摘要：
To deal with the nonlinear coupling, strong disturbances and parametric uncertainties existing in the multi-motor web-winding system, a robust decentralized $H_\infty $ control method is proposed in this paper. First, the whole web-winding system is considered as a synthetic system composed of several subsystems. Giving that some parameters are time dependent and set points are modified during the winding process, each subsystem can be seen as a dynamic interval system and interval matrix is introduced. Then, a robust decentralized $H_\infty $ controller is designed to attenuate tension fluctuations introduced by the external disturbances and interaction between two consecutive subsystems. Sufficient condition for the existence of robust decentralized $H_\infty $ control law is presented in terms of linear matrix inequality. Finally, some simulations and experiments are conducted with the conventional decentralized controller and the proposed controller. The comparative results show that the proposed control scheme greatly improves the control performance of the web tensions.
关键词：
Most probable point (MPP);performance measure approach (PMA);reliability-based design optimization (RBDO);time-variant reliability;stochastic process
摘要：
Although a series of decoupled or single loop methods have been developed for reliability-based design optimization (RBDO) problems to improve the computational efficiency, it seems hard to extend these strategies to time-variant RBDO due to the complexity of the problems brought by the involvement of time. This paper proposes a new approach for time-variant reliability-based design optimization, expecting to provide an efficient tool for design of some complex structure under time-variant uncertainties. The main idea of the proposed method is the definition of the equivalent most probable point (EMPP). With the EMPP, the original time-variant RBDO problem can be transformed into an equivalent time-invariant RBDO problem formulated by performance measure approach (PMA). Hence, the existing PMA-based time-invariant RBDO methods can be applied to solve the equivalent problem. Therefore, those RBDO methods can be easily extended to time-variant RBDO problems, and hence the computational cost can be effectively reduced. Finally, two numerical examples and an engineering application are used to demonstrate the effectiveness of the proposed method.
摘要：
This paper develops an uncertainty propagation analysis method to analyze transmit/receive (T/R) modules with uncertain parameters, such as variability and tolerances in the physical parameters and geometry produced in the manufacturing processes. The method is a combination of the variance decomposition-based sensitivity analysis and the moment-based arbitrary polynomial chaos (MBaPC). First, the electromagnetic simulation model of a practical T/R module is created. Secondly, based on the model, the sensitivity analysis is carried out to determine the sensitive parameters to the amplitude difference and the phase difference between the input and output electromagnetic signal. Thirdly, their four order statistical moments are calculated using the MBaPC. At last, according to the maximum entropy principle, the statistical moments are used to fit the probability distribution functions of the amplitude difference and the phase difference of the T/R module. The results computed by MBaPC have been validated accurate and efficient compared with Monte Carlo simulation approach.
摘要：
Parametric correlation exists widely in engineering problems. This paper presents an approach of evidence-theory-based design optimization (EBDO) with parametric correlations, which provides an effective computational tool for the structural reliability design involving epistemic uncertainties. According to the existing samples, the most fitting copula function is selected to formulate the joint basic probability assignment (BPA) of the correlated variables. The joint BPA is applied in the constraint reliability analysis, and an approximate technology is given to enhance the efficiency. A decoupling strategy is proposed for transforming the nested optimization of EBDO into a sequential iterative process of deterministic optimization and reliability analysis. The effectiveness of the proposed approach is demonstrated through two numerical examples and an engineering application.
关键词：
Uncertainty propagation;Multimodal probability density function;Convergence mechanism;Sparse grid numerical integration;Maximum entropy method
摘要：
In practical engineering applications, random variables may follow multimodal distributions with multiple modes in the probability density functions, such as the structural fatigue stress of a steel bridge carrying both highway and railway traffic and the vibratory load of a blade subject to stochastic dynamic excitations, etc. Traditional uncertainty propagation methods are mainly used to treat random variables with only unimodal probability density functions, which, therefore, tend to result in large computational errors when multimodal probability density functions are involved. In this paper, an uncertainty propagation method is developed for problems in which multimodal probability density functions are involved. Firstly, the multimodal probability density functions of input random variables are established using the Gaussian mixture model. Secondly, the uncertainties of the input random variables are propagated to the response function through an integration of the sparse grid numerical method and maximum entropy method. Finally, the convergence mechanism is developed to improve the uncertainty propagation accuracy step by step. Two numerical examples and one engineering application are studied to demonstrate the effectiveness of the proposed method.
摘要：
BACKGROUND This study assessed lung models for the influence of respiratory mechanics and inspiratory effort on breathing pattern and simulator-ventilator cycling synchronization in non-invasive ventilation. MATERIAL AND METHODS A Respironics V60 ventilator was connected to an active lung simulator modeling mildly restrictive, severely restrictive, obstructive and mixed obstructive/restrictive profiles. Pressure-support ventilation (PSV) and proportional-assist ventilation (PAV) were set to obtain similar tidal volume (VT). PAV was applied at flow assist (FA) 40-90% of resistance (Rrs) and volume assist (VA) 40-90% of elastance (Ers). Measurements were performed with system air leak of 25-28 L/minute. Ventilator performance and simulator-ventilator asynchrony were evaluated. RESULTS At comparable VT, PAV had slightly lower peak inspiratory flow and higher driving pressure compared with PSV. Premature cycling occurred in the obstructive, severely restrictive and mildly restrictive models. During PAV, time for airway pressure to achieve 90% of maximum during inspiration (T90) in the severely restrictive model was shorter than those of the obstructive and mixed obstructive/restrictive models and close to that measured in the PSV mode. Increasing FA level reduced inspiratory trigger workload (PTP(3)(0)(0)) in obstructive and mixed obstructive/restrictive models. Increasing FA level decreased inspiratory time (TI) and tended to aggravate premature cycling, whereas increasing VA level attenuated this effect. CONCLUSIONS PAV with an appropriate combination of FA and VA decreases work of breathing during the inspiratory phase and improves simulator-ventilator cycling synchrony. FA has greater impact than VA in the adaptation to inspiratory effort demand. High VA level might help improve cycling synchrony.
摘要：
The conventional robust optimization methods usually focus on problems with unimodal random variables. In real applications, input random variables may follow multimodal distributions with multiple peaks in their probability density. When multimodal random variables are involved, the conventional methods, such as the mean-variance-based methods, will be not accurate. This paper presents an efficient robust optimization method, which provides a potential computational tool for engineering problems involving multimodal random variables. A robustness metric is formulated by introducing the concept of accepting/rejecting the limit to calculate the failure probability of the performance response, which can directly capture the multimodal characteristics of the performance. A second-order higher moment method is presented to efficiently conduct the probability calculation in the inner loop of design optimization. The proposed decoupling strategy drives the probability calculation and the design optimization sequentially and alternately. This method is applied to the three micromachine design problems, including a sweat-rate sensor, a piezoelectric sensor, and an image sensing module. The numerical results show that the method has excellent engineering practicality due to the comprehensive performance in terms of efficiency, accuracy, and convergence.
期刊：
IEEE Transactions on Systems, Man, and Cybernetics: Systems,2018年50(12):5162-5171 ISSN：2168-2216
通讯作者：
Lu, Xinjiang;Fan, Bin
作者机构：
[Lu, Xinjiang; Ming, Li; Lu, XJ; Fan, Bin; Hu, Tete] Cent South Univ, Sch Mech & Elect Engn, State Key Lab High Performance Complex Mfg, Changsha 410083, Hunan, Peoples R China.;[Fan, Bin] Hunan City Univ, Dept Mech Design Mfg & Automat, Yiyang 413002, Peoples R China.
通讯机构：
[Lu, XJ; Fan, B] C;[Fan, Bin] H;Cent South Univ, Sch Mech & Elect Engn, State Key Lab High Performance Complex Mfg, Changsha 410083, Hunan, Peoples R China.;Hunan City Univ, Dept Mech Design Mfg & Automat, Yiyang 413002, Peoples R China.
关键词：
Cluster;Collaboration;Collaborative work;Data models;Manufacturing;Noise measurement;Robustness;Support vector machines;collaborative learning;least squares support vector machine (LS-SVM);relative density degree;robustness
摘要：
The least squares support vector machine (LS-SVM) is often employed to model data with a nonlinear distribution using a divide-and-conquer strategy. However, when nonlinear data are contaminated by either noise or outliers, LS-SVM is often an ineffective approach due to a lack of robustness. In this paper, a collaborative learning-based clustered LS-SVM method is proposed for modeling of nonlinear processes that are subject to noise or outliers. First, a large-scale dataset is divided into several subsets and the data distribution of each subset is estimated. A robust LS-SVM is then developed to represent each subset using this distributional information. A global model is further constructed through integration of all submodels, whose continuity and smoothness are ensured by the development of the collaborative learning technique. As a result, the proposed method considers both the nonlinear distribution of data and the robustness of each submodel, and ensures the continuity and smoothness of the global model. Thus, it can effectively model nonlinear data that is subject to either noise or outliers. As further validation of this approach, both artificial and real cases demonstrated its effectiveness.
摘要：
Conventional decoupling approaches usually employ first-order reliability method to deal with probabilistic constraints in a reliability-based design optimization problem. In first-order reliability method, constraint functions are transformed into a standard normal space. Extra non-linearity introduced by the non-normal-to-normal transformation may increase the error in reliability analysis and then result in the reliability-based design optimization analysis with insufficient accuracy. In this article, a decoupling approach is proposed to provide an alternative tool for the reliability-based design optimization problems. To improve accuracy, the reliability analysis is performed by first-order asymptotic integration method without any extra non-linearity transformation. To achieve high efficiency, an approximate technique of reliability analysis is given to avoid calculating time-consuming performance function. Two numerical examples and an application of practical laptop structural design are presented to validate the effectiveness of the proposed approach.
摘要：
A novel LS-SVM control method is proposed for general unknown nonlinear systems. A linear kernel LS-SVM model is firstly developed for input/output (I/O) approximation. The LS-SVM control law is then derived directly from this developed model without any approximation and assumption. It further proves that the control error is fully equal to the LS-SVM modeling error. This means that a desirable control performance can be achieved because the LS-SVM has been proven to have an outstanding modeling ability in the previous studies. Case studies finally demonstrate the effectiveness of the proposed LS-SVM control approach.
作者机构：
[Zhong, WB] Hunan Univ, Coll Mat Sci & Engn, Changsha 410082, Peoples R China.;Hunan City Univ, Dept Mech, Yiyang 413000, Peoples R China.;Beijing Inst Chem Technol, Dept Polymer Sci, Beijing 100029, Peoples R China.
通讯机构：
[Zhong, WB] H;Hunan Univ, Coll Mat Sci & Engn, Changsha 410082, Peoples R China.
摘要：
Polypyrrole (PPy) nanowire networks have been synthesized in high yield (higher than 90%) by chemical oxidative polymerization of pyrrole in the presence of hexadecyltrimethylammonium bromide (HTAB) and organic diacids (oxalic acid, tartaric acid, or glutaric acid) and triacid (citric acid). The diameter of nanowire is 60−90 nm. The influence of reaction conditions, such as polymerization temperature, polymerization time, and the molar ratios of HTAB to organic acids and pyrrole, on the morphologies of the PPy nanowire networks has been systematically investigated. In addition, the interconnected PPy nanoparticles are prepared without using HTAB. The film of PPy nanowire networks and nanoparticles is superhydrophilic. A plausible formation mechanism of PPy nanowire networks is discussed.
摘要：
Summary: Polyaniline (PANI) nanowires and sub‐micro/nanostructured dendrites are synthesized and immobilized on PP‐g‐PAA film surfaces via routine oxidative polymerization of aniline under different conditions, where grafting poly(acrylic acid) (PAA) served as a template and dopant, and SDS as a surfactant. The immobilized PANI enhances the surface hydrophilicity of the poly(propylene) (PP) films, and a superhydrophilic surface is obtained in this way. The mechanism of forming different morphologies of PANI and of correspondingly obtaining a superhydrophilic surface are briefly discussed. FESEM image shows the PANI sub‐micro/nanostructured dendrites immobilized on the surfaces of PP films. The modified surface is highly hydrophilic with a water contact angle of 3°.
