作者:
Xue, FeiWang, XinWang, JunqiuZha, Hongbin
School of Electrical Engineering and Computer Sciences Peking University Beijing100871 China
Beijing Changcheng Aeronautical Measurement and Control Technology Research Institute Beijing10081 China
We propose a novel deep visual odometry (VO) method that considers global information by selecting memory and refining poses. Existing learning-based methods take the VO task as a pure tracking problem via recovering ...
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This paper investigates how to compensate for curvature response mismatch in lateral Model Predictive control (MPC) of an autonomous vehicle. The standard kinematic bicycle model does not describe accurately the vehic...
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ISBN:
(数字)9781728141497
ISBN:
(纸本)9781728141503
This paper investigates how to compensate for curvature response mismatch in lateral Model Predictive control (MPC) of an autonomous vehicle. The standard kinematic bicycle model does not describe accurately the vehicle yaw-rate dynamics, leading to inaccurate motion prediction when used in MPC. Therefore, the standard model is extended with a nonlinear function that maps the curvature response of the vehicle to a given request. Experimental data shows that a two Gaussian functions approximation gives an accurate description of this mapping. Both simulation and experimental results show that the corresponding modified model significantly improves the control performance when using Reference Aware MPC for autonomous driving of a Scania heavy-duty construction truck.
We present a faithful geometric picture for genuine tripartite entanglement of discrete, continuous, and hybrid quantum systems. We first show that the triangle relation (Formula Presented) holds for all subadditive b...
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An improved Tikhonov regularization algorithm MCTR based on Markov radial basis function is proposed to obtain the feedback of closed-loop control for pulverized coal injection process in thermal power plant, so as to...
An improved Tikhonov regularization algorithm MCTR based on Markov radial basis function is proposed to obtain the feedback of closed-loop control for pulverized coal injection process in thermal power plant, so as to solve the ill posed problem in temperature field reconstruction in furnace. The algorithm constructs a new regularization matrix to replace the standard Tikhonov regularization element matrix, so as to achieve the correction effect of the new algorithm. MCTR algorithm determines the boundary singular value of small singular value defined in this paper by determining the proportion between the standard deviation component corresponding to small singular value and the sum of standard deviation components corresponding to all singular values after singular value decomposition of coefficient matrix. After determining the boundary, a new regularization matrix is constructed according to the eigenvector corresponding to small singular value. Compared with the MTR algorithm using the identity matrix as the regularization matrix, MCTR algorithm only selectively modifies the parameters corresponding to small singular values after determining the regularization parameters, which improves the stability of the parameter solution and the reconstruction accuracy of the temperature field, and is helpful to the automatic control of thermal power plants and the efficiency of coal combustion.
Aiming at a large number of abnormal data in wind turbine operation data, considering the wind turbine operation characteristics and data clustering, this paper proposes a method for cleaning abnormal power data of wi...
ISBN:
(数字)9781728157481
ISBN:
(纸本)9781728157498
Aiming at a large number of abnormal data in wind turbine operation data, considering the wind turbine operation characteristics and data clustering, this paper proposes a method for cleaning abnormal power data of wind turbines based on high-dimensional space clustering. First, based on the control strategy differences and operating mechanisms of wind turbines, the mechanism cleaning of abnormal wind power data is performed; Second, consider the wind speed, rotor speed, and power, and use Gaussian mixture model (GMM) to cluster the data in three-dimensional space to achieve the preliminary cleaning of abnormal power data of wind turbines; Finally, on the basis of the preliminary cleaned data, an optimized multi-directional quartile method is used in the Copula space for refined cleaning. The actual data of a certain type of wind turbine in North China is selected for example analysis. The simulation results show that the method proposed in this paper is reasonable and effective.
As the scale of object detection dataset is smaller than that of image recognition dataset ImageNet, transfer learning has become a basic training method for deep learning object detection models, which will pretrain ...
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Digital behavior change interventions (DBCIs) have been found to positively impact health behaviors and are becoming increasingly important as an emerging topic for control systems applications. However, their effecti...
Digital behavior change interventions (DBCIs) have been found to positively impact health behaviors and are becoming increasingly important as an emerging topic for control systems applications. However, their effectiveness is heavily dependent upon user engagement with both the digital tool (e.g., mHealth app, wearable activity tracker) and the behavior change intervention (e.g., exercise activity planning). In this paper, engagement refers to the unique interactions of a participant with either of these components resulting in digital traces (e.g., app page views). Furthermore, engagement in DBCIs will change over the course of the intervention in response to an individual’s environment, context, and psychological state. Intensive data collection enables modeling engagement in DBCIs as a dynamical system using fluid analogies, and applying prediction-error methods from system identification to estimate models. Missingness represents both a fundamental and practical concern in this application domain. This work addresses missingness using a novel Bayesian imputation method applied to data from the HeartSteps II physical activity intervention study. The benefits of this approach include the ability to impute missing data points more accurately than traditional methods and quantify uncertainty resulting from imputation and data scarcity; the latter is essential to the implementation of robust closed-loop interventions. The methods presented in this work provide insights into critical factors that impact engagement behavior over time and in context, ultimately benefiting the development of digital behavior change interventions relying on controlengineering approaches.
performance evaluation method for the combustion system in the variable load process of circulating fluidized bed (CFB) unit based on the minimum variance control is proposed. Each operating parameter are initially we...
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A large variety of sophisticated metaheuristic methods have been proposed for photovoltaic parameter extraction. Our aim is not to develop another metaheuristic method but to investigate two practically important yet ...
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Human intelligence is a mental capability that can describe the level of individual behavioral and cognitive abilities. Recent works suggest that the resting state graph metrics and similarity measures that capture th...
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ISBN:
(数字)9781728172965
ISBN:
(纸本)9781728172972
Human intelligence is a mental capability that can describe the level of individual behavioral and cognitive abilities. Recent works suggest that the resting state graph metrics and similarity measures that capture the nonlinear interactions between regions are better than other conventional approaches to link neuroimaging data to intelligence metrics. In this study, for the first time, we investigated the capacity of mutual information (MI) in predicting the intelligence. To this end, the network edges are defined based on MI and the relationship between graph metrics extracted from resting state brain networks and intelligence is explored. Results show that graphs constructed based on MI have stronger relationship with intelligence in comparison to those constructed based on Pearson correlation.
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