper, we study a distributed parameter estimation problem with an asynchronous communication protocol over multi-agent systems. Different from traditional time-driven communication schemes, in this work, data can be transmitted between agents intermittently rather than in a steady stream. First, we propose a recursive distributed estimator based on an event-triggered communication scheme, through which each agent can decide whether the current estimate is sent out to its neighbors or not. With this scheme, considerable communications between agents can be effectively reduced. Then, under mild conditions including a collective observability, we provide a design principle of triggering thresholds to guarantee the asymptotic unbiasedness and strong consistency. Furthermore, under certain conditions, we reveal that, with probability one, for every agent the time interval between two successive triggering instants goes to infinity as time goes to infinity. Finally, we provide a numerical simulation to validate the theoretical results of this paper.
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