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6th International Conference on Information Science and Technology (ICIST)

作者： Li, Canhe Zhao, Yongsheng Wang, Guofeng Fan, Yunsheng Bai, Yiming Dalian Maritime Univ Coll Informat Sci & Technol Dalian 116026 Peoples R China

ISBN: (纸本)9781509012244

This paper presents an adaptive Radial Basis Function (RBF) neural network controller for the nonlinear course control of unmanned surface vessel (USV) with modeling errors and unknown bounded environment disturbances. An adaptive RBF neural network system is employed to approximate the uncertain term induced by modeling errors and unknown bounded environment disturbances. It is theoretically proved that the proposed adaptive RBF neural network controller can make the USV be tracked the designed heading angle and turning rate with arbitrary accuracy, while guaranteeing the asymptotic stability of the closed-loop course tracking control system of USV. Comparative studies are carried out between the proposed control scheme and the PD control under the same control parameters, and the results show that the proposed control scheme has a good performance.

关键词： USV course tracking IMF neural network modeling errors environment disturbances

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Efficient reconstruction algorithms for three-dimensional tomographic imaging

Efficient reconstruction algorithms for three-dimensional to...

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作者： Helle Majander Aalto University

学位级别：博士

This thesis considers nonlinear parameter estimation problems arising from tomographic imaging modalities governed by elliptic partial differential equations. These are ill-posed inverse problems and hence their solution requires regularization or, in the Bayesian frame- work, incorporation of prior information about the to-be-reconstructed spatially varying parameter. In particular, if the parameter is known to have distinct inclusions in a constant background, we quantify such information by assuming that after discretization the parameter follows an edge-enhancing prior distribution. Moreover, we study how to recover from differ- ent kinds of errors in the data, since even small ones can be enough to ruin the reconstruction for an ill-posed tomographic imaging problem. We consider the solution ofthe investigated inverse problem to be the maximum a posteriori estimate for the parameter of interest, which can be found by solving a minimization problem. We propose to search for the minimizer by an iterative algorithm based on combining lineariza- tions of the forward model, lagged diffusivity steps and a priorconditioned Krylov subspace method (LSQR). By presenting examples from electrical impedance tomography (EIT), diffuse optical tomography (DOT) and quantitative photoacoustic tomography (QPAT), we demon- strate that such a method can be implemented efﬁciently enough to be feasible for solving large-scale three-dimensional problems. In addition, we use a conformal invariance result for the complete electrode model (CEM) of EIT to compensate for geometric modeling errors.

关键词： parameter estimation problem tomographic imaging edge-enhancing regularization modeling errors priorconditioning LSQR electrical impedance tomography complete electrode model diffuse optical tomography quantitative photoacoustic tomography

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Statistical Analysis of the MUSIC Algorithm in the Presence of modeling errors, Taking Into Account the Resolution Probability

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IEEE TRANSACTIONS ON SIGNAL PROCESSING 2010年第8期58卷 4156-4166页

作者： Ferreol, Anne Larzabal, Pascal Viberg, Mats THALES F-92700 Colombes France Universud CNRS ENS Cachan SATIE F-94235 Cachan France Chalmers Dept Signals & Syst S-41296 Gothenburg Sweden

This paper considers the statistical performance of the MUSIC method under the condition that two closely spaced sources impinging on an array of sensors are effectively resolved, i.e., the spectrum exhibits two peaks in the neighborhood of the true directions-of-arrival (DOA). The MUSIC algorithm is known to have an infinite resolution power in theory. However, in the presence of modeling errors, sources can not be resolved with certainty, even if the array correlation matrix is perfectly known. The focus of this paper is to predict the bias and variance of the DOA estimates taking into account the possible resolution failure of MUSIC. This performance prediction, based on our recent mathematical investigation, is new to the best of our knowledge. A general mathematical framework to derive closed form expressions of the bias and variance versus the model mismatch, conditioned on a general statistical resolution test is proposed. In order to illustrate our mathematical approach, statistical tests with one and two conditions, respectively, are investigated. The accuracy of the performance prediction is illustrated in a simulation study. It is found that the proposed approach outperforms the "classical" technique, which ignores the possible resolution failure of the MUSIC algorithm. Therefore, our results provide better tools for determining the necessary antenna calibration accuracy to achieve some targeted specifications on the estimator performance.

关键词： DOA estimation performances modeling errors MUSIC resolution

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ROBUSTNESS OF OPTIMIZED COLLISION AVOIDANCE LOGIC TO modeling errors

ROBUSTNESS OF OPTIMIZED COLLISION AVOIDANCE LOGIC TO MODELIN...

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29th Digital Avionics Systems Conference on Improving Our Environment through Green Avionics and ATM Solutions

作者： Kochenderfer, Mykel J. Chryssanthacopoulos, James P. Radecki, Peter P. MIT Lincoln Lab Lexington MA 02173 USA

ISBN: (纸本)9781424466177

Collision avoidance systems, whether for manned or unmanned aircraft, must reliably prevent collision while minimizing alerts. Deciding what action to execute at a particular instant may be framed as a multiple-objective optimization problem that can be solved offline by computers. Prior work has explored methods of efficiently computing the optimal collision avoidance logic from a probabilistic model of aircraft behavior and a cost function. One potential concern with using a probabilistic model to construct the logic is that the model may not adequately represent the real world. Inaccuracies in the model could lead to vulnerabilities in the system when deployed. This paper evaluates the robustness of collision avoidance optimization to modeling errors.

关键词： air traffic control collision avoidance collision avoidance error analysis manned aircraft modeling errors multiple objective optimization problem optimisation probabilistic model probability robust control robustness unmanned aircraft

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Trend and Bounds for Error Growth in Controlled Lagrangian Particle Tracking

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IEEE JOURNAL OF OCEANIC ENGINEERING 2014年第1期39卷 10-25页

作者： Szwaykowska, Klementyna Zhang, Fumin Georgia Inst Technol Sch Elect & Comp Engn Atlanta GA 30332 USA

This paper establishes the method of controlled Lagrangian particle tracking (CLPT) to analyze the offsets between physical positions of marine robots in the ocean and simulated positions of controlled particles in an ocean model. The offset, which we term the CLPT error, demonstrates distinguished characteristics not previously seen in drifters and floats that cannot be actively controlled. The CLPT error growth over time is exponential until it reaches a turning point that only depends on the resolution of the ocean model. After this turning point, the error growth slows down significantly to polynomial functions of time. In the ideal case, a theoretical upper threshold on exponential growth of CLPT error can be derived. These characteristics are proved theoretically, verified via simulation, and justified with ocean experimental data. The method of CLPT may be applied to improve the accuracy of ocean circulation models and the performance of navigation algorithms for marine robots.

关键词： Autonomous underwater vehicles (AUVs) stochastic systems Markov models model-based control modeling errors

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Postprandial performance of Dexcom® SEVEN® PLUS and Medtronic® Paradigm® Veo™: modeling and statistical analysis

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BIOMEDICAL SIGNAL PROCESSING AND CONTROL 2014年第1期10卷 322-331页

作者： Laguna, Alejandro J. Rossetti, Paolo Javier Ampudia-Blasco, F. Vehi, Josep Bondia, Jorge Univ Politecn Valencia Inst Univ Automat & Informat Ind Valencia 46022 Spain Valencia Clin Univ Hosp Dept Endocrinol Diabet Reference Unit Valencia 46010 Spain Univ Girona Inst Informat & Aplicac Girona 17071 Spain

Background: Minimizing excessive postprandial glucose excursion is still an unmet need in treating diabetes. This work addresses the analysis and modeling in the postprandial state of two commercial CGM devices. Methods: Twelve patients with type 1 diabetes were studied in the postprandial state on four different occasions under controlled conditions. Each time, we performed simultaneous glucose monitoring using the Dexcom SEVEN(R) PLUS (47 datasets) and the Medtronic Paradigm(R) Veo(TM) (42 datasets). The following statistical properties of the error signal were analyzed and modeled sequentially for the two devices: the lag time, the error stationarity, the error probability distribution and the time correlation. Finally, models were built for sensor simulation in silico studies. Results: Lag time followed an exponential probability distribution for both monitors (mu(sevenplus) = 108, mu(veo) = 1.69). Standard deviation and mean of the error signal, calculated as time-dependent signals across the population of sensors, were time-varying and correlated with the reference value and its rate of change, respectively. In both cases, a high variability of postprandial behaviors was observed. After non-stationarity compensation, a logistic distribution was obtained for the SEVEN(R) PLUS error (close to normal distribution). Regarding the Paradigm(R) Veo(TM), a multimodal distribution was obtained, which turned into normal after elimination of five "unstable" sensors. Finally, a first order autoregressive model fitted the SEVEN(R) PLUS error time-series while a third-order filter was necessary for the Paradigm(R) Veo(TM). Conclusions: The Paradigm(R) Veo(TM) device exhibited greater delay variability with higher delay time and higher probability of abnormal sensor behaviors as compared to the SEVEN(R) PLUS device. In both cases, the observed variability may have important clinical implications in postprandial performance. Therefore, further improvements are needed in calib

关键词： Continuous glucose monitoring Statistical modeling Error analysis Simulation modeling errors Biomedical Systems

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Bayesian anomaly detection in heterogeneous media with applications to geophysical tomography

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INVERSE PROBLEMS 2014年第11期30卷 114013-114013页

作者： Simon, Martin Johannes Gutenberg Univ Mainz Dept Math Mainz Germany

In this paper, we consider the problem of detecting a parameterized anomaly in an isotropic, stationary and ergodic conductivity random field via electrical impedance tomography. A homogenization result for a stochastic forward problem built on the complete electrode model is derived, which serves as the basis for a two-stage numerical method in the framework of Bayesian inverse problems. The novelty of this method lies in the introduction of an enhanced error model accounting for the approximation errors that result from reducing the full forward model to a homogenized one. In the first stage, a MAP estimate for the reduced forward model equipped with the enhanced error model is computed. Then, in the second stage, a bootstrap prior based on the first stage results is defined and the resulting posterior distribution is sampled via Markov chain Monte Carlo. We provide the theoretical foundation of the proposed method, discuss different aspects of a numerical implementation and present numerical experiments to support our findings.

关键词： inverse problems electrical impedance tomography statistical inversion modeling errors model reduction homogenization

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Kinetic isotope effects significantly influence intracellular metabolite ¹³C labeling patterns and flux determination

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BIOTECHNOLOGY JOURNAL 2013年第9期8卷 1080-U140页

作者： Wasylenko, Thomas M. Stephanopoulos, Gregory MIT Dept Chem Engn Cambridge MA 02139 USA

Rigorous mathematical modeling of carbon-labeling experiments allows estimation of fluxes through the pathways of central carbon metabolism, yielding powerful information for basic scientific studies as well as for a wide range of applications. However, the mathematical models that have been developed for flux determination from C-13 labeling data have commonly neglected the influence of kinetic isotope effects on the distribution of C-13 label in intracellular metabolites, as these effects have often been assumed to be inconsequential. We have used measurements of the C-13 isotope effects on the pyruvate dehydrogenase enzyme from the literature to model isotopic fractionation at the pyruvate node and quantify the modeling errors expected to result from the assumption that isotope effects are negligible. We show that under some conditions kinetic isotope effects have a significant impact on the C-13 labeling patterns of intracellular metabolites, and the errors associated with neglecting isotope effects in C-13-metabolic flux analysis models can be comparable in size to measurement errors associated with GC-MS. Thus, kinetic isotope effects must be considered in any rigorous assessment of errors in C-13 labeling data, goodness-of-fit between model and data, confidence intervals of estimated metabolic fluxes, and statistical significance of differences between estimated metabolic flux distributions.

关键词： Isotope Effects Isotopomer modeling Metabolic Engineering Metabolic Flux Analysis modeling errors

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Feedforward coefficient identification and nonlinear composite feedback control with applications to 3-DOF planar motor

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JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY 2013年第3期27卷 895-907页

作者： Li Xin Yang Kai-ming Zhu Yu Yu Dong-dong Tsinghua Univ Dept Precis Instruments & Mechanol State Key Lab Tribol Beijing 100084 Peoples R China

Due to modeling errors, accurate feedforward coefficient of the controller cannot be obtained with the standard method on the basis of the nominal model. Meanwhile, the system is uncertain in practice. Consequently, the MIMO (multi-input multi-output) system of the planar motor cannot be completely decoupled by feedback linearization, and the convergence of the tracking errors is no longer guaranteed. In order to improve the robustness and the tracking ability of the planar motor, a feedforward coefficient identification method and nonlinear composite feedback controller are proposed, thus guaranteeing stability by Lyapunov theory, wherein the feedforward coefficient can be obtained by the PD control experiment. The results of two different trajectory tracking experiments show that it is more accurate than the standard method. Moreover, this coefficient is suitable for different trajectories, so it avoids the drawback of ILC (iterative learning control) method, by which the feedforward term obtained cannot be reused if the length of the trajectory changes. The nonlinear composite feedback controller consists of u (1) and u (2) terms. u (1) is designed to compensate for modeling errors, therefore the robustness is improved and the coupling effects among multi-DOF (degrees of freedom) are reduced. In balancing the trade-off between disturbance rejection and noise sensitivity, an amplitude-based variable-gain function is applied in u (2). The trajectory tracking experimental results show that the overall controller is an attractive approach for the uncertain multi-DOF systems.

关键词： Planar motor modeling errors Feedforward coefficient identification Nonlinear composite feedback controller Trajectory tracking

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Self-adaptive Robust Control of Joint Robots for modeling Error

Self-adaptive Robust Control of Joint Robots for Modeling Er...

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International Conference on Information Engineering for Mechanics and Materials (ICIMM 2013)

作者： Su, Peng Yang, Yang Beihang Univ Dept Mech Design & Automat Beijing 100191 Peoples R China

ISBN: (纸本)9783037858851

For joint robot system contains inevitable model error in the modeling process, an effective method is proposed for self-adaptive stability control in this paper. After building the robot dynamics model, error factors are analyzed in the model. Based on robust control theory, an improved self-adaptive PID controller is designed and its Lyapunov stability is verified. Finally, by simulation for a two-link manipulator, the result which shows the control method has well efficiency and practicality for robust stability control. The results will be significant for the precise control of the robot system.

关键词： modeling errors Self-adaptive Stability Robust

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