Cooperative path dynamic planning of a UCAV （unmanned combat air vehicle） team not only considers the capability of task requirement of single UCAV, but also considers the cooperative dynamic connection among member...Cooperative path dynamic planning of a UCAV （unmanned combat air vehicle） team not only considers the capability of task requirement of single UCAV, but also considers the cooperative dynamic connection among members of the UCAV team. A cooperative path dynamic planning model of the UCAV team by applying a global optimization method is discussed in this paper and the corresponding model is built and analyzed. By the example simulation, the reasonable result acquired indicates that the model could meet dynamic planning demand under the circumstance of membership functions. The model is easy to be realized and has good practicability.展开更多
Demand Responsive Transit (DRT) responds to the dynamic users’ requests without any fixed routes and timetablesand determines the stop and the start according to the demands. This study explores the optimization of d...Demand Responsive Transit (DRT) responds to the dynamic users’ requests without any fixed routes and timetablesand determines the stop and the start according to the demands. This study explores the optimization of dynamicvehicle scheduling and real-time route planning in urban public transportation systems, with a focus on busservices. It addresses the limitations of current shared mobility routing algorithms, which are primarily designedfor simpler, single origin/destination scenarios, and do not meet the complex demands of bus transit systems. Theresearch introduces an route planning algorithm designed to dynamically accommodate passenger travel needsand enable real-time route modifications. Unlike traditional methods, this algorithm leverages a queue-based,multi-objective heuristic A∗ approach, offering a solution to the inflexibility and limited coverage of suburbanbus routes. Also, this study conducts a comparative analysis of the proposed algorithm with solutions based onGenetic Algorithm (GA) and Ant Colony Optimization Algorithm (ACO), focusing on calculation time, routelength, passenger waiting time, boarding time, and detour rate. The findings demonstrate that the proposedalgorithmsignificantly enhances route planning speed, achieving an 80–100-fold increase in efficiency over existingmodels, thereby supporting the real-time demands of Demand-Responsive Transportation (DRT) systems. Thestudy concludes that this algorithm not only optimizes route planning in bus transit but also presents a scalablesolution for improving urban mobility.展开更多
A new seam-tracking method based on dynamic trajectory planning for a mobile welding robot is proposed in order to improve the response lag of the mobile robot and the high frequency oscillation in seam-tracking.By us...A new seam-tracking method based on dynamic trajectory planning for a mobile welding robot is proposed in order to improve the response lag of the mobile robot and the high frequency oscillation in seam-tracking.By using a front-placed laser-based vision sensor to dynamically extract the location of the weld seam in front of torch,the trend and direction of the weld line is roughly obtained.The robot system autonomously and dynamically performs trajectory planning based on the isometric approximation model.Arc sensor technology is applied to detect the offset during welding process in real time.The dynamic compensation of the weld path is done in combination with the control of the mobile robot and the executive body installed on it.Simulated and experimental results demonstrate that the method effectively increases the stability of welding speed and smoothness of the weld track,and hence the weld formation in curves and corners is improved.展开更多
Presents the mobile robots dynamic motion planning problem with a task to find an obstacle free route that requires minimum travel time from the start point to the destination point in a changing environment, due to t...Presents the mobile robots dynamic motion planning problem with a task to find an obstacle free route that requires minimum travel time from the start point to the destination point in a changing environment, due to the obstacle’s moving. An Genetic Algorithm fuzzy (GA Fuzzy) based optimal approach proposed to find any obstacle free path and the GA used to select the optimal one, points out that using this learned knowledge off line, a mobile robot can navigate to its goal point when it faces new scenario on line. Concludes with the optimal rule base given and the simulation results showing its effectiveness.展开更多
A dynamic advanced planning and scheduling （DAPS） problem is addressed where new orders arrive on a continuous basis. A periodic policy with frozen interval is adopted to increase stability on the shop floor. A gene...A dynamic advanced planning and scheduling （DAPS） problem is addressed where new orders arrive on a continuous basis. A periodic policy with frozen interval is adopted to increase stability on the shop floor. A genetic algorithm is developed to find a schedule at each rescheduling point for both original orders and new orders that both production idle time and penalties on tardiness and earliness of orders are minimized. The proposed methodology is tested on a small example to illustrate the effect of the frozen interval. The results indicate that the suggested approach can improve the schedule stability while retaining efficiency.展开更多
At the first sight it seems that advanced operation research is not used enough in continuous production systems as comparison with mass production, batch production and job shop systems, but really in a comprehensive...At the first sight it seems that advanced operation research is not used enough in continuous production systems as comparison with mass production, batch production and job shop systems, but really in a comprehensive evaluation the advanced operation research techniques can be used in continuous production systems in developing countries very widely, because of initial inadequate plant layout, stage by stage development of production lines, the purchase of second hand machineries from various countries, plurality of customers. A case of production system planning is proposed for a chemical company in which the above mentioned conditions are almost presented. The goals and constraints in this issue are as follows： （1） Minimizing deviation of customer＇s requirements. （2） Maximizing the profit. （3） Minimizing the frequencies of changes in formula production. （4） Minimizing the inventory of final products. （5） Balancing the production sections with regard to rate in production. （6） Limitation in inventory of raw material. The present situation is in such a way that various techniques such as goal programming, linear programming and dynamic programming can be used. But dynamic production programming issues are divided into two categories, at first one with limitation in production capacity and another with unlimited production capacity. For the first category, a systematic and acceptable solution has not been presented yet. Therefore an innovative method is used to convert the dynamic situation to a zero- one model. At last this issue is changed to a goal programming model with non-linear limitations with the use of GRG algorithm and that＇s how it is solved.展开更多
Mission planning was thoroughly studied in the areas of multiple intelligent agent systems,such as multiple unmanned air vehicles,and multiple processor systems.However,it still faces challenges due to the system comp...Mission planning was thoroughly studied in the areas of multiple intelligent agent systems,such as multiple unmanned air vehicles,and multiple processor systems.However,it still faces challenges due to the system complexity,the execution order constraints,and the dynamic environment uncertainty.To address it,a coordinated dynamic mission planning scheme is proposed utilizing the method of the weighted AND/OR tree and the AOE-Network.In the scheme,the mission is decomposed into a time-constraint weighted AND/OR tree,which is converted into an AOE-Network for mission planning.Then,a dynamic planning algorithm is designed which uses task subcontracting and dynamic re-decomposition to coordinate conflicts.The scheme can reduce the task complexity and its execution time by implementing real-time dynamic re-planning.The simulation proves the effectiveness of this approach.展开更多
Starting with cultural context of historic block, this paper investigated current situation of Shengjinta Historic Block in Nanchang City, Jiangxi Province, proposed dynamic protection planning and sustainable industr...Starting with cultural context of historic block, this paper investigated current situation of Shengjinta Historic Block in Nanchang City, Jiangxi Province, proposed dynamic protection planning and sustainable industrial upgrading strategies, specifically, by repairing, clearing, preserving and restoring historic streets and lanes, courtyards and folk dwel ings from six perspectives of planar layout, traffic pattern, spatial texture, facade decoration, landscape planning, and characteristic culture. In view of the specifi c geographical location, food shops and leisure green spaces are constructed to build a modern urban living system for residents in the ancient block.展开更多
Aiming at the faults of some weak nodes in the concentrated solar power-photovoltaic(CSP-PV)hybrid power generation system,it is impossible to restore the transient voltage only relying on the reactive power regulatio...Aiming at the faults of some weak nodes in the concentrated solar power-photovoltaic(CSP-PV)hybrid power generation system,it is impossible to restore the transient voltage only relying on the reactive power regulation capability of the system itself.We propose a dynamic reactive power planning method suitable for CSP-PV hybrid power generation system.The method determines the installation node of the dynamic reactive power compensation device and its compensation capacity based on the reactive power adjustment capability of the system itself.The critical fault node is determined by the transient voltage stability recovery index,and the weak node of the system is initially determined.Based on this,the sensitivity index is used to determine the installation node of the dynamic reactive power compensation device.Dynamic reactive power planning optimization model is established with the lowest investment cost of dynamic reactive power compensation device and the improvement of system transient voltage stability.Furthermore,the component of the reactive power compensation node is optimized by particle swarm optimization based on differential evolution(DE-PSO).The simulation results of the example system show that compared with the dynamic position compensation device installation location optimization method,the proposed method can improve the transient voltage stability of the system under the same reactive power compensation cost.展开更多
For low-speed underwater vehicles, the ocean currents has a great influence on them, and the changes in ocean currents is complex and continuous, thus whose impact must be taken into consideration in the path planning...For low-speed underwater vehicles, the ocean currents has a great influence on them, and the changes in ocean currents is complex and continuous, thus whose impact must be taken into consideration in the path planning. There are still lack of authoritative indicator and method for the cooperating path planning. The calculation of the voyage time is a difficult problem in the time-varying ocean, for the existing methods of the cooperating path planning, the computation time will increase exponentially as the autonomous underwater vehicle（AUV） counts increase, rendering them unfeasible. A collaborative path planning method is presehted for multi-AUV under the influence of time-varying ocean currents based on the dynamic programming algorithm. Each AUV cooperates with the one who has the longest estimated time of sailing, enabling the arrays of AUV to get their common goal in the shortest time with minimum timedifference. At the same time, they could avoid the obstacles along the way to the target. Simulation results show that the proposed method has a promising applicability.展开更多
Increasing urbanization in the cities of northern Mexico reflects a general trend to increased temperatures, so it is likely that heat waves amplify the frequency and intensity in urban centers, mainly located in arid...Increasing urbanization in the cities of northern Mexico reflects a general trend to increased temperatures, so it is likely that heat waves amplify the frequency and intensity in urban centers, mainly located in arid and semiarid as Mexicali city with extremely arid climate, very hot in summer and cold and rainy in winter. Mexicali, Baja California, Mexico is located at N32°38＇ and W115°20＇. The urban area is expanded over 14,890 hectares, with a population rise the 689,775. In the last four decades has experienced an accelerated industrial growth and mismatched land uses, for example： most of the industrial parks were established before the 1980 in what was the outskirts of the city, but nowadays practically are inside of the urban area contributing to the increase the urban temperature. The heat islands profile shows that are intensified in industrial areas as well as trade and services. The preliminary scenarios of climate change for Mexicali indicate that for the decade of 2080 the temperature will increase between 4.2℃ and 4.4℃. This paper addresses in a simulation context, an industrial and commercial city sector and their ability to implement urban heat island mitigation strategies. The simulation of this process requires several spatial analysis tools and specific knowledge about the processes that increase urban temperatures. In this work, only land use, land cover and buildings are considered. The proposed method takes into account the actual spatial organization to analyze trends for the proposed growth areas.展开更多
A variable dimensional state space（VDSS） has been proposed to improve the re-planning time when the robotic systems operate in large unknown environments.VDSS is constructed by uniforming lattice state space and gri...A variable dimensional state space（VDSS） has been proposed to improve the re-planning time when the robotic systems operate in large unknown environments.VDSS is constructed by uniforming lattice state space and grid state space.In VDSS,the lattice state space is only used to construct search space in the local area which is a small circle area near the robot,and grid state space elsewhere.We have tested VDSS with up to 80 indoor and outdoor maps in simulation and on segbot robot platform.Through the simulation and segbot robot experiments,it shows that exploring on VDSS is significantly faster than exploring on lattice state space by Anytime Dynamic A＊（AD＊） planner and VDSS is feasible to be used on robotic systems.展开更多
Traditionally, heuristic re-planning algorithms are used to tackle the problem of dynamic task planning for multiple satellites. However, the traditional heuristic strategies depend on the concrete tasks, which often ...Traditionally, heuristic re-planning algorithms are used to tackle the problem of dynamic task planning for multiple satellites. However, the traditional heuristic strategies depend on the concrete tasks, which often affect the result’s optimality. Noticing that the historical information of cooperative task planning will impact the latter planning results, we propose a hybrid learning algorithm for dynamic multi-satellite task planning, which is based on the multi-agent reinforcement learning of policy iteration and the transfer learning. The reinforcement learning strategy of each satellite is described with neural networks. The policy neural network individuals with the best topological structure and weights are found by applying co-evolutionary search iteratively. To avoid the failure of the historical learning caused by the randomly occurring observation requests, a novel approach is proposed to balance the quality and efficiency of the task planning, which converts the historical learning strategy to the current initial learning strategy by applying the transfer learning algorithm. The simulations and analysis show the feasibility and adaptability of the proposed approach especially for the situation with randomly occurring observation requests.展开更多
This paper presents a computationally efficient real-time trajectory planning framework for typical unmanned combat aerial vehicle （UCAV） performing autonomous air-to-surface （A/S） attack. It combines the benefits...This paper presents a computationally efficient real-time trajectory planning framework for typical unmanned combat aerial vehicle （UCAV） performing autonomous air-to-surface （A/S） attack. It combines the benefits of inverse dynamics optimization method and receding horizon optimal control technique. Firstly, the ground attack trajectory planning problem is mathematically formulated as a receding horizon optimal control problem （RHC-OCP）. In particular, an approximate elliptic launch acceptable region （LAR） model is proposed to model the critical weapon delivery constraints. Secondly, a planning algorithm based on inverse dynamics optimization, which has high computational efficiency and good convergence properties, is developed to solve the RHCOCP in real-time. Thirdly, in order to improve robustness and adaptivity in a dynamic and uncer- tain environment, a two-degree-of-freedom （2-DOF） receding horizon control architecture is introduced and a regular real-time update strategy is proposed as well, and the real-time feedback can be achieved and the not-converged situations can be handled. Finally, numerical simulations demon- strate the efficiency of this framework, and the results also show that the presented technique is well suited for real-time implementation in dynamic and uncertain environment.展开更多
Most current research on the trajectory planning of the autonomous lane change focuses on high-speed scenarios and assumes that the states of the surrounding vehicles keep stable during the lane change.The methods bas...Most current research on the trajectory planning of the autonomous lane change focuses on high-speed scenarios and assumes that the states of the surrounding vehicles keep stable during the lane change.The methods based on geometric-curve are mostly used for trajectory planning.In this paper,considering the inevitable development of the autonomous driving,the surrounding vehicles are assumed to be driven by human drivers,while the ego vehicles are able to autonomously change lanes.Representative local lane-change scenarios are then designed and analyzed in detail aiming at medium-and low-speed lane-change conditions.Additionally,in contrast with most research,dynamic trajectory planning which considers the possible state variations of the surrounding vehicles and the driver characteristics is studied and described by a fifth-order polynomial function.The safety and comfort of the dynamic trajectory planning are validated through simulation.Moreover,the elastic soft constraint of the safety domain is designed,whereby the sensitivity of the studied dynamic trajectory planning system is reduced under the premise of ensuring safety.The effectiveness of the elastic soft constraint in terms of improving comfort during the lane change is verified through simulation.The availability of the dynamic trajectory planning system with the elastic soft constraint is demonstrated with the addition of trajectory tracking based on model predictive control,showing its potential in practical applications.展开更多
This paper reviewed the development of control technology in domestic and foreign launch vehicle(LV), and based on which, the key technologies of control system for Chinese heavy-lift launch vehicles were proposed. A ...This paper reviewed the development of control technology in domestic and foreign launch vehicle(LV), and based on which, the key technologies of control system for Chinese heavy-lift launch vehicles were proposed. A dynamic on-line trajectory planning technique was discussed to meet the demand of guidance control under complex constraints, and model based identification and adaptive control technology was suggested to deal with the control problems caused by model uncertainty and disturbance, and an integrated avionics system based on high speed communication was put forward for module integration and distributed control, and FBG based real time flight control was also discussed. Moreover, other key technologies, such as wireless interconnection, wireless power transfer, and temporal and spatial partitioning operating system, are both briefly introduced for the application in control systems. These studies will lead to breakthroughs in autonomous flight control in LV, and provide technical support for more long-term deep space explorations.展开更多
This paper proposes the architecture of an intelligent flight launcher system as well as fundamental solutions to capability prediction and dynamic planning. This effort reflects the latest progress in the application...This paper proposes the architecture of an intelligent flight launcher system as well as fundamental solutions to capability prediction and dynamic planning. This effort reflects the latest progress in the applications of intelligent and autonomous technology for launcher flights. The paper first describes the characteristics and capabilities of intelligent and autonomous systems and classifies various related technologies. In the context of intelligent and autonomous technology in aerospace engineering, it then focuses on technical difficulties involved with intelligent flight and reviews developments in the field. An E^3 classification model of an intelligent flight launcher is then proposed and its application scenarios are discussed. Based on an intelligent flight system configuration of the launcher, the online trajectory planning and initial value guess are examined, and vertical landing is provided as an example to explain the effects of the implementation of computational intelligence to flight systems.展开更多
In the existing modular joint design and control methods of collaborative robots, the inertia of the manipulator link is large,the dynamic trajectory planning ability is weak, the collision stop safety strategy is dep...In the existing modular joint design and control methods of collaborative robots, the inertia of the manipulator link is large,the dynamic trajectory planning ability is weak, the collision stop safety strategy is dependent, and the adaptability and safety to the changing environment are limited. This paper develops a six-degree-of-freedom lightweight collaborative manipulator with real-time dynamic trajectory planning and active compliance control. Firstly, a novel motor installation, joint transmission, and link design method is put forward to reduce the inertia of the links and improve intrinsic safety. At the same time, to enhance the dynamic operation capability and quick response of the manipulator, a smooth planning of position and orientation under initial/end pose and velocity constraints is proposed. The adaptability to the environment is improved by the active compliance control. Finally, experiments are carried out to verify the effectiveness of the proposed design, planning, and control methods.展开更多
This paper focuses on autonomous motion control of a nonholonomic platform with a robotic arm, which is called mobile manipulator. It serves in transportation of loads in imperfectly known industrial environments with...This paper focuses on autonomous motion control of a nonholonomic platform with a robotic arm, which is called mobile manipulator. It serves in transportation of loads in imperfectly known industrial environments with unknown dynamic obstacles. A union of both procedures is used to solve the general problems of collision-free motion. The problem of collision-free motion for mobile manipulators has been approached from two directions, Planning and Reactive Control. The dynamic path planning can be used to solve the problem of locomotion of mobile platform, and reactive approaches can be employed to solve the motion planning of the arm. The execution can generate the commands for the servo-systems of the robot so as to follow a given nominal trajectory while reacting in real-time to unexpected events. The execution can be designed as an Adaptive Fuzzy Neural Controller. In real world systems, sensor-based motion control becomes essential to deal with model uncertainties and unexpected obstacles.展开更多
基金supported by the National Social Science Foundation of China in 2012 under Grant No. 11GJ003-074the Science Foundation of Aeronautics of China under Grant No. 20085584010
文摘Cooperative path dynamic planning of a UCAV （unmanned combat air vehicle） team not only considers the capability of task requirement of single UCAV, but also considers the cooperative dynamic connection among members of the UCAV team. A cooperative path dynamic planning model of the UCAV team by applying a global optimization method is discussed in this paper and the corresponding model is built and analyzed. By the example simulation, the reasonable result acquired indicates that the model could meet dynamic planning demand under the circumstance of membership functions. The model is easy to be realized and has good practicability.
文摘Demand Responsive Transit (DRT) responds to the dynamic users’ requests without any fixed routes and timetablesand determines the stop and the start according to the demands. This study explores the optimization of dynamicvehicle scheduling and real-time route planning in urban public transportation systems, with a focus on busservices. It addresses the limitations of current shared mobility routing algorithms, which are primarily designedfor simpler, single origin/destination scenarios, and do not meet the complex demands of bus transit systems. Theresearch introduces an route planning algorithm designed to dynamically accommodate passenger travel needsand enable real-time route modifications. Unlike traditional methods, this algorithm leverages a queue-based,multi-objective heuristic A∗ approach, offering a solution to the inflexibility and limited coverage of suburbanbus routes. Also, this study conducts a comparative analysis of the proposed algorithm with solutions based onGenetic Algorithm (GA) and Ant Colony Optimization Algorithm (ACO), focusing on calculation time, routelength, passenger waiting time, boarding time, and detour rate. The findings demonstrate that the proposedalgorithmsignificantly enhances route planning speed, achieving an 80–100-fold increase in efficiency over existingmodels, thereby supporting the real-time demands of Demand-Responsive Transportation (DRT) systems. Thestudy concludes that this algorithm not only optimizes route planning in bus transit but also presents a scalablesolution for improving urban mobility.
基金supported by the National Natural Science Foundation of China(51605251)Tsinghua University Initiative Scientific Research Program(2014Z05093).
文摘A new seam-tracking method based on dynamic trajectory planning for a mobile welding robot is proposed in order to improve the response lag of the mobile robot and the high frequency oscillation in seam-tracking.By using a front-placed laser-based vision sensor to dynamically extract the location of the weld seam in front of torch,the trend and direction of the weld line is roughly obtained.The robot system autonomously and dynamically performs trajectory planning based on the isometric approximation model.Arc sensor technology is applied to detect the offset during welding process in real time.The dynamic compensation of the weld path is done in combination with the control of the mobile robot and the executive body installed on it.Simulated and experimental results demonstrate that the method effectively increases the stability of welding speed and smoothness of the weld track,and hence the weld formation in curves and corners is improved.
文摘Presents the mobile robots dynamic motion planning problem with a task to find an obstacle free route that requires minimum travel time from the start point to the destination point in a changing environment, due to the obstacle’s moving. An Genetic Algorithm fuzzy (GA Fuzzy) based optimal approach proposed to find any obstacle free path and the GA used to select the optimal one, points out that using this learned knowledge off line, a mobile robot can navigate to its goal point when it faces new scenario on line. Concludes with the optimal rule base given and the simulation results showing its effectiveness.
基金This project is supported by the Hong Kong Polytechnic University,China(No,G-RGF9).
文摘A dynamic advanced planning and scheduling （DAPS） problem is addressed where new orders arrive on a continuous basis. A periodic policy with frozen interval is adopted to increase stability on the shop floor. A genetic algorithm is developed to find a schedule at each rescheduling point for both original orders and new orders that both production idle time and penalties on tardiness and earliness of orders are minimized. The proposed methodology is tested on a small example to illustrate the effect of the frozen interval. The results indicate that the suggested approach can improve the schedule stability while retaining efficiency.
文摘At the first sight it seems that advanced operation research is not used enough in continuous production systems as comparison with mass production, batch production and job shop systems, but really in a comprehensive evaluation the advanced operation research techniques can be used in continuous production systems in developing countries very widely, because of initial inadequate plant layout, stage by stage development of production lines, the purchase of second hand machineries from various countries, plurality of customers. A case of production system planning is proposed for a chemical company in which the above mentioned conditions are almost presented. The goals and constraints in this issue are as follows： （1） Minimizing deviation of customer＇s requirements. （2） Maximizing the profit. （3） Minimizing the frequencies of changes in formula production. （4） Minimizing the inventory of final products. （5） Balancing the production sections with regard to rate in production. （6） Limitation in inventory of raw material. The present situation is in such a way that various techniques such as goal programming, linear programming and dynamic programming can be used. But dynamic production programming issues are divided into two categories, at first one with limitation in production capacity and another with unlimited production capacity. For the first category, a systematic and acceptable solution has not been presented yet. Therefore an innovative method is used to convert the dynamic situation to a zero- one model. At last this issue is changed to a goal programming model with non-linear limitations with the use of GRG algorithm and that＇s how it is solved.
基金Projects(61071096,61003233,61073103)supported by the National Natural Science Foundation of ChinaProjects(20100162110012,20110162110042)supported by the Research Fund for the Doctoral Program of Higher Education of China
文摘Mission planning was thoroughly studied in the areas of multiple intelligent agent systems,such as multiple unmanned air vehicles,and multiple processor systems.However,it still faces challenges due to the system complexity,the execution order constraints,and the dynamic environment uncertainty.To address it,a coordinated dynamic mission planning scheme is proposed utilizing the method of the weighted AND/OR tree and the AOE-Network.In the scheme,the mission is decomposed into a time-constraint weighted AND/OR tree,which is converted into an AOE-Network for mission planning.Then,a dynamic planning algorithm is designed which uses task subcontracting and dynamic re-decomposition to coordinate conflicts.The scheme can reduce the task complexity and its execution time by implementing real-time dynamic re-planning.The simulation proves the effectiveness of this approach.
文摘Starting with cultural context of historic block, this paper investigated current situation of Shengjinta Historic Block in Nanchang City, Jiangxi Province, proposed dynamic protection planning and sustainable industrial upgrading strategies, specifically, by repairing, clearing, preserving and restoring historic streets and lanes, courtyards and folk dwel ings from six perspectives of planar layout, traffic pattern, spatial texture, facade decoration, landscape planning, and characteristic culture. In view of the specifi c geographical location, food shops and leisure green spaces are constructed to build a modern urban living system for residents in the ancient block.
基金Science and Technology Projects of State Grid Corporation of China(No.SGGSKY00FJJS1800140)。
文摘Aiming at the faults of some weak nodes in the concentrated solar power-photovoltaic(CSP-PV)hybrid power generation system,it is impossible to restore the transient voltage only relying on the reactive power regulation capability of the system itself.We propose a dynamic reactive power planning method suitable for CSP-PV hybrid power generation system.The method determines the installation node of the dynamic reactive power compensation device and its compensation capacity based on the reactive power adjustment capability of the system itself.The critical fault node is determined by the transient voltage stability recovery index,and the weak node of the system is initially determined.Based on this,the sensitivity index is used to determine the installation node of the dynamic reactive power compensation device.Dynamic reactive power planning optimization model is established with the lowest investment cost of dynamic reactive power compensation device and the improvement of system transient voltage stability.Furthermore,the component of the reactive power compensation node is optimized by particle swarm optimization based on differential evolution(DE-PSO).The simulation results of the example system show that compared with the dynamic position compensation device installation location optimization method,the proposed method can improve the transient voltage stability of the system under the same reactive power compensation cost.
基金supported by the National Natural Science Foundation of China(5110917951179156+2 种基金5137917661473233)the Natural Science Basic Research Plan in Shaanxi Province of China(2014JQ8330)
文摘For low-speed underwater vehicles, the ocean currents has a great influence on them, and the changes in ocean currents is complex and continuous, thus whose impact must be taken into consideration in the path planning. There are still lack of authoritative indicator and method for the cooperating path planning. The calculation of the voyage time is a difficult problem in the time-varying ocean, for the existing methods of the cooperating path planning, the computation time will increase exponentially as the autonomous underwater vehicle（AUV） counts increase, rendering them unfeasible. A collaborative path planning method is presehted for multi-AUV under the influence of time-varying ocean currents based on the dynamic programming algorithm. Each AUV cooperates with the one who has the longest estimated time of sailing, enabling the arrays of AUV to get their common goal in the shortest time with minimum timedifference. At the same time, they could avoid the obstacles along the way to the target. Simulation results show that the proposed method has a promising applicability.
文摘Increasing urbanization in the cities of northern Mexico reflects a general trend to increased temperatures, so it is likely that heat waves amplify the frequency and intensity in urban centers, mainly located in arid and semiarid as Mexicali city with extremely arid climate, very hot in summer and cold and rainy in winter. Mexicali, Baja California, Mexico is located at N32°38＇ and W115°20＇. The urban area is expanded over 14,890 hectares, with a population rise the 689,775. In the last four decades has experienced an accelerated industrial growth and mismatched land uses, for example： most of the industrial parks were established before the 1980 in what was the outskirts of the city, but nowadays practically are inside of the urban area contributing to the increase the urban temperature. The heat islands profile shows that are intensified in industrial areas as well as trade and services. The preliminary scenarios of climate change for Mexicali indicate that for the decade of 2080 the temperature will increase between 4.2℃ and 4.4℃. This paper addresses in a simulation context, an industrial and commercial city sector and their ability to implement urban heat island mitigation strategies. The simulation of this process requires several spatial analysis tools and specific knowledge about the processes that increase urban temperatures. In this work, only land use, land cover and buildings are considered. The proposed method takes into account the actual spatial organization to analyze trends for the proposed growth areas.
基金Supported by the National Natural Science Foundation of China(90920304)
文摘A variable dimensional state space（VDSS） has been proposed to improve the re-planning time when the robotic systems operate in large unknown environments.VDSS is constructed by uniforming lattice state space and grid state space.In VDSS,the lattice state space is only used to construct search space in the local area which is a small circle area near the robot,and grid state space elsewhere.We have tested VDSS with up to 80 indoor and outdoor maps in simulation and on segbot robot platform.Through the simulation and segbot robot experiments,it shows that exploring on VDSS is significantly faster than exploring on lattice state space by Anytime Dynamic A＊（AD＊） planner and VDSS is feasible to be used on robotic systems.
文摘Traditionally, heuristic re-planning algorithms are used to tackle the problem of dynamic task planning for multiple satellites. However, the traditional heuristic strategies depend on the concrete tasks, which often affect the result’s optimality. Noticing that the historical information of cooperative task planning will impact the latter planning results, we propose a hybrid learning algorithm for dynamic multi-satellite task planning, which is based on the multi-agent reinforcement learning of policy iteration and the transfer learning. The reinforcement learning strategy of each satellite is described with neural networks. The policy neural network individuals with the best topological structure and weights are found by applying co-evolutionary search iteratively. To avoid the failure of the historical learning caused by the randomly occurring observation requests, a novel approach is proposed to balance the quality and efficiency of the task planning, which converts the historical learning strategy to the current initial learning strategy by applying the transfer learning algorithm. The simulations and analysis show the feasibility and adaptability of the proposed approach especially for the situation with randomly occurring observation requests.
基金supported by the National Defense Foundation of China(No.403060103)
文摘This paper presents a computationally efficient real-time trajectory planning framework for typical unmanned combat aerial vehicle （UCAV） performing autonomous air-to-surface （A/S） attack. It combines the benefits of inverse dynamics optimization method and receding horizon optimal control technique. Firstly, the ground attack trajectory planning problem is mathematically formulated as a receding horizon optimal control problem （RHC-OCP）. In particular, an approximate elliptic launch acceptable region （LAR） model is proposed to model the critical weapon delivery constraints. Secondly, a planning algorithm based on inverse dynamics optimization, which has high computational efficiency and good convergence properties, is developed to solve the RHCOCP in real-time. Thirdly, in order to improve robustness and adaptivity in a dynamic and uncer- tain environment, a two-degree-of-freedom （2-DOF） receding horizon control architecture is introduced and a regular real-time update strategy is proposed as well, and the real-time feedback can be achieved and the not-converged situations can be handled. Finally, numerical simulations demon- strate the efficiency of this framework, and the results also show that the presented technique is well suited for real-time implementation in dynamic and uncertain environment.
文摘Most current research on the trajectory planning of the autonomous lane change focuses on high-speed scenarios and assumes that the states of the surrounding vehicles keep stable during the lane change.The methods based on geometric-curve are mostly used for trajectory planning.In this paper,considering the inevitable development of the autonomous driving,the surrounding vehicles are assumed to be driven by human drivers,while the ego vehicles are able to autonomously change lanes.Representative local lane-change scenarios are then designed and analyzed in detail aiming at medium-and low-speed lane-change conditions.Additionally,in contrast with most research,dynamic trajectory planning which considers the possible state variations of the surrounding vehicles and the driver characteristics is studied and described by a fifth-order polynomial function.The safety and comfort of the dynamic trajectory planning are validated through simulation.Moreover,the elastic soft constraint of the safety domain is designed,whereby the sensitivity of the studied dynamic trajectory planning system is reduced under the premise of ensuring safety.The effectiveness of the elastic soft constraint in terms of improving comfort during the lane change is verified through simulation.The availability of the dynamic trajectory planning system with the elastic soft constraint is demonstrated with the addition of trajectory tracking based on model predictive control,showing its potential in practical applications.
文摘This paper reviewed the development of control technology in domestic and foreign launch vehicle(LV), and based on which, the key technologies of control system for Chinese heavy-lift launch vehicles were proposed. A dynamic on-line trajectory planning technique was discussed to meet the demand of guidance control under complex constraints, and model based identification and adaptive control technology was suggested to deal with the control problems caused by model uncertainty and disturbance, and an integrated avionics system based on high speed communication was put forward for module integration and distributed control, and FBG based real time flight control was also discussed. Moreover, other key technologies, such as wireless interconnection, wireless power transfer, and temporal and spatial partitioning operating system, are both briefly introduced for the application in control systems. These studies will lead to breakthroughs in autonomous flight control in LV, and provide technical support for more long-term deep space explorations.
文摘This paper proposes the architecture of an intelligent flight launcher system as well as fundamental solutions to capability prediction and dynamic planning. This effort reflects the latest progress in the applications of intelligent and autonomous technology for launcher flights. The paper first describes the characteristics and capabilities of intelligent and autonomous systems and classifies various related technologies. In the context of intelligent and autonomous technology in aerospace engineering, it then focuses on technical difficulties involved with intelligent flight and reviews developments in the field. An E^3 classification model of an intelligent flight launcher is then proposed and its application scenarios are discussed. Based on an intelligent flight system configuration of the launcher, the online trajectory planning and initial value guess are examined, and vertical landing is provided as an example to explain the effects of the implementation of computational intelligence to flight systems.
基金supported by National Key Research and Development Program of China (No. 2018AAA0103003)National Natural Science Foundation of China(No. 61773378)+1 种基金the Basic Research Program (No.JCKY*******B029)the Strategic Priority Research Program of Chinese Academy of Sciences (No. XDB32050100)。
文摘In the existing modular joint design and control methods of collaborative robots, the inertia of the manipulator link is large,the dynamic trajectory planning ability is weak, the collision stop safety strategy is dependent, and the adaptability and safety to the changing environment are limited. This paper develops a six-degree-of-freedom lightweight collaborative manipulator with real-time dynamic trajectory planning and active compliance control. Firstly, a novel motor installation, joint transmission, and link design method is put forward to reduce the inertia of the links and improve intrinsic safety. At the same time, to enhance the dynamic operation capability and quick response of the manipulator, a smooth planning of position and orientation under initial/end pose and velocity constraints is proposed. The adaptability to the environment is improved by the active compliance control. Finally, experiments are carried out to verify the effectiveness of the proposed design, planning, and control methods.
文摘This paper focuses on autonomous motion control of a nonholonomic platform with a robotic arm, which is called mobile manipulator. It serves in transportation of loads in imperfectly known industrial environments with unknown dynamic obstacles. A union of both procedures is used to solve the general problems of collision-free motion. The problem of collision-free motion for mobile manipulators has been approached from two directions, Planning and Reactive Control. The dynamic path planning can be used to solve the problem of locomotion of mobile platform, and reactive approaches can be employed to solve the motion planning of the arm. The execution can generate the commands for the servo-systems of the robot so as to follow a given nominal trajectory while reacting in real-time to unexpected events. The execution can be designed as an Adaptive Fuzzy Neural Controller. In real world systems, sensor-based motion control becomes essential to deal with model uncertainties and unexpected obstacles.
