System identification is the science of constructing models from data. A model is never an exact description of reality, and it is desirable that the identified model comes accompanied by certificates of quality able ...
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System identification is the science of constructing models from data. A model is never an exact description of reality, and it is desirable that the identified model comes accompanied by certificates of quality able to describe the level of precision of the model and its domain of validity. This paper is about certified system identification. Our contention is that data contains more information than traditional identification methods can exploit, and, by looking at classical identification problems with new eyes, methods can be developed carrying precise quality guarantees that are valid under general assumptions. Taking the challenge of developing these methods may lead to a paradigm shift in many contexts in which identification is applied.
This paper is devoted to the modeling problem of hypersonic vehicle with significant couplings. An integrated approach is developed to analytically model the dynamics of hypersonic vehicle, in which the effects of var...
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ISBN:
(纸本)9781467325813
This paper is devoted to the modeling problem of hypersonic vehicle with significant couplings. An integrated approach is developed to analytically model the dynamics of hypersonic vehicle, in which the effects of variable mass, spherical rotating earth, and couplings among the sub-models are considered. Furthermore, a preliminary analysis is conducted using the general data of a hypersonic vehicle. The simulation results show that the maximum of the Coriolis force can reach values up to 7.02% of the vehicle weight, and that the thermal load determined by the nonuniform aerodynamic heating and the properties of the structure has a significant influence on the elastic deformation.
Earlier investigations show that the results of hazard identification (HAZID) and analysis (e.g. HAZOP or FMEA) can effectively be used for knowledge-based diagnosis of complex process systems in their steady-state op...
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Recently automotive nets are adopted to solve increasing problems in automotive electronic *** of automotive local area network from CAN and LIN can solve the problems of the increasing of wire bunch weight and lack i...
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Recently automotive nets are adopted to solve increasing problems in automotive electronic *** of automotive local area network from CAN and LIN can solve the problems of the increasing of wire bunch weight and lack in module installation ***,the multilayer automotive nets software becomes more and more complex,and the development expense is difficult to predict and to keep in *** this paper,the modeling method of hierarchical automotive nets and the substitution operation based on object-oriented colored Petri net(OOCPN) are *** OOCPN model which analyzes the software structure and validates the collision mechanism of CAN/LIN bus can speed the automobile system ***,the subsystems are divided and modeled by object-oriented Petri net(OOPN).According to the sets of message sharing relations,the message ports among them are set and the communication gate transitions are ***,the OOPN model is substituted step by step until the inner objects in the automotive body control modules(BCM) are indivisible and colored by colored Petri net(CPN).And the color subsets mark the node messages for the collision ***,the OOCPN model of the automotive body CAN/LIN nets is assembled,which keeps the message sets and the system can be *** proposed model is used to analyze features of information sharing among the objects,and it is also used to describe each subsystem real-time behavior of processing messages and implemental device controllers operating,and puts forward a reasonable software framework for the automotive body control *** research can help to design the communication model in the automotive body system effectively and provide a convenient and rapid way for developing the logical hierarchy software.
The mean-square exponential stability problem is investigated for a class of stochastic time-varying delay systems with Markovian jumping parameters. By decomposing the delay interval into multiple equidistant subinte...
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The mean-square exponential stability problem is investigated for a class of stochastic time-varying delay systems with Markovian jumping parameters. By decomposing the delay interval into multiple equidistant subintervals, a new delay-dependent and decay-rate-dependent criterion is presented based on constructing a novel Lyapunov functional and employing stochastic analysis technique. Besides, the decay rate has no conventional constraint and can be selected according to different practical conditions. Finally, two numerical examples are provided to show that the obtained result has less conservatism than some existing ones in the literature.
A novel image deblurring method based on high-order non-local range Markov Random Field (NLR-MRF) prior is proposed in the paper. NLR-MRF provides an effective framework to model the statistical prior of natural image...
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A novel image deblurring method based on high-order non-local range Markov Random Field (NLR-MRF) prior is proposed in the paper. NLR-MRF provides an effective framework to model the statistical prior of natural images and leads to excellent performance in the application of image denoising and inpainting. Moreover, the framework will be extended to image deblurring in our work. Instead of commonly used maximum a-posteriori (MAP) estimation, which has several shortcomings, the high-order NLR-MRF prior is integrated into Bayesian minimum mean squared error (MMSE) estimation framework. Then, an efficient Gibbs sampling algorithm is adopted to compute MMSE estimation. The proposed method frees the user from determining regularization parameter beforehand, which relies on unknown noise level. We perform experiments on synthetic and real-world data to demonstrate the effectiveness of our method. Both quantitatively and qualitatively evaluations show superior or comparable results to the state-of-art deblurring methods.
A novel structure identification procedure for discrete event systems described by Petri nets are proposed in this paper for model-based diagnostic purposes that utilize the notions and tools of process mining. The id...
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ISBN:
(纸本)9780889868632
A novel structure identification procedure for discrete event systems described by Petri nets are proposed in this paper for model-based diagnostic purposes that utilize the notions and tools of process mining. The identification of the structurally different discrete event system models describing a system in its normal and/or faulty modes was used for model-based isolation of the considered faulty modes. From the available process mining techniques that allow for the automatic construction of process models in Petri net form based on event logs, the genetic algorithm-based structure identification procedure has been found to be most capable of identifying the characteristic structural elements of the faulty models. The proposed procedures are illustrated on a simple example of an operated parking gate automaton with two faulty modes.
Episodes of complete failure to respond during attentive tasks - lapses of responsiveness ('lapses') - accompanied by behavioral signs of sleep such as slow-eyeclosure are known as behavioral microsleeps (BMs)...
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ISBN:
(纸本)9781457717871
Episodes of complete failure to respond during attentive tasks - lapses of responsiveness ('lapses') - accompanied by behavioral signs of sleep such as slow-eyeclosure are known as behavioral microsleeps (BMs). The occurrence of BMs can have serious/fatal consequences, particularly in the transport sectors, and therefore further investigations on neurophysiological correlates of BMs are highly desirable. In this paper we propose a combination of High Resolution EEG techniques and an advanced method for time-varying functional connectivity estimation for reconstructing the temporal evolution of causal relations between cortical regions of BMs occurring during a visuomotor tracking task. The preliminary results highlight connectivity patterns involving parietal and fronto-parietal areas both preceding and following the onset of a BM.
This paper considers the design of robust H∞ filters for continuous-time linear systems with uncertainties described by integral quadratic constraints (IQCs). The synthesis problem can be converted into an infinite-d...
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Abstract This paper introduces a new multi-mode Extended Kalman Filter (EKF) algorithm for attitude estimation of small UAVs during the whole flight (from take off to landing). At first, it examines the available INS/...
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Abstract This paper introduces a new multi-mode Extended Kalman Filter (EKF) algorithm for attitude estimation of small UAVs during the whole flight (from take off to landing). At first, it examines the available INS/GPS measurements from the point of view of applicability in the estimator on ground and in air. From this, a multi-mode EKF is developed which switches between measurements to use them optimally. The quaternion representation of rotation was used to avoid singularity and derive a closed form solution of the Heun scheme in the discretization of system dynamics. Filter initialization and observability issues are also covered. After presenting the computational steps of the EKF the hybrid automata representation is described. This includes the description of estimator modes, automata states and input events. Finally, the graph of the automata representation is published. The paper ends with the description of tuning process and presentation of off-line test results on real noisy data. The new EKF performed well during all the tests including flights with stabilization controllers based on the estimated Euler angles.
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