This paper analyses the HBEFA-based instantaneous vehicle emissions model implemented in the SUMO microscopic traffic simulation. We identify significant discrepancies between real vehicle emissions measured with port...
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Intelligent vehicles and autonomous driving systems rely on scenario engineering for intelligence and index (I&I), calibration and certification (C&C), and verification and validation (V&V). To extract and...
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Intelligent vehicles and autonomous driving systems rely on scenario engineering for intelligence and index (I&I), calibration and certification (C&C), and verification and validation (V&V). To extract and index scenarios, various vehicle interactions are worthy of much attention, and deserve refined descriptions and labels. However, existing methods cannot cope well with the problem of scenario classification and labeling with vehicle interactions as the core. In this paper, we propose VistaScenario framework to conduct interaction scenario engineering for vehicles with intelligent systems for transport automation. Based on the summarized basic types of vehicle interactions, we slice scenario data stream into a series of segments via spatiotemporal scenario evolution tree. We also propose the scenario metric Graph-DTW based on Graph Computation Tree and Dynamic Time Warping to conduct refined scenario comparison and labeling. The extreme interaction scenarios and corner cases can be efficiently filtered and extracted. Moreover, with naturalistic scenario datasets, testing examples on trajectory prediction model demonstrate the effectiveness and advantages of our framework. VistaScenario can provide solid support for the usage and indexing of scenario data, further promote the development of intelligent vehicles and transport automation. IEEE
The article is devoted to the analysis of the possibilities of improving the methodology for selecting the operation parameters of the longitudinal differential protection of a power transformer when using new types o...
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We study the problem of policy estimation for the Linear Quadratic Regulator (LQR) in discrete-time linear timeinvariant uncertain dynamical systems. We propose a Moreau Envelope-based surrogate LQR cost, built from a...
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Model mismatch often presents significant challenges in model-based controller design. This paper investigates model predictive control (MPC) for uncertain linear systems with input constraints, where the uncertainty ...
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A buck-boost converter is used chiefly for PFC purposes in power electronics converter systems because the voltage regulation in a PFC converter can easily be made using a buck-boost converter. In this paper, using th...
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This research looks into electrical grids that will soon likely become more intelligent. In light of this, there is a growing need for intelligent, adaptable microgrids that can function both independently and in conj...
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The exponential growth of academic publications has made scholarly research recommender systems indispensable tools for researchers. These systems rely on diverse evaluation metrics to assess their effectiveness and r...
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In this paper,we review the development of a phase theory for systems and networks in its first five years,represented by a trilogy:Matrix phases and their properties;The MIMO LTI system phase response,its physical in...
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In this paper,we review the development of a phase theory for systems and networks in its first five years,represented by a trilogy:Matrix phases and their properties;The MIMO LTI system phase response,its physical interpretations,the small phase theorem,and the sectored real lemma;The synchronization of a multi-agent network using phase *** the end,we also summarize a list of ongoing research on the phase theory and speculate what will happen in the next five years.
Recently, a reference derived some new higher-order output tracking properties for direct model reference adaptive control(MRAC) of linear time-invariant(LTI) systems: limt→∞ e(i)(t) = 0, i = 1,..., n*-1, wh...
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Recently, a reference derived some new higher-order output tracking properties for direct model reference adaptive control(MRAC) of linear time-invariant(LTI) systems: limt→∞ e(i)(t) = 0, i = 1,..., n*-1, where n*and e(i)(t) denote the relative degree of the system and the i-th derivative of the output tracking error, respectively. However, a naturally arising question involves whether indirect adaptive control(including indirect MRAC and indirect adaptive pole placement control) of LTI systems still has higher-order tracking properties. Such properties have not been reported in the literature. Therefore, this paper provides an affirmative answer to this question. Such higher-order tracking properties are new discoveries since they hold without any additional design conditions and, in particular, without the persistent excitation condition. Given the higher-order properties, a new adaptive control system is developed with stronger tracking features.(1) It can track a reference signal with any order derivatives being unknown.(2) It has higher-order exponential or practical output tracking properties.(3) Finally, it is different from the usual MRAC system, whose reference signal's derivatives up to the n*order are assumed to be known. Finally, two simulation examples are provided to verify the theoretical results obtained in this paper.
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