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Harmonic drive systems (HDS) are high-precision robotic transmissions featuring compact size and high gear ratios. However, issues like kinematic transmission errors hamper their precision performance. This article focuses on data-driven modeling and analysis of an HDS to improve kinematic error compensation. The background introduces HDS mechanics, nonlinear attributes, and modeling approaches from literature. The HDS dynamics are derived using Lagrange equations. Experiments under aggressive conditions provide training data exhibiting deterministic patterns. Various linear and nonlinear models have been developed. The best-performing model, based on a nonlinear neural network, achieves over 98\% accuracy for one-step predictions on both the training and validation data sets. A phenomenological model separates the kinematic error into a periodic pure part and flexible part. Apart from implementation of estimated transmission error injection compensation, novel compensation mechanisms policies for the kinematic error are analyzed and proposed, including nonlinear model predictive control and frequency loop-shaping. The feedback loop is analyzed to select the controller for vibration mitigation. Main contributions include the nonlinear dynamics derivation, data-driven nonlinear modeling of flexible kinematic errors, repeatable experiment design, and proposed novel compensation mechanism and policies. Future work involves using physics-informed neural networks, sensitivity analysis, full life-cycle monitoring, and extracting physical laws directly from data., Comment: arXiv admin comment: This artucle has been removed by arXiv administrators as the submitter did not have the rights to agree to the license at the time of submission

The digital transformation of pharmaceutical industry is a challenging task due to the high complexity of involved elements and the strict regulatory compliance. Maintenance activities in the pharmaceutical industry play an essential role in ensuring product quality and integral functioning of equipment and premises. This paper first identifies the key challenges of digitalization in pharmaceutical industry and creates the corresponding problem space for key involved elements. A literature review is conducted to investigate the mainstream maintenance strategies, digitalization models, tools and official guidance from authorities in pharmaceutical industry. Based on the review result, a semantic-driven digitalization framework is proposed aiming to improve the digital continuity and cohesion of digital resources and technologies for maintenance activities in the pharmaceutical industry. A case study is conducted to verify the feasibility of the proposed framework based on the water sampling activities in Merck Serono facility in Switzerland. A tool-chain is presented to enable the functional modules of the framework. Some of the key functional modules within the framework are implemented and have demonstrated satisfactory performance. As one of the outcomes, a digital sampling assistant with web-based services is created to support the automated workflow of water sampling activities. The implementation result proves the potential of the proposed framework to solve the identified problems of maintenance digitalization in the pharmaceutical industry.

This paper investigates the finite-time adaptive fuzzy tracking control problem for a class of pure-feedback system with full-state constraints. With the help of Mean-Value Theorem, the pure-feedback nonlinear system is transformed into strict-feedback case. By employing finite-time-stable like function and state transformation for output tracking error, the output tracking error converges to a predefined set in a fixed finite interval. To tackle the problem of state constraints, integral Barrier Lyapunov functions are utilized to guarantee that the state variables remain within the prescribed constraints with feasibility check. Fuzzy logic systems are utilized to approximate the unknown nonlinear functions. In addition, all the signals in the closed-loop system are guaranteed to be semi-global ultimately uniformly bounded. Finally, two simulation examples are given to show the effectiveness of the proposed control strategy.

This brief constructs the adaptive backstepping control scheme for a class of pure-feedback systems with input delay and full state constraints. With the help of Mean Value Theorem, the pure-feedback system is transformed into strict-feedback one. Barrier Lyapunov functions are employed to guarantee all of the states remain constrained within predefined sets. By introducing the Pade approximation method and corresponding intermediate, the impact generated by input delay on the output tracking performance of the system can be eliminated. Furthermore, a low-pass filter driven by a newly-defined control input, is employed to generate the actual control input, which facilitates the design of backstepping control. To approximate the unknown functions with a desired level of accuracy, the fuzzy logic systems (FLSs) are utilized by choosing appropriate fuzzy rules, logics and so on. The minimal learning parameter (MLP) technique is employed to decrease the number of nodes and parameters in FLSs, and dynamic surface control (DSC) technique is leveraged to avoid so-called "explosion of complexity". Moreover, smooth robust compensators are introduced to circumvent the influences of external disturbance and approximation errors. By stability analysis, it is proved that all of signals in the closed-loop system are semi-globally ultimately uniform bounded, and the tracking error can be within a arbitrary small neighbor of origin via selecting appropriate parameters of controllers. Finally, the results of numerical illustration are provided to demonstrate the effectiveness of the designed method., Comment: arXiv admin note: text overlap with arXiv:2310.15407

We prove a comparison theorem between Greenberg--Benois $\mathcal{L}$-invariants and Fontaine--Mazur $\mathcal{L}$-invariants. Such a comparison theorem supplies an affirmative answer to a speculation of Besser--de Shalit.

We construct a Hecke-equivariant pairing on the overconvergent cohomology of Bianchi threefolds. Applying the strategy of Kim and Bella\"iche, we use this pairing to construct $p$-adic adjoint $L$-functions for Bianchi cuspforms and show that it detects the ramification locus of the cuspidal Bianchi eigenvariety over the weight space. Combining results of Barrera Salazar--Williams, we show a non-vanishing result of this $p$-adic adjoint $L$-function at certain points. Finally, we obtain a formula relating this pairing with the adjoint $L$-values of the corresponding cuspidal Bianchi eigenforms.

We introduce a theory of finite polynomial cohomology with coefficients in this paper. We prove several basic properties and introduce an Abel-Jacobi map with coefficients. As applications, we use such a cohomology theory to study arithmetics of compact Shimura curves over $\mathbb{Q}$, and simplify proofs of the works of Darmon-Rotger and Bertolini-Darmon-Prasanna.

We study the adjoint Bloch--Kato Selmer groups attached to a classical point in the cuspidal eigenvariety associated with $\mathrm{GSp}_{2g}$. Our strategy is based on the study of families of Galois representations on the eigenvariety, which is inspired by the book of J. Bellaiche and G. Chenevier.

The aim of this paper is twofold. We first present a construction of overconvergent automorphic sheaves for Siegel modular forms by generalising the perfectoid method, originally introduced by Chojecki-Hansen-Johansson for automorphic forms on compact Shimura curves over $\mathbf{Q}$. These sheaves are then verified to be isomorphic to the ones introduced by Andreatta-Iovita-Pilloni. Secondly, we establish an overconvergent Eichler-Shimura morphism for Siegel modular forms, generalising the result of Andreatta-Iovita-Stevens for elliptic modular forms.

In the present paper, we first construct a pairing on the space of analytic distributions associated with $\mathrm{GSp}_{2g}$. By considering the overconvergent parabolic cohomology groups and following the work of Johansson--Newton, we construct the cuspidal eigenvariety for $\mathrm{GSp}_{2g}$. The pairing on the analytic distributions then induces a pairing on some coherent sheaves of the cuspidal eigenvariety. As an application, we follow the strategy of Bella\"{i}che to study the ramification locus of the cuspidal eigenvariety over the corresponding weight space.

The effect of Coulomb interaction screening on non-relativistic free-free absorption is investigated by integrating the numerical continuum wave functions. The screened potential is taken to be in Debye-H\H{u}ckel (Yukawa) form with a screening length D. It is found that the values of the free-free Gaunt factors for different Debye screening lengths D for a given initial electron energy \eps_i and absorbing photon energy \omega, generally lie between those of the pure Coulomb field and field-free case. However, for initial electron energies below 0.1 Ry and fixed photon energy, the Gaunt factors show dramatic enhancements (broad and narrow resonances) in the vicinities of the critical screening lengths, Dnl, at which the energies of nl bound states in the potential merge into the continuum. These enhancements of the Gaunt factors can be significantly higher than their values in the unscreened (Coulomb) case over a broad range of \eps_i. The observed broad and narrow resonances in the Gaunt factors are related to the temporary formation of weakly bound (virtual) and resonant (quasi-bound) states of the low-energy initial electron on the Debye-H\H{u}ckel potential when the screening length is in the vicinity of Dnl., Comment: 11 pages, 5 figures, Physical Review A (accepted)