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Deep Koopman Approach for Nonlinear Dynamics and Control of Tendon-Driven Continuum Robots

IEEE ROBOTICS AND AUTOMATION LETTERS 2025年第3期10卷 2926-2933页

作者： Feizi, Navid Pedrosa, Filipe C. Jayender, Jagadeesan Patel, Rajni V. London Hlth Sci Ctr Canadian Surg Technol & Adv Robot CSTAR London ON N6A 5A5 Canada Western Univ Sch Biomed Engn London ON N6A 3K7 Canada Western Univ Dept Elect & Comp Engn CSTAR London ON N6A 3K7 Canada Harvard Med Sch Brigham & Womens Hosp Dept Radiol Boston MA 02115 USA Western Univ Dept Elect & Comp Engn CSTAR Dept Clin Neurol SciDept Surg London ON N6A 3K7 Canada

Tendon-driven continuum robots (TDCRs) have received widespread attention in the medical domain due to their slender shape and flexibility. Modeling the dynamics of TDCRs involves continuum mechanics that result in nonlinear and computationally intensive models posing challenges for real-time control. In this work, we propose efficient, and control-oriented modeling of the nonlinear dynamics of TDCRs leveraging the deep Koopman approach. This method transforms the states of the system into an intrinsic nonlinear manifold, where the autonomous dynamics are approximated linearly, and the actuation input enters the system with a bilinear term. The proposed model captures the nonlinearities, including space-dependent variations in the system spectrum. Position control is implemented using a linear quadratic controller, leveraging the linear nature of the Koopman operator. The accuracy of the proposed method is experimentally validated using a dual-tendon robotic steerable catheter, achieving a position tracking error of 1.64 mm (SD = 0.74) for multi-sinusoidal, and 0.60 mm (SD = 0.30) for sinusoidal (0.05 Hz) target trajectories. The results demonstrate the potential for applying the proposed approach for real-time control of a broad range of TDCRs.

关键词： eigenvalues and eigenfunctions Nonlinear dynamical systems Computational modeling Aerospace electronics Robots Catheters Real-time systems Deep learning Continuum robots Manifolds Deep Koopman tendon-driven continuum robot (TDCR) nonlinear dynamics real-time control robotic catheter

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Reweighted Subspace Clustering Guided by Local and Global Structure Preservation

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IEEE TRANSACTIONS ON CYBERNETICS 2025年第3期55卷 1436-1449页

作者： Zhou, Jie Huang, Chucheng Gao, Can Wang, Yangbo Pedrycz, Witold Yuan, Ge Shenzhen Univ Natl Engn Lab Big Data Syst Comp Technol Shenzhen 518060 Peoples R China Shenzhen Inst Artificial Intelligence & Robot Soc SZU Branch Shenzhen 518060 Peoples R China Shenzhen Univ Coll Comp Sci & Software Engn Shenzhen 518060 Peoples R China Commun Univ China Sch Comp Sci & Cybersecur Beijing 100024 Peoples R China Univ Alberta Dept Elect & Comp Engn Edmonton AB T6G 2R3 Canada

Subspace clustering has attracted significant interest for its capacity to partition high-dimensional data into multiple subspaces. The current approaches to subspace clustering predominantly revolve around two key aspects: 1) the construction of an effective similarity matrix and 2) the pursuit of sparsity within the projection matrix. However, assessing whether the dimensionality of the projected subspace is the true dimensionality of the data is challenging. Therefore, the clustering performance may decrease when dealing with scenarios such as subspace overlap, insufficient projected dimensions, data noise, etc., since the defined dimensionality of the projected lower-dimensional space may deviate significantly from its true value. In this research, we introduce a novel reweighting strategy, which is applied to projected coordinates for the first time and propose a reweighted subspace clustering model guided by the preservation of the both local and global structural characteristics (RWSC). The projected subspaces are reweighted to augment or suppress the importance of different coordinates, so that data with overlapping subspaces can be better distinguished and the redundant coordinates produced by the predefined number of projected dimensions can be further removed. By introducing reweighting strategies, the bias caused by imprecise dimensionalities in subspace clustering can be alleviated. Moreover, global scatter structure preservation and adaptive local structure learning are integrated into the proposed model, which helps RWSC capture more intrinsic structures and its robustness and applicability can then be improved. Through rigorous experiments on both synthetic and real-world datasets, the effectiveness and superiority of RWSC are empirically verified.

关键词： High dimensional data Clustering methods Robustness Noise measurement Linear programming Laplace equations eigenvalues and eigenfunctions Computational modeling Vectors Training Local and global structures projection subspace reweighting subspace clustering

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Inversion of Time-Evolving Sound Speed Profiles by DREAM-zs With QPSO Proposal Distribution

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IEEE JOURNAL OF OCEANIC ENGINEERING 2025年第2期50卷 1403-1418页

作者： Wang, Ye Li, Jianlong Chen, Jing Xu, Yida Zeng, Lingzao Zhejiang Univ Coll Informat Sci Elect Engn Hangzhou 310027 Peoples R China Zhejiang Univ Hainan Inst Sanya 572025 Peoples R China Zhejiang Univ Coll Environm Resource Sci Hangzhou 310029 Peoples R China

Sound speed profile (SSP) inversion using acoustic data is an efficient approach for estimating SSPs, though it presents a nonlinear and non-Gaussian problem. To improve the spatial resolution of SSP inversion, a range-dependent environment is considered, which increases the number of parameters to be estimated. These challenges limit the performance of commonly used methods, such as the ensemble Kalman filter (EnKF) and particle filter (PF). While EnKFs can handle high-dimensional problems, they assume Gaussian probability distributions. PFs are better suited for highly nonlinear and non-Gaussian systems but are generally more computationally intensive. DiffeRential evolution adaptive Metropolis (DREAM)-zs, a Markov chain Monte Carlo method, is effective for approximating high-dimensional probability distributions, although its convergence speed decreases rapidly as the dimensionality of the parameter space increases. Quantum-behaved particle swarm optimization (QPSO), which combines principles from quantum mechanics and PSO, is a probabilistic optimization algorithm that has been proven successful in various optimization problems. To enhance the efficiency of DREAM-zs, the QPSO proposal distribution is embedded during the burn-in period, forming the DREAM-zqs method. The proposed method is used to track time-evolving SSPs in a range-dependent environment. The inversion problem is formulated in a state-space form, integrating data from the regional ocean modeling system to improve efficiency by shifting the state vector. Simulations and experimental results demonstrate that both DREAM-zs and DREAM-zqs outperform EnKF and PF, with DREAM-zqs achieving faster convergence than DREAM-zs while maintaining inversion accuracy.

关键词： Vectors Acoustics Proposals Sea measurements Read only memory Pressure measurement Noise Mathematical models Estimation eigenvalues and eigenfunctions DiffeRential evolution adaptive Metropolis (DREAM)-zs quantum-behaved particle swarm optimization (QPSO) acoustic inversion sound speed profile (SSP)

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Boundary output feedback stabilization for 2-D and 3-D parabolic equations

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AUTOMATICA 2025年 176卷

作者： Lhachemi, Hugo Munteanu, Ionut Prieur, Christophe Univ Paris Saclay CNRS CentraleSupelec Lab Signaux & Syst F-91190 Gif Sur Yvette France Alexandru Ioan Cuza Univ Fac Math Bd Carol 111 Iasi 700506 Romania Romanian Acad O Mayer Inst Math Bd Carol 18 Iasi 700505 Romania Univ Grenoble Alpes Gipsa Lab CNRS Grenoble INP F-38000 Grenoble France

The present paper addresses the topic of boundary output feedback stabilization of parabolic-type equations, governed by linear differential operators which can be diagonalized by the introduction of adequate weighting functions (by means of the Sturm-Liouville method), and which evolve in bounded spatial domains that are subsets of Rd, d = 2, 3. Generalizing previous works for the boundary output feedback control of 1-D parabolic PDEs and for the state feedback control of multi-D parabolic PDEs, we report in this paper an output feedback boundary stabilizing control with internal Dirichlet measurements designed by means of a finite-dimensional observer. The reported control design procedure is shown to be systematic for 2-D and 3-D parabolic equations. (c) 2025 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY license (http://***/licenses/by/4.0/).

关键词： Second order parabolic equations Exponential asymptotic stabilization Observer design eigenvalues and eigenfunctions Spectral decomposition Proportional feedback control

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Tuning of parity-time symmetry effect through exceptional points in non-Hermitian terahertz metasurface

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JOURNAL OF APPLIED PHYSICS 2025年第5期137卷

作者： Bhardwaj, Anshul Islam, Maidul Panwar, Anuraj Kumar, Gagan Indian Inst Technol Guwahati Dept Phys Gauhati 781039 Assam India Assam Royal Global Univ Dept Phys Gauhati 781035 Assam India Jaypee Inst Informat Technol Dept Phys & Mat Sci & Engn Noida 62 Uttar Pradesh India

In this article, we investigate parity-time (PT) symmetry in a non-Hermitian terahertz metasurface composed of two orthogonally oriented split ring resonators. Initially, one resonator is diagonally displaced relative to the other to study PT-symmetry in the system. The eigenvalues and eigenstates of the metasurface are examined at various displacement values to analyze the PT-symmetric phase transition. At a specific displacement, the metasurface design exhibits degenerate eigenvalues, marking the occurrence of an exceptional point. Beyond this point, the system transitions into a broken PT-symmetry phase. PT-symmetry is further explored by displacing the second resonator vertically and horizontally. This investigation reveals the presence of exceptional points during the transition from PT-asymmetry to PT-symmetry states. Additionally, the role of the split gap in the second resonator relative to the first is analyzed in this non-Hermitian system. It is observed that near-field coupling between the resonators plays a significant role during displacement. This is supported by the application of coupled mode theory to the metasurface. This comprehensive study on the impact of resonator displacement leading to exceptional points in a strongly coupled system holds potential for highly sensitive sensing applications and other advancements in photonics.

关键词： eigenvalues and eigenfunctions

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A Novel Approach to Construct a Good Dataset for Differential-Neural Cryptanalysis

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IEEE TRANSACTIONS ON DEPENDABLE AND SECURE COMPUTING 2025年第1期22卷 246-262页

作者： Seok, Byoungjin Lee, Changhoon Korea Univ Dept Informat Secur Sch Cybersecur Seoul 02841 South Korea Seoul Natl Univ Sci & Technol Dept Comp Sci & Engn Seoul 01811 South Korea

Recently, differential-neural cryptanalysis, which combines deep learning with differential cryptanalysis, has gained attention as a powerful and practical cryptanalysis method. This approach offers the advantage of enabling deep learning to analyze cryptographic properties, traditionally demanding substantial time and expertise. Nevertheless, the black-box nature of deep learning models poses challenges for cryptanalysts in comprehending the construction of the differential dataset. In particular, since the differential dataset serves as the foundation for generating the neural distinguisher, there is a pressing need for an effective methodology to construct a high-quality differential dataset. In this paper, we propose a novel approach to construct a good differential dataset for differential-neural cryptanalysis. First, we conducted an analysis to find the difference between well-trainable differential datasets and other differential datasets using Principal Component Analysis (PCA) and K-means clustering. Building upon our analysis results, we proposed the exploring algorithm for the generation of well-trainable differential dataset. This proposed algorithm assesses the input differences within the differential dataset by identifying significant principal components. If such components are found, a cluster evaluation is performed on the differential dataset. In our experiments, the proposed algorithm successfully identified favorable input differences, leading to improved accuracy in neural distinguisher training for SPECK and SIMON. Compared to the performance of the existing Gohr's neural input difference algorithm, our proposed algorithm was more effective in finding good input differences with higher accuracy. From the perspective of execution time, it showed an improvement of approximately 30%.

关键词： Training Principal component analysis eigenvalues and eigenfunctions Deep learning Cryptography Covariance matrices Ciphers Differential-neural cryptanalysis neural distinguisher principal component analysis k-means clustering

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Enhancing the Small-Signal Stability of Power Grids via Optimally Coordinating Inverter-Based Resources

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IEEE TRANSACTIONS ON SUSTAINABLE ENERGY 2025年第1期16卷 17-31页

作者： Yuan, Hui Xin, Huanhai Li, Zhiyi Li, Shiyang Dai, Jiang Gao, Huisheng Zhejiang Univ Coll Elect Engn Hangzhou 310027 Peoples R China China Southern Power Grid Elect Power Res Inst Guangzhou 510663 Peoples R China Guizhou Elect Power Dispatching & Commun Bur Guiyang 550000 Peoples R China

Modern power systems with the high penetration of inverter-based resources (IBRs) commonly face phase-lock loops (PLLs)-dominated small-signal stability issues, especially in low short-circuit grids. These issues can be addressed by refining controllers' design of IBRs, which however fails to be effective when power grids are operating under some critical conditions. To this end, this paper presents a novel optimization model for coordinating active power outputs (i.e., operation adjustment) of IBRs while satisfying small-signal stability constraints (SSSCs). In particular, SSSCs are formulated based on a new metric that quantifies the small-signal stability from the viewpoint of grid strength, which is especially suitable for those "black-boxed" IBRs. To reduce the problem-solving complexity due to the inherent discontinuity and nonlinearity, a sequential solution approach is proposed to decompose the original optimization problem into a sequence of sub-optimization problems (SOPs). Also, a dynamical-region-adjustment method and a convex-relaxing method are integrated to ensure the existence of feasible solutions and further enhance the solution efficiency. Finally, the performance of the proposed method is verified based on two test power systems.

关键词： Power system stability Optimization Stability criteria eigenvalues and eigenfunctions State-space methods Power system dynamics Power grids Inverter-based resource (IBR) operation adjustment small-signal stability grid strength

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Defect-induced modification of electronic and optical properties of CeO2 unveiled by many-body Green's function theory

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JOURNAL OF CHEMICAL PHYSICS 2025年第5期162卷 054107页

作者： Zhang, Mengyu Song, Yiting Jiang, Ya-nan Ma, Yuchen Shandong Univ Sch Chem & Chem Engn Jinan 250100 Peoples R China

We explore the impact of point defects, including oxygen vacancies (Ov), cerium interstitials (Ce-int), and hydroxyl groups (Hy), on the electronic and optical properties of bulk CeO2 using many-body Green's function theory (GW method and Bethe-Salpeter equation). Although these three defects all produce occupied electronic levels near the conduction band minimum, they impose quite different effects. Ov and Ce-int induce strong peaks in the low-energy region of the imaginary part of the microscopic dielectric function, indicating stronger electronic screening compared to the pristine CeO2. This causes pronounced narrowing of the bandgap, e.g., by 0.8 eV in G(0)W(0) and 1.6 eV in the eigenvalue self-consistent GW for Ov. Comparatively, Hy affects little electronic screening and bandgap at different levels of GW calculations. For the lowest several 4f orbitals, the exchange part of the self-energy (|Sigma(x)| > 9 eV) in GW is much stronger than the correlation part (|Sigma(c)| < 5 eV) for Ov and Ce-int, while |Sigma(c)| is much stronger than |Sigma(x)| instead for the pristine CeO2 and Hy. Quasiparticle weights in Ov and Ce-int decrease by a large quantity compared to the pristine CeO2. Consideration of Ov and Ce-int might to some extent relieve the discrepancy between the GW bandgap of the pristine CeO2 and the experimental gap. Ov and Ce-int could reduce the excitonic binding energy several times and result in optical absorption, which corresponds to the experiments.

关键词： eigenvalues and eigenfunctions

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Unravelling chain confinement and dynamics of weakly entangled polymers in one component nanocomposites

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SOFT MATTER 2025年 2025 Mar 13页

作者： Kruteva, M. Monkenbusch, M. Sharma, A. Allgaier, J. Hoffmann, I. Rosi, B. Dulle, M. Porcar, L. Matsarskaia, O. Richter, D. Forschungszentrum Julich Julich Ctr Neutron Sci D-52428 Julich Germany CSIR Natl Chem Lab Pune 411008 Maharashtra India Inst Laue Langevin ILL F-38000 Grenoble France European Spallat Source ESS Partikelgatan 2 S-22484 Lund Sweden

Structure and dynamics of polymer chains grafted to a nanoparticle (NP) surface in one component nanocomposites (OCNC) are investigated by small angle scattering (SAXS, SANS) and neutron spin echo (NSE). The OCNC were realized by self-assembly of block-copolymers and subsequent cross-linking of the core. The sizes of the resulting NPs were narrowly distributed. Owing to equal core and shell volumes the melt structure is that of a concentrated colloidal dispersion of cores. The melt structure could be reasonably well described by a Percus-Yevick structure factor. In order to access more deeply the dynamics, three differently labeled materials with labels at the inner- or outer part and the whole graft were studied. The experimental data were evaluated in terms of models allowing for site dependent friction. For this purpose, the Langevin equation containing a friction profile was solved and the dynamic structure factor in terms of its eigenvalues and eigenvectors was compared to the data. The evaluation shows increased friction towards the grafting points. In addition, topological restrictions of motion due to the dense arrangements of micellar cores and the presence of neighboring chains were considered and compared with those of a corresponding melt. Assuming homogenous relaxation of all grafts did not yield a satisfactory data description, but rather at least two differently relaxing chain ensembles had to be considered.

关键词： eigenvalues and eigenfunctions

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Fine settling particle transport in wetland flows: Effects of vegetation and settling velocity

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PHYSICS OF FLUIDS 2025年第3期37卷

作者： Huang, Shan Guo, Jinlan Macau Univ Sci & Technol Fac Innovat Engn Macau Peoples R China Natl Univ Singapore Dept Civil & Environm Engn Singapore Singapore

Prediction of particle transport in wetland flows has numerous applications in ecological engineering practice. The present work extends earlier investigations [Guo et al., "Dispersion in a vegetated flow of solute from a continuous source with bed absorption," J. Hydrol. 617, 129027 (2023) and Guo and Chen, "Solute dispersion from a continuous release source in a vegetated flow: An analytical study," Water Resour. Res. 58, e2021WR030255 (2022)] to analytically examine the transport process of fine settling particles from a continuous release source in wetland flows. By including the term of longitudinal diffusion, the second-order linear ordinary differential equations are analytically solved. The solution is validated by previous numerical and experimental results. The steady-state vertical mean and two-dimensional concentration distribution are explicitly examined, along with the influence of vegetation factor (a factor which is proportional to the square root of the vegetation stress;higher canopy densities lead to higher values) and settling velocity on concentration distribution. Results show that the steady-state concentration field reaches the stable value at the downstream dimensionless location of about x=0.5. The stable concentration value is larger with the smaller value of vegetation factor. The two-dimensional concentration field illustrates a layered distribution and more particles are concentrated on the bed wall layer under the effect of settling velocity. The stable vertical concentration profile is analogous to the zeroth-order eigenfunction. The steady vertical concentration solution can be used to predict the suspended sediment concentration profile. The findings reveal potential applications in environmental and industrial settings, such as wetland soil and water conservation, as well as ecological restoration.

关键词： eigenvalues and eigenfunctions

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