arXiv subjects

Yirui Cong

Publications and source records attributed to Yirui Cong.

At least 19 recordsLinked to original sources

arXiv2025

Asymptotic Boundedness of Distributed Set-Membership Filtering

Asymptotic boundedness is a crucial property of Distributed Set-Membership Filtering (DSMFing) that prevents the unbounded growth of the set estimates caused by the wrapping effect. However, this important property remains underinvestigated, compared to its noise-free and stochastic-noise counterparts, i.e., the convergence of Distributed Observers (DOs) and the bounded error covariance of Distributed Kalman Filters (DKFs). This paper studies the asymptotic boundedness of DSMFing for linear discrete-time systems. A novel concept, termed the Collective Observation-Information Tower (COIT), is introduced to characterize the fundamental relationship between the structure of graphs and the set estimates, which enables the boundedness analysis. Leveraging the COIT, an easily verifiable sufficient condition for the asymptotic boundedness of linear DSMFing is established. Surprisingly, the sufficient condition generalizes the well-known collective detectability condition for DOs and DKFs; it links DSMFs to existing distributed estimation methods and reveals the unique characteristic of DSMFs.

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arXiv2024

Optimal Set-Membership Smoothing

This article studies the Set-Membership Smoothing (SMSing) problem for non-stochastic Hidden Markov Models. By adopting the mathematical concept of uncertain variables, an optimal SMSing framework is established for the first time. This optimal framework reveals the principles of SMSing and the relationship between set-membership filtering and smoothing. Based on the design principles, we put forward two SMSing algorithms: one for linear systems with zonotopic constrained uncertainties, where the solution is given in a closed form, and the other for a class of nonlinear systems. Numerical simulations corroborate the effectiveness of our theoretical results.

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arXiv2024

Formation Under Communication Constraints: Control Performance Meets Channel Capacity

In wireless communication-based formation control systems, the control performance is significantly impacted by the channel capacity of each communication link between agents. This relationship, however, remains under-investigated in the existing studies. To address this gap, the formation control problem of classical second-order multi-agent systems with bounded process noises was considered taking into account the channel capacity. More specifically, the model of communication links between agents is first established, based on a new concept -- guaranteed communication region, which characterizes all possible locations for successful message decoding in the present of control-system uncertainty. Furthermore, we rigorously prove that, the guaranteed communication region does not unboundedly increase with the transmission time, which indicates an important trade-off between the guaranteed communication region and the data rate. The fundamental limits of data rate for any desired accuracy are also obtained. Finally, the integrated design to achieve the desired formation accuracy is proposed, where an estimation-based controller and transmit power control strategy are developed.

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arXiv2023

Existence and Completeness of Bounded Disturbance Observers: A Set-Membership Viewpoint

This paper investigates the boundedness of the Disturbance Observer (DO) for linear discrete-time systems. In contrast to previous studies that focus on analyzing and/or designing observer gains, our analysis and synthesis approach is based on a set-membership viewpoint. From this viewpoint, a necessary and sufficient existence condition of bounded DOs is first established, which can be easily verified. Furthermore, a set-membership filter-based DO is developed, and its completeness is proved; thus, our proposed DO is bounded if and only if bounded DOs exist. We also prove that the proposed DO has the capability to achieve the worst-case optimality, which can provide a benchmark for the design of DOs. Finally, numerical simulations are performed to corroborate the effectiveness of the theoretical results.

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arXiv2023

Cooperative Filtering with Range Measurements: A Distributed Constrained Zonotopic Method

This article studies the distributed estimation problem of a multi-agent system with bounded absolute and relative range measurements. Parts of the agents are with high-accuracy absolute measurements, which are considered as anchors; the other agents utilize lowaccuracy absolute and relative range measurements, each derives an uncertain range that contains its true state in a distributed manner. Different from previous studies, we design a distributed algorithm to handle the range measurements based on extended constrained zonotopes, which has low computational complexity and high precision. With our proposed algorithm, agents can derive their uncertain range sequentially along the chain topology, such that agents with low-accuracy sensors can benefit from the high-accuracy absolute measurements of anchors and improve the estimation performance. Simulation results corroborate the effectiveness of our proposed algorithm and verify our method can significantly improve the estimation accuracy.

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arXiv2023

Distributed Set-membership Filtering Frameworks For Multi-agent Systems With Absolute and Relative Measurements

In this paper, we focus on the distributed set-membership filtering (SMFing) problem for a multi-agent system with absolute (taken from agents themselves) and relative (taken from neighbors) measurements. In the literature, the relative measurements are difficult to deal with, and the SMFs highly rely on specific set descriptions. As a result, establishing the general distributed SMFing framework having relative measurements is still an open problem. To solve this problem, first, we provide the set description based on uncertain variables determined by the relative measurements between two agents as the foundation. Surprisingly, the accurate description requires only a single calculation step rather than multiple iterations, which can effectively reduce computational complexity. Based on the derived set description, called the uncertain range, we propose two distributed SMFing frameworks: one calculates the joint uncertain range of the agent itself and its neighbors, while the other only computes the marginal uncertain range of each local system. Furthermore, we compare the performance of our proposed two distributed SMFing frameworks and the benchmark -- centralized SMFing framework. A rigorous set analysis reveals that the distributed SMF can be essentially considered as the process of computing the marginal uncertain range to outer bound the projection of the uncertain range obtained by the centralized SMF in the corresponding subspace. Simulation results corroborate the effectiveness of our proposed distributed frameworks and verify our theoretical analysis.

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arXiv2023

Set-Membership Filtering-Based Cooperative State Estimation for Multi-Agent Systems

In this article, we focus on the cooperative state estimation problem of a multi-agent system. Each agent is equipped with absolute and relative measurements. The purpose of this research is to make each agent generate its own state estimation with only local measurement information and local communication with neighborhood agents using Set Membership Filter(SMF). To handle this problem, we analyzed centralized SMF framework as a benchmark of distributed SMF and propose a finite-horizon method called OIT-Inspired centralized constrained zonotopic algorithm. Moreover, we put forward a distributed Set Membership Filtering(SMFing) framework and develop a distributed constained zonotopic algorithm. Finally, simulation verified our theoretical results, that our proposed algorithms can effectively estimate the state of each agent.

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arXiv2022

Stability of Linear Set-Membership Filters With Respect to Initial Conditions: An Observation-Information Perspective

The issue of filter stability with respect to (w.r.t.) the initial condition refers to the unreliable filtering process caused by improper prior information of the initial state. This paper focuses on analyzing and resolving the stability issue w.r.t. the initial condition of the classical Set-Membership Filters (SMFs) for linear time-invariance systems, which has not yet been well understood in the literature. To this end, we propose a new concept -- the Observation-Information Tower (OIT), which describes how the measurements affect the estimate in a set-intersection manner without relying on the initial condition. The proposed OIT enables a rigorous stability analysis, a new SMFing framework, as well as an efficient filtering algorithm. Specifically, based on the OIT, explicit necessary and sufficient conditions for stability w.r.t. the initial condition are provided for the classical SMFing framework. Furthermore, the OIT inspires a stability-guaranteed SMFing framework, which fully handles the stability issue w.r.t. the initial condition. Finally, with the OIT-inspired framework, we develop a fast and stable constrained zonotopic SMF, which significantly overcomes the wrapping effect.

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arXiv2020

Implementation of UAV Coordination Based on a Hierarchical Multi-UAV Simulation Platform

In this paper, a hierarchical multi-UAV simulation platform,called XTDrone, is designed for UAV swarms, which is completely open-source 4 . There are six layers in XTDrone: communication, simulator,low-level control, high-level control, coordination, and human interac-tion layers. XTDrone has three advantages. Firstly, the simulation speedcan be adjusted to match the computer performance, based on the lock-step mode. Thus, the simulations can be conducted on a work stationor on a personal laptop, for different purposes. Secondly, a simplifiedsimulator is also developed which enables quick algorithm designing sothat the approximated behavior of UAV swarms can be observed inadvance. Thirdly, XTDrone is based on ROS, Gazebo, and PX4, andhence the codes in simulations can be easily transplanted to embeddedsystems. Note that XTDrone can support various types of multi-UAVmissions, and we provide two important demos in this paper: one is aground-station-based multi-UAV cooperative search, and the other is adistributed UAV formation flight, including consensus-based formationcontrol, task assignment, and obstacle avoidance.

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arXiv2020

Rethinking the Mathematical Framework and Optimality of Set-Membership Filtering

Set-Membership Filter (SMF) has been extensively studied for state estimation in the presence of bounded noises with unknown statistics. Since it was first introduced in the 1960s, the studies on SMF have used the set-based description as its mathematical framework. One important issue that has been overlooked is the optimality of SMF. In this work, we put forward a new mathematical framework for SMF using concepts of uncertain variables. We first establish two basic properties of uncertain variables, namely, the law of total range (a non-stochastic version of the law of total probability) and the equivalent Bayes' rule. This enables us to put forward a general SMFing framework with established optimality. Furthermore, we obtain the optimal SMF under a non-stochastic Markov condition, which is shown to be fundamentally equivalent to the Bayes filter. Note that the classical SMF in the literature is only equivalent to the optimal SMF we obtained under the non-stochastic Markov condition. When this condition is violated, we show that the classical SMF is not optimal and it only gives an outer bound on the optimal estimation.

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arXiv2019

Mission Oriented Miniature Fixed-wing UAV Swarms: A Multi-layered and Distributed Architecture

UAV swarms have triggered wide concern due to their potential application values in recent years. While there are studies proposed in terms of the architecture design for UAV swarms, two main challenges still exist: (1) Scalability, supporting a large scale of vehicles; (2) Versatility, integrating diversified missions. To this end, a multi-layered and distributed architecture for mission oriented miniature fixed-wing UAV swarms is presented in this paper. The proposed architecture is built on the concept of modularity. It divides the overall system to five layers: low-level control, high-level control, coordination, communication and human interaction layers, and many modules that can be viewed as black boxes with interfaces of inputs and outputs. In this way, not only the complexity of developing a large system can be reduced, but also the versatility of supporting diversified missions can be ensured. Furthermore, the proposed architecture is fully distributed that each UAV performs the decision-making procedure autonomously so as to achieve better scalability. Moreover, different kinds of aerial platforms can be feasibly extended by using the control allocation matrices and the integrated hardware box. A prototype swarm system based on the proposed architecture is built and the proposed architecture is evaluated through field experiments with a scale of 21 fixed-wing UAVs. Particularly, to the best of our knowledge, this paper is the first work which successfully demonstrates formation flight, target recognition and tracking missions within an integrated architecture for fixed-wing UAV swarms through field experiments.

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arXiv2019

Coordinated Path Following Control of Fixed-wing Unmanned Aerial Vehicles

In this paper, we investigate the problem of coordinated path following for fixed-wing UAVs with speed constraints in 2D plane. The objective is to steer a fleet of UAVs along the path(s) while achieving the desired sequenced inter-UAV arc distance. In contrast to the previous coordinated path following studies, we are able through our proposed hybrid control law to deal with the forward speed and the angular speed constraints of fixed-wing UAVs. More specifically, the hybrid control law makes all the UAVs work at two different levels: those UAVs whose path following errors are within an invariant set (i.e., the designed coordination set) work at the coordination level; and the other UAVs work at the single-agent level. At the coordination level, we prove that even with speed constraints, the proposed control law can make sure the path following errors reduce to zero, while the desired arc distances converge to the desired value. At the single-agent level, the convergence analysis for the path following error entering the coordination set is provided. We develop a hardware-in-the-loop simulation testbed of the multi-UAV system by using actual autopilots and the X-Plane simulator. The effectiveness of the proposed approach is corroborated with both MATLAB and the testbed.

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arXiv2018

Gaussian Signalling for Covert Communications

In this work, we examine the optimality of Gaussian signalling for covert communications with an upper bound on $\mathcal{D}(p_{_1}||p_{_0})$ or $\mathcal{D}(p_{_0}||p_{_1})$ as the covertness constraint, where $\mathcal{D}(p_{_1}||p_{_0})$ and $\mathcal{D}(p_{_0}||p_{_1})$ are different due to the asymmetry of Kullback-Leibler divergence, $p_{_0}(y)$ and $p_{_1}(y)$ are the likelihood functions of the observation ${y}$ at the warden under the null hypothesis (no covert transmission) and alternative hypothesis (a covert transmission occurs), respectively. Considering additive white Gaussian noise at both the receiver and the warden, we prove that Gaussian signalling is optimal in terms of maximizing the mutual information of transmitted and received signals for covert communications with an upper bound on $\mathcal{D}(p_{_1}||p_{_0})$ as the constraint. More interestingly, we also prove that Gaussian signalling is not optimal for covert communications with an upper bound on $\mathcal{D}(p_{_0}||p_{_1})$ as the constraint, for which as we explicitly show skew-normal signalling can outperform Gaussian signalling in terms of achieving higher mutual information. Finally, we prove that, for Gaussian signalling, an upper bound on $\mathcal{D}(p_{_1}||p_{_0})$ is a tighter covertness constraint in terms of leading to lower mutual information than the same upper bound on $\mathcal{D}(p_{_0}||p_{_1})$, by proving $\mathcal{D}(p_{_0}||p_{_1}) \leq \mathcal{D}(p_{_1}||p_{_0})$.

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arXiv2017

Covert Communication with Finite Blocklength in AWGN Channels

Covert communication is to achieve a reliable transmission from a transmitter to a receiver while guaranteeing an arbitrarily small probability of this transmission being detected by a warden. In this work, we study the covert communication in AWGN channels with finite blocklength, in which the number of channel uses is finite. Specifically, we analytically prove that the entire block (all available channel uses) should be utilized to maximize the effective throughput of the transmission subject to a predetermined covert requirement. This is a nontrivial result because more channel uses results in more observations at the warden for detecting the transmission. We also determine the maximum allowable transmit power per channel use, which is shown to decrease as the blocklength increases. Despite the decrease in the maximum allowable transmit power per channel use, the maximum allowable total power over the entire block is proved to increase with the blocklength, which leads to the fact that the effective throughput increases with the blocklength.

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arXiv2016

Rate-Achieving Policy in Finite-Horizon Throughput Region for Multi-User Interference Channels

This paper studies a wireless network consisting of multiple transmitter-receiver pairs sharing the same spectrum where interference is regarded as noise. Previously, the throughput region of such a network was characterized for either one time slot or an infinite time horizon. This work aims to close the gap by investigating the throughput region for transmissions over a finite time horizon. We derive an efficient algorithm to examine the achievability of any given rate in the finite-horizon throughput region and provide the rate-achieving policy. The computational efficiency of our algorithm comes from the use of A* search with a carefully chosen heuristic function and a tree pruning strategy. We also show that the celebrated max-weight algorithm which finds all achievable rates in the infinite-horizon throughput region fails to work for the finite-horizon throughput region.

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arXiv2016

Event-Trigger Based Robust-Optimal Control for Energy Harvesting Transmitter

This paper studies an online algorithm for an energy harvesting transmitter, where the transmission (completion) time is considered as the system performance. Unlike the existing online algorithms which more or less require the knowledge on the future behavior of the energy-harvesting rate, we consider a practical but significantly more challenging scenario where the energy-harvesting rate is assumed to be totally unknown. Our design is formulated as a robust-optimal control problem which aims to optimize the worst-case performance. The transmit power is designed only based on the current battery energy level and the data queue length directly monitored by the transmitter itself. Specifically, we apply an event-trigger approach in which the transmitter continuously monitors the battery energy and triggers an event when a significant change occurs. Once an event is triggered, the transmit power is updated according to the solution to the robust-optimal control problem, which is given in a simple analytic form. We present numerical results on the transmission time achieved by the proposed design and demonstrate its robust-optimality.

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arXiv2016

Finite-Horizon Throughput Region for Wireless Multi-User Interference Channels

This paper studies a wireless network consisting of multiple transmitter-receiver pairs where interference is treated as noise. Previously, the throughput region of such networks was characterized for either one time slot or an infinite time horizon. We aim to fill the gap by investigating the throughput region for transmissions over a finite time horizon. Unlike the infinite-horizon throughput region, which is simply the convex hull of the throughput region of one time slot, the finite-horizon throughput region is generally non-convex. Instead of directly characterizing all achievable rate-tuples in the finite-horizon throughput region, we propose a metric termed the rate margin, which not only determines whether any given rate-tuple is within the throughput region (i.e., achievable or unachievable), but also tells the amount of scaling that can be done to the given achievable (unachievable) rate-tuple such that the resulting rate-tuple is still within (brought back into) the throughput region. Furthermore, we derive an efficient algorithm to find the rate-achieving policy for any given rate-tuple in the finite-horizon throughput region.

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arXiv2016

Offline Delay-Optimal Transmission for Energy Harvesting Nodes

This paper investigates the offline packet-delay-minimization problem for an energy harvesting transmitter. To overcome the non-convexity of the problem, we propose a C2-diffeomorphic transformation and provide the necessary and sufficient condition for the transformed problem to a standard convex optimization problem. Based on this condition, a simple choice of the transformation is determined which allows an analytically tractable solution of the original non-convex problem to be easily obtained once the transformed convex problem is solved. We further study the structure of the optimal transmission policy in a special case and find it to follow a weighted-directional-water-filling structure. In particular, the optimal policy tends to allocate more power in earlier time slots and less power in later time slots. Our analytical insight is verified by simulation results.

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