Article
Engineering, Aerospace
Chenjian Ran, Zili Deng
Summary: A new methodology for improving measurement accuracy and robustness in networked multisensor systems is proposed in this paper, which includes a new soft sensor concept and three new approaches. By applying these new approaches, a universal robust fusion Kalman filtering theory is presented, with proven stability and effectiveness in practical applications.
AEROSPACE SCIENCE AND TECHNOLOGY
(2021)
Article
Engineering, Electrical & Electronic
Pan Li, Jianfeng Li, Fuhui Zhou, Xiaofei Zhang, Qihui Wu
Summary: This paper presents an optimization strategy for array orientations in a 3D direct position determination (DPD) system using uniform linear arrays (ULAs) to locate emitters. The E-optimality criterion is exploited to minimize the spectral norm of the Cramer-Rao lower bound (CRLB) and formulate the problem. The paper also proposes a semi-definite relaxation (SDR) solution for large-scale antenna array systems and validates its near-optimal localization performance through simulations.
Article
Automation & Control Systems
Yuan Gao, Zili Deng
Summary: This article presents two universal approaches for solving the robust fusion estimation problems in networked sensor systems (NSSs) with hard and soft sensors. These approaches are proven to be robust and accurate for real-time applications. The effectiveness of the proposed methods is demonstrated through a simulation applied to a two-mass spring damper mechanical system.
INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL
(2023)
Article
Automation & Control Systems
Jingang Liu, Gang Hao
Summary: This paper focuses on covariance intersection (CI) fusion for multi-sensor linear time-varying systems with unknown cross-covariance. A CI fusion weighted by diagonal matrix (DCI) is proposed, which is proven to be unbiased, robust and more accurate than classical CI fusion. The genetic simulated annealing (GSA) algorithm is used for multi-parameter optimization problem caused by diagonal matrix weights. To address the time-consuming optimization process in the GSA algorithm, the Back Propagation (BP) network is employed to obtain the optimal weights. The proposed DCI based on GSA algorithm and BP network achieves higher accuracy and better stability compared to classic CI fusion algorithms. Simulation analyses validate the effectiveness and correctness of the conclusion.
ASIAN JOURNAL OF CONTROL
(2023)
Article
Computer Science, Information Systems
Changlin Zhou, Chunyang Wang, Jian Gong, Lei Bao, Geng Chen, Mingjie Liu
Summary: This paper presents a solution for robust beamforming and target power estimation in the presence of main-lobe interference. The solution involves the use of a weighting matrix at the receiving end, which is obtained through semi-definite programming and singular value decomposition. The effectiveness of the proposed method is confirmed through performance comparison.
Article
Automation & Control Systems
Yuan Gao, Zili Deng
Summary: A new augmented state method with fictitious noises is proposed for multisensor time-varying networked mixed uncertain systems, which transforms the original system into a standard system without delays and with uncertain-variance fictitious white noises to improve robustness and estimation accuracy.
IMA JOURNAL OF MATHEMATICAL CONTROL AND INFORMATION
(2021)
Article
Automation & Control Systems
Zhongyao Hu, Bo Chen, Wen-An Zhang, Li Yu
Summary: This article proposes hierarchy-structure-independent hierarchical CI fusion and fusion-order-independent sequential CI fusion, by analogy with batch CI fusion, to avoid negative effects caused by uncertainties. Finally, two simulations verify the effectiveness and advantages of the proposed methods.
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
(2023)
Article
Operations Research & Management Science
V. Jeyakumar, G. Li, D. Woolnough, H. Wu
Summary: In this paper, an improved robust optimization model is proposed for addressing data uncertainty in hypoxia-based radiation treatment planning. The model demonstrates effective handling of uncertainties in the dose influence matrix and re-oxygenation data in numerical experiments.
Article
Chemistry, Analytical
Wenjuan Qi, Shigang Wang
Summary: This paper addresses the problem of robust Kalman filtering for multisensor time-varying systems with uncertainties of noise variances. Robust local and fused time-varying Kalman filters are presented based on worst-case conservative system with conservative upper bounds of noise variances. The robustness and accuracy relations of the filters are proved, and steady-state robust filters for time-invariant systems are also presented.
Article
Robotics
Liang Li, Ming Yang
Summary: This article introduces a pose fusion method that considers the correlation among measurements, utilizing the theory of covariance intersection to separate independent and dependent uncertainties. It provides a correlated pose fusion algorithm on the manifold and a localization framework, with experimental results validating its advantages over state-of-the-art methods.
IEEE TRANSACTIONS ON ROBOTICS
(2021)
Article
Computer Science, Artificial Intelligence
Christopher W. Hays, Troy Henderson
Summary: Fusing information from separate sensors is a common problem in various scientific and engineering fields, with multiple potential solutions available in literature. This study presents a fusion methodology that cooperatively combines the information from two sources while maintaining both consistency and tightness. Analytically derived upper and lower bounds for a scaling parameter, Omega, are also provided to ensure the consistency and tightness of the fusion solution. The results show that the proposed solution outperforms the current state-of-the-art solution by providing tighter approximations of the optimal solution while maintaining the optimal solution as the lower bound.
INFORMATION FUSION
(2023)
Article
Automation & Control Systems
Georgios Kotsalis, Guanghui Lan, Arkadi S. Nemirovski
Summary: This work tackles the finite-horizon robust covariance control problem for discrete time, partially observable, linear systems with constraints on deterministic uncertain-but-bounded disturbances. A computationally tractable procedure for designing control policies is developed, ensuring the required performance specifications. The theoretical findings are demonstrated through a numerical example.
SIAM JOURNAL ON CONTROL AND OPTIMIZATION
(2021)
Article
Automation & Control Systems
Weijian Li, Xianlin Zeng, Yiguang Hong, Haibo Ji
Summary: This paper investigates distributed computation for semi-definite programming (SDP) problems over multi-agent networks. Two SDP problems are transformed into distributed optimization problems by utilizing their structures and introducing consensus constraints. Two distributed algorithms are proposed based on primal-dual and consensus methods, with convergence proven to optimal solutions and rates evaluated by the duality gap.
Article
Automation & Control Systems
Muhammed O. Sayin, Tamer Basar
Summary: A robust sensor design framework is introduced to defend against an unknown type attacker in stochastic control systems, utilizing a robust linear-plus-noise signaling strategy to minimize damage to the system's objective. The solution concept of Stackelberg equilibrium is applied, with necessary and sufficient conditions formulated for a linear matrix inequality in the posterior belief covariance matrix. This allows for the computation of robust sensor design strategies globally, even in nonconvex and highly nonlinear optimization problems.
IEEE TRANSACTIONS ON AUTOMATIC CONTROL
(2021)
Article
Automation & Control Systems
Jiri Ajgl, Ondrej Straka
Summary: This paper presents a linear rule for covariance intersection fusion and discusses the case when some elements of the cross-correlation matrix are known. It introduces techniques for constructing upper bounds of the joint mean square error matrix and considers explicit configurations for fusing up to four estimates, while also noting their applicability for more than four estimates.
