107 research outputs found

    Adaptive Sliding Mode Control Using Robust Feedback Compensator for MEMS Gyroscope

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    An adaptive sliding mode control using robust feedback compensator is presented for a MEMS gyroscope in the presence of external disturbances and parameter uncertainties. An adaptive controller with a robust term is used to improve the robustness of the control system and compensate the system nonlinearities. The proposed robust adaptive control can estimate the angular velocity and all the system parameters including damping and stiffness coefficients in the Lyapunov framework. In addition, standard adaptive control scheme without robust algorithm is compared with the proposed robust adaptive scheme in the aspect of numerical simulation and algorithm derivation. Numerical simulations show that the robust adaptive control has better robustness in the presence of external disturbances than the standard adaptive control

    The Comparative Study of Vibration Control of Flexible Structure Using Smart Materials

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    Considerable attention has been devoted to active vibration control using intelligent materials as PZT actuators. This paper presents results on active control schemes for vibration suppression of flexible steel cantilever beam with bonded piezoelectric actuators. The PZT patches are surface bonded near the fixed end of flexible steel cantilever beam. The dynamic model of the flexible steel cantilever beam is derived. Active vibration control methods: optimal PID control, strain rate feedback control (SRF), and positive position feedback control (PPF) are investigated and implemented using xPC Target real-time system. Experimental results demonstrate that the SRF and PPF controls have better performance in suppressing the vibration of cantilever steel beam than the optimal PID control

    A Novel Sliding Mode Control Technique for Indirect Current Controlled Active Power Filter

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    A novel sliding mode control (SMC) method for indirect current controlled three-phase parallel active power filter is presented in this paper. There are two designed closed loops in the system: one is the DC voltage controlling loop and the other is the reference current tracking loop. The first loop with a PI regulator is used to control the DC voltage approximating to the given voltage of capacitor, and the output of PI regulator through a low-pass filter is applied as the input of the power supply reference currents. The second loop implements the tracking of the reference currents using integral sliding mode controller, which can improve the harmonic treating performance. Compared with the direct current control technique, it is convenient to be implemented with digital signal processing system because of simpler system structure and better harmonic treating property. Simulation results verify that the generated reference currents have the same amplitude with the load currents, demonstrating the superior harmonic compensating effects with the proposed shunt active power filter compared with the hysteresis method

    Adaptive Control of MEMS Gyroscope Based on T-S Fuzzy Model

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    A multi-input multioutput (MIMO) Takagi-Sugeno (T-S) fuzzy model is built on the basis of a nonlinear model of MEMS gyroscope. A reference model is adjusted so that a local linear state feedback controller could be designed for each T-S fuzzy submodel based on a parallel distributed compensation (PDC) method. A parameter estimation scheme for updating the parameters of the T-S fuzzy models is designed and analyzed based on the Lyapunov theory. A new adaptive law can be selected to be the former adaptive law plus a nonnegative in variable to guarantee that the derivative of the Lyapunov function is smaller than zero. The controller output is implemented on the nonlinear model and T-S fuzzy model, respectively, for the purpose of comparison. Numerical simulations are investigated to verify the effectiveness of the proposed control scheme and the correctness of the T-S fuzzy model

    Robust H

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    The robust filtering problem for a class of uncertain discrete-time fuzzy stochastic systems with sensor nonlinearities and time-varying delay is investigated. The parameter uncertainties are assumed to be time varying norm bounded in both the state and measurement equations. By using the Lyapunov stability theory and some new relaxed techniques, sufficient conditions are proposed to guarantee the robustly stochastic stability with a prescribed H∞ performance level of the filtering error system for all admissible uncertainties, sensor nonlinearities, and time-varying delays. These conditions are dependent on the lower and upper bounds of the time-varying delays and are obtained in terms of a linear matrix inequality (LMI). Finally, two simulation examples are provided to illustrate the effectiveness of the proposed methods

    Topological Magnetoresistance of Magnetic Skyrmionic Bubbles

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    Magnetic skyrmions offer promising prospects for constructing future energy-efficient and high-density information technology, leading to extensive explorations of new skyrmionic materials recently. The topological Hall effect has been widely adopted as a distinctive marker of skyrmion emergence. Alternately, here we propose a novel signature of skyrmion state by quantitatively investigating the magnetoresistance (MR) induced by skyrmionic bubbles in CeMn2Ge2. An intriguing finding was revealed: the anomalous MR measured at different temperatures can be normalized into a single curve, regardless of sample thickness. This behavior can be accurately reproduced by the recent chiral spin textures MR model. Further analysis of the MR anomaly allowed us to quantitatively examine the effective magnetic fields of various scattering channels. Remarkably, the analyses, combined with the Lorentz transmission electronic microscopy results, indicate that the in-plane scattering channel with triplet exchange interactions predominantly governs the magnetotransport in the Bloch-type skyrmionic bubble state. Our results not only provide insights into the quantum correction on MR induced by skyrmionic bubble phase, but also present an electrical probing method for studying chiral spin texture formation, evolution and their topological properties, which opens up exciting possibilities for identifying new skyrmionic materials and advancing the methodology for studying chiral spin textures.Comment: 17 pages,5 figures,submitte

    Identification and validation of an immune-related gene prognostic signature for clear cell renal carcinoma

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    Clear Cell Renal Carcinoma (ccRCC) accounts for nearly 80% of renal carcinoma cases, and immunotherapy plays an important role in ccRCC therapy. However, the responses to immunotherapy and overall survival for ccRCC patients are still hard to predict. Here, we constructed an immune-related predictive signature using 19 genes based on TCGA datasets. We also analyzed its relationships between disease prognosis, infiltrating immune cells, immune subtypes, mutation load, immune dysfunction, immune escape, etc. We found that our signature can distinguish immune characteristics and predict immunotherapeutic response for ccRCC patients with better prognostic prediction value than other immune scores. The expression levels of prognostic genes were determined by RT-qPCR assay. This signature may help to predict overall survival and guide the treatment for patients with ccRCC

    Baichuan 2: Open Large-scale Language Models

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    Large language models (LLMs) have demonstrated remarkable performance on a variety of natural language tasks based on just a few examples of natural language instructions, reducing the need for extensive feature engineering. However, most powerful LLMs are closed-source or limited in their capability for languages other than English. In this technical report, we present Baichuan 2, a series of large-scale multilingual language models containing 7 billion and 13 billion parameters, trained from scratch, on 2.6 trillion tokens. Baichuan 2 matches or outperforms other open-source models of similar size on public benchmarks like MMLU, CMMLU, GSM8K, and HumanEval. Furthermore, Baichuan 2 excels in vertical domains such as medicine and law. We will release all pre-training model checkpoints to benefit the research community in better understanding the training dynamics of Baichuan 2.Comment: Baichuan 2 technical report. Github: https://github.com/baichuan-inc/Baichuan
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