| 1. |
- Nie, Linlin, et al.
(author)
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Improved Nonlinear Extended Observer Based Adaptive Fuzzy Output Feedback Control for a Class of Uncertain Nonlinear Systems With Unknown Input Hysteresis
- 2023
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In: IEEE Transactions on Fuzzy Systems. - 1941-0034 .- 1063-6706. ; 31:10, s. 3679-3689
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Journal article (peer-reviewed)abstract
- This study focuses on the problem of adaptive fuzzy dynamic surface output feedback control for a class of uncertain nonlinear systems subjected to unknown input hysteresis. A Prandtl-Ishlinskii (PI) model is applied to the uncertain nonlinear system for describing the unknown input hysteresis, making the controller design feasible. In addition, a nonlinear extended state observer (NESO) is designed for simultaneously estimating the unmeasurable states and generalized disturbances, including the nonlinear hysteresis term of the PI model and external disturbances. In addition, a novel nonlinear function is designed to replace fal(·) function of the general NESO to address a modification that increases the convergence speed. Considering the incorporation of the improved nonlinear extended state observer (INESO), an adaptive output feedback control scheme is proposed based on fuzzy logic system and dynamic surface techniques. A command filter is employed to avoid the 'explosion of complexity' problem inherent in the backstepping technique, while compensating the filtering error caused by adopting the filter. The Lyapunov approach is used to demonstrate the stability of the entire closed-loop system. Experiments regarding a piezoelectric micropositioning stage are conducted, the results of which illustrate that the proposed adaptive fuzzy output feedback control method can guarantee a satisfactory tracking performance.
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| 2. |
- Wang, Yifan, et al.
(author)
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Composite Data Driven-based Adaptive Control for a Piezoelectric Linear Motor
- 2022
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In: IEEE Transactions on Instrumentation and Measurement. - 1557-9662 .- 0018-9456. ; 71
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Journal article (peer-reviewed)abstract
- Piezoelectric linear motors play an important role in ultra-precision manufacturing technology. However, the complex nonlinear relationship between the input and output of the piezoelectric linear motors limits their further application. In this paper, to achieve precise motion control for a piezoelectric linear motor, a composite data driven-based adaptive control method is proposed, consisting of a correction controller, model free adaptive controller (MFAC), and low pass filter. The proposed control method addresses the demand for a precise model of the piezoelectric linear motor and solely relies on the linear model and input/output measurement data. First, an experimental test is implemented to analyze the complex nonlinearity between input and output signals of the controlled system, and a correction control is employed based on the dynamic linear sub-model of the piezoelectric linear motor to improve its dynamic and static characteristics. Then, to avoid the influence of unmodeled dynamics, such as inherent nonlinearity and external vibration, a MFAC is established as a feedback controller using data driven technology. In addition, a low pass filter is incorporated into the feedback loop to eliminate high frequency measurement noise in the system, thus improving the transient response of the MFAC method. Finally, the theoretical analysis of the error convergence is presented. The effectiveness of the proposed method is verified via comparisons with a correction control method, correction control-based digital sliding-mode control method, and correction control-based MFAC method. The experimental results indicate that the proposed control method is suitable for engineering applications. In particular, the root-mean-square error (RMSE) for the third-order S-curve tracking using the proposed is reduced by more than 15%, compared with the RMSEs for the cases with contrast control methods.
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| 3. |
- Wang, Yifan, et al.
(author)
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Time delay recursive neural network-based direct adaptive control for a piezo-actuated stage
- 2023
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In: Science China Technological Sciences. - 1869-1900 .- 1674-7321. ; 66:5, s. 1397-1407
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Journal article (peer-reviewed)abstract
- Piezo-actuated stage is a core component in micro-nano manufacturing field. However, the inherent nonlinearity, such as rate-dependent hysteresis, in the piezo-actuated stage severely impacts its tracking accuracy. This study proposes a direct adaptive control (DAC) method to realize high precision tracking. The proposed controller is designed by a time delay recursive neural network. Compared with those existing DAC methods designed under the general Lipschitz condition, the proposed control method can be easily generalized to the actual systems, which have hysteresis behavior. Then, a hopfield neural network (HNN) estimator is proposed to adjust the parameters of the proposed controller online. Meanwhile, a modular model consisting of linear submodel, hysteresis submodel, and lumped uncertainties is established based on the HNN estimator to describe the piezo-actuated stage in this study. Thus, the performance of the HNN estimator can be exhibited visually through the modeling results. The proposed control method eradicates the adverse effects on the control performance arising from the inaccuracy in establishing the offline model and improves the capability to suppress the influence of hysteresis on the tracking accuracy of piezo-actuated stage in comparison with the conventional DAC methods. The stability of the control system is studied. Finally, a series of comparison experiments with a dual neural networks-based data driven adaptive controller are carried out to demonstrate the superiority of the proposed controller.
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| 4. |
- Yu, Yewei, et al.
(author)
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Neural network based iterative learning control for magnetic shape memory alloy actuator with iteration-dependent uncertainties
- 2023
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In: Mechanical Systems and Signal Processing. - : Elsevier BV. - 0888-3270 .- 1096-1216. ; 187
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Journal article (peer-reviewed)abstract
- The magnetic shape memory alloy based actuator (MSMA-BA) is an indispensable component mechanism for high-precision positioning systems as it possesses the advantages of high precision, low energy consumption, and large stroke. However, hysteresis is an intrinsic property of MSMA material, which seriously affects the positioning accuracy of MSMA-BA. In this study, we propose a multi meta-model approach incorporating the nonlinear auto-regressive moving average with exogenous inputs (NARMAX) and Bouc–Wen (BW) models to describe the complex dynamic hysteresis of MSMA-BA. In particular, the BW model is introduced into the NARMAX model as an exogenous variable function, and a wavelet neural network (WNN) is adopted to construct the nonlinear function of the multi meta-model. In addition, iterative learning control is combined with a WNN to improve its convergence speed. A two-valued function is employed in the controller design process, so as to make use of history iteration information in updating control input. The main contribution of this study is the convergence analysis of the proposed iteration learning controller with iteration-dependent uncertainties (non-strict repetition of the initial state and varying iteration length). The experiments conducted on the MSMA-BA illustrate the validity of the proposed control scheme.
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| 5. |
- Zhang, Juqing, et al.
(author)
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Super-enhancers conserved within placental mammals maintain stem cell pluripotency
- 2022
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In: Proceedings of the National Academy of Sciences of the United States of America. - : Proceedings of the National Academy of Sciences (PNAS). - 0027-8424 .- 1091-6490. ; 119:40
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Journal article (peer-reviewed)abstract
- Despite pluripotent stem cells sharing key transcription factors, their maintenance involves distinct genetic inputs. Emerging evidence suggests that super-enhancers (SEs) can function as master regulatory hubs to control cell identity and pluripotency in humans and mice. However, whether pluripotency-associated SEs share an evolutionary origin in mammals remains elusive. Here, we performed comprehensive comparative epigenomic and transcription factor binding analyses among pigs, humans, and mice to identify pluripotency-associated SEs. Like typical enhancers, SEs displayed rapid evolu-tion in mammals. We showed that BRD4 is an essential and conserved activator for mammalian pluripotency-associated SEs. Comparative motif enrichment analysis revealed 30 shared transcription factor binding motifs among the three species. The majority of transcriptional factors that bind to identified motifs are known regulators associated with pluripotency. Further, we discovered three pluripotency-associated SEs (SE-SOX2, SE-PIM1, and SE-FGFR1) that displayed remarkable conservation in pla-cental mammals and were sufficient to drive reporter gene expression in a pluripotency-dependent manner. Disruption of these conserved SEs through the CRISPR-Cas9 approach severely impaired stem cell pluripotency. Our study provides insights into the understanding of conserved regulatory mechanisms underlying the maintenance of plu-ripotency as well as species-specific modulation of the pluripotency-associated regula-tory networks in mammals.
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| 6. |
- Zhao, Xue, et al.
(author)
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BCN-Encapsulated Nano-nickel Synergistically Promotes Ambient Electrochemical Dinitrogen Reduction
- 2020
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In: ACS Applied Materials and Interfaces. - : AMER CHEMICAL SOC. - 1944-8244 .- 1944-8252. ; 12:28, s. 31419-31430
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Journal article (peer-reviewed)abstract
- The electricity provided by solar or wind power can drive nitrogen in the atmosphere, combining with ubiquitous water to form ammonia, and distributed production methods can alleviate the irreversible damage to the environment caused by the energy-intensive Haber-Bosch process. Here, we have designed a novel Ni-doped BCN heterojunction (S/M-BOPS-1) as a catalyst for the electrochemical nitrogen reduction reaction (NRR). The ammonia yield rate and Faraday efficiency in NRR driven by S/M-BOPS-1 reach up to 16.72 mu g(-1) h(-1) cm(-2) and 13.06%, respectively. Moreover, S/M-BOPS-1 still maintains high NRR activity and excellent stability after recycling for eight times and long-time operation of 12 h. Using density functional theory calculations, we reveal a possible NRR path for N-2 to NH3 on Ni, BCN, and the S/M-BOPS-1 composite surfaces. The interaction between the BCN matrix and Ni nanoparticles promotes a synergetic effect for the electrochemical NRR efficiency due to the partial electron transfer from the Ni particles to BCN that inhibits hydrogen evolution reaction and decreases the rate-determining step on Ni surfaces toward NRR by similar to 1.5 times. Therefore, efficient NRR performance can be achieved by tuning the electronic properties of non-noble metals via the formation of a heterointerface.
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| 7. |
- Zhao, Xue, et al.
(author)
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Potassium ions promote electrochemical nitrogen reduction on nano-Au catalysts triggered by bifunctional boron supramolecular assembly
- 2020
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In: Journal of Materials Chemistry A. - : Royal Society of Chemistry (RSC). - 2050-7488 .- 2050-7496. ; 8:26, s. 13086-13094
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Journal article (peer-reviewed)abstract
- The electrochemical way of reducing nitrogen to ammonia presents green and economic advantages to dial down irreversible damage caused by the energy-intensive Haber-Bosch process. Here, we introduce an advanced catalyst CB[7]-K-2[B12H12]@Au with highly dispersed and ultrafine nano-gold. The CB[7]-K-2[B12H12]@Au electrochemically driven ammonia yield and Faraday efficiency is as high as 41.69 mu g h(-1)mg(cat.)(-1)and 29.53% (at -0.4 Vvs.RHE), respectively, reaching the US Department of Energy (DOE) utility index of ambient ammonia production along with excellent cycle stability and tolerance that indicates a high potential of industrial practical value. Experimental results and theoretical calculations show that the key to an excellent electrochemical nitrogen reduction performance lies in the smart design of the CB[7]-K-2[B12H12]@Au catalyst combining the stable substrate anchored Au nanoparticles and K(+)ions that effectively prevent the hydrogen evolution reaction and polarize *N(2)leading to lowering of the rate determining step. This research will promote the further development of electrochemical ammonia production with low environmental impact.
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