This paper presents a Nonlinear Model Predictive Controller(NMPC)for the path following of autonomous vehicles and an algorithm to adaptively adjust the preview distance.The prediction model includes vehicle dynamics,...This paper presents a Nonlinear Model Predictive Controller(NMPC)for the path following of autonomous vehicles and an algorithm to adaptively adjust the preview distance.The prediction model includes vehicle dynamics,path following dynamics,and system input dynamics.The single-track vehicle model considers the vehicle’s coupled lateral and longitudinal dynamics,as well as nonlinear tire forces.The tracking error dynamics are derived based on the curvilinear coordinates.The cost function is designed to minimize path tracking errors and control effort while considering constraints such as actuator bounds and tire grip limits.An algorithm that utilizes the optimal preview distance vector to query the corresponding reference curvature and reference speed.The length of the preview path is adaptively adjusted based on the vehicle speed,heading error,and path curvature.We validate the controller performance in a simulation environment with the autonomous racing scenario.The simulation results show that the vehicle accurately follows the highly dynamic path with small tracking errors.The maximum preview distance can be prior estimated and guidance the selection of the prediction horizon for NMPC.展开更多
A new mechanics model, which reveals additional longitudinal force transmission between the continuously welded rails and the bridges, is established on the fact that the influence of the mutual relative displacement ...A new mechanics model, which reveals additional longitudinal force transmission between the continuously welded rails and the bridges, is established on the fact that the influence of the mutual relative displacement (among) the rail, the sleeper and the beam is taken into account. An example is presented and numerical results are compared. The results show that the additional longitudinal forces calculated with the new model are less than those of the previous, especially in the case of the flexible pier bridges. The new model is also suitable for the analysis of the additional longitudinal force transmission between rails and bridges of ballastless track with small resistance fasteners without taking the sleeper displacement into account, and compared with the ballast bridges, the ballastless bridges have a much stronger additional longitudinal force transmission between the continuously welded rails and the bridges.展开更多
A non-linear regression model is proposed to forecast the aggregated passenger volume of Beijing-Shanghai high-speed railway(HSR) line in China. Train services and temporal features of passenger volume are studied to ...A non-linear regression model is proposed to forecast the aggregated passenger volume of Beijing-Shanghai high-speed railway(HSR) line in China. Train services and temporal features of passenger volume are studied to have a prior knowledge about this high-speed railway line. Then, based on a theoretical curve that depicts the relationship among passenger demand, transportation capacity and passenger volume, a non-linear regression model is established with consideration of the effect of capacity constraint. Through experiments, it is found that the proposed model can perform better in both forecasting accuracy and stability compared with linear regression models and back-propagation neural networks. In addition to the forecasting ability, with a definite formation, the proposed model can be further used to forecast the effects of train planning policies.展开更多
There is still an obstacle to prevent neural network from wider and more effective applications, i.e., the lack of effective theories of models identification. Based on information theory and its generalization, this ...There is still an obstacle to prevent neural network from wider and more effective applications, i.e., the lack of effective theories of models identification. Based on information theory and its generalization, this paper introduces a universal method to achieve nonlinear models identification. Two key quantities, which are called nonlinear irreducible auto-correlation (NIAC) and generalized nonlinear irreducible auto-correlation (GNIAC), are defined and discussed. NIAC and GNIAC correspond with intrinstic irreducible auto-(dependency) (IAD) and generalized irreducible auto-(dependency) (GIAD) of time series respectively. By investigating the evolving trend of NIAC and GNIAC, the optimal auto-regressive order of nonlinear auto-regressive models could be determined naturally. Subsequently, an efficient algorithm computing NIAC and GNIAC is discussed. Experiments on simulating data sets and typical nonlinear prediction models indicate remarkable correlation between optimal auto-regressive order and the highest order that NIAC-GNIAC have a remarkable non-zero value, therefore demonstrate the validity of the proposal in this paper.展开更多
In South Africa, electricity is supplied through thousands-of-kilometers of overhead power cables, which is owned by Eskom the national energy supplier. Currently monitoring of these overhead power cables are done by ...In South Africa, electricity is supplied through thousands-of-kilometers of overhead power cables, which is owned by Eskom the national energy supplier. Currently monitoring of these overhead power cables are done by means of helicopter inspection flights and foot patrols, which are infrequent and expensive. In this paper, the authors present the design of a prototype power line crawler （inspection robot） for the monitoring of these overhead power lines in South Africa. The designed prototype power line crawler is capable of driving on the wire, balancing on the wire and is capable of maneuvering past certain obstacles found on the overhead power cables. The prototype power line crawler is designed to host a monitoring system that monitors the power line as the inspection robot drives on it. Various experimental tests were performed and are presented in this paper, showing the capability of performing these tasks. This prototype inspection robot ensures a platform for future development in this area.展开更多
The national energy supplier （Eskom in South Africa） supplies electricity through thousands-of-kilometers of overhead power lines. The current methods of inspection of these overhead power lines are infrequent and e...The national energy supplier （Eskom in South Africa） supplies electricity through thousands-of-kilometers of overhead power lines. The current methods of inspection of these overhead power lines are infrequent and expensive. In this paper, the authors present the development of a prototype monitoring system for power line inspection in South Africa. The developed prototype monitoring system collects data （information） from the overhead power lines, is remotely accessible and fits into a power line robot. The prototype monitoring system makes use ofa PandaBoard （SBC） with GPS receiver and 5 MP camera to collect data. Hardware fatigue is the biggest problem faced on the overhead power lines and is captured by means of the 5 MP camera and is displayed on a website hosted by the PandaBoard via Wi-Fi. The monitoring system has low power consumption, is light weight, compact and easily collects data. The data obtained from the prototype monitoring system was satisfactory and provides an improved solution for monitoring power lines for Eskom in South Africa.展开更多
基金“National Science and Technology Council”(NSTC 111-2221-E-027-088)。
文摘This paper presents a Nonlinear Model Predictive Controller(NMPC)for the path following of autonomous vehicles and an algorithm to adaptively adjust the preview distance.The prediction model includes vehicle dynamics,path following dynamics,and system input dynamics.The single-track vehicle model considers the vehicle’s coupled lateral and longitudinal dynamics,as well as nonlinear tire forces.The tracking error dynamics are derived based on the curvilinear coordinates.The cost function is designed to minimize path tracking errors and control effort while considering constraints such as actuator bounds and tire grip limits.An algorithm that utilizes the optimal preview distance vector to query the corresponding reference curvature and reference speed.The length of the preview path is adaptively adjusted based on the vehicle speed,heading error,and path curvature.We validate the controller performance in a simulation environment with the autonomous racing scenario.The simulation results show that the vehicle accurately follows the highly dynamic path with small tracking errors.The maximum preview distance can be prior estimated and guidance the selection of the prediction horizon for NMPC.
文摘A new mechanics model, which reveals additional longitudinal force transmission between the continuously welded rails and the bridges, is established on the fact that the influence of the mutual relative displacement (among) the rail, the sleeper and the beam is taken into account. An example is presented and numerical results are compared. The results show that the additional longitudinal forces calculated with the new model are less than those of the previous, especially in the case of the flexible pier bridges. The new model is also suitable for the analysis of the additional longitudinal force transmission between rails and bridges of ballastless track with small resistance fasteners without taking the sleeper displacement into account, and compared with the ballast bridges, the ballastless bridges have a much stronger additional longitudinal force transmission between the continuously welded rails and the bridges.
基金Project(2014YJS080) supported by the Fundamental Research Funds for the Central Universities of China
文摘A non-linear regression model is proposed to forecast the aggregated passenger volume of Beijing-Shanghai high-speed railway(HSR) line in China. Train services and temporal features of passenger volume are studied to have a prior knowledge about this high-speed railway line. Then, based on a theoretical curve that depicts the relationship among passenger demand, transportation capacity and passenger volume, a non-linear regression model is established with consideration of the effect of capacity constraint. Through experiments, it is found that the proposed model can perform better in both forecasting accuracy and stability compared with linear regression models and back-propagation neural networks. In addition to the forecasting ability, with a definite formation, the proposed model can be further used to forecast the effects of train planning policies.
文摘There is still an obstacle to prevent neural network from wider and more effective applications, i.e., the lack of effective theories of models identification. Based on information theory and its generalization, this paper introduces a universal method to achieve nonlinear models identification. Two key quantities, which are called nonlinear irreducible auto-correlation (NIAC) and generalized nonlinear irreducible auto-correlation (GNIAC), are defined and discussed. NIAC and GNIAC correspond with intrinstic irreducible auto-(dependency) (IAD) and generalized irreducible auto-(dependency) (GIAD) of time series respectively. By investigating the evolving trend of NIAC and GNIAC, the optimal auto-regressive order of nonlinear auto-regressive models could be determined naturally. Subsequently, an efficient algorithm computing NIAC and GNIAC is discussed. Experiments on simulating data sets and typical nonlinear prediction models indicate remarkable correlation between optimal auto-regressive order and the highest order that NIAC-GNIAC have a remarkable non-zero value, therefore demonstrate the validity of the proposal in this paper.
文摘In South Africa, electricity is supplied through thousands-of-kilometers of overhead power cables, which is owned by Eskom the national energy supplier. Currently monitoring of these overhead power cables are done by means of helicopter inspection flights and foot patrols, which are infrequent and expensive. In this paper, the authors present the design of a prototype power line crawler （inspection robot） for the monitoring of these overhead power lines in South Africa. The designed prototype power line crawler is capable of driving on the wire, balancing on the wire and is capable of maneuvering past certain obstacles found on the overhead power cables. The prototype power line crawler is designed to host a monitoring system that monitors the power line as the inspection robot drives on it. Various experimental tests were performed and are presented in this paper, showing the capability of performing these tasks. This prototype inspection robot ensures a platform for future development in this area.
文摘The national energy supplier （Eskom in South Africa） supplies electricity through thousands-of-kilometers of overhead power lines. The current methods of inspection of these overhead power lines are infrequent and expensive. In this paper, the authors present the development of a prototype monitoring system for power line inspection in South Africa. The developed prototype monitoring system collects data （information） from the overhead power lines, is remotely accessible and fits into a power line robot. The prototype monitoring system makes use ofa PandaBoard （SBC） with GPS receiver and 5 MP camera to collect data. Hardware fatigue is the biggest problem faced on the overhead power lines and is captured by means of the 5 MP camera and is displayed on a website hosted by the PandaBoard via Wi-Fi. The monitoring system has low power consumption, is light weight, compact and easily collects data. The data obtained from the prototype monitoring system was satisfactory and provides an improved solution for monitoring power lines for Eskom in South Africa.
