The helicopter Trailing-Edge Flaps(TEFs)technology is one of the recent hot topics in morphing wing research.By employing controlled deflection,TEFs can effectively reduce the vibration level of helicopters.Thus,desig...The helicopter Trailing-Edge Flaps(TEFs)technology is one of the recent hot topics in morphing wing research.By employing controlled deflection,TEFs can effectively reduce the vibration level of helicopters.Thus,designing specific vibration reduction control methods for the helicopters equipped with trailing-edge flaps is of significant practical value.This paper studies the optimal control problem for helicopter-vibration systems with TEFs under the framework of adaptive dynamic programming combined with Reinforcement Learning(RL).Time-delay and disturbances,caused by complexity of helicopter dynamics,inevitably deteriorate the control performance of vibration reduction.To solve this problem,a zero-sum game formulation with a linear quadratic form for reducing vibration of helicopter systems is presented with a virtual predictor.In this context,an off-policy reinforcement learning algorithm is developed to determine the optimal control policy.The algorithm utilizes only vertical vibration load data to achieve a policy that reduces vibration,attains Nash equilibrium,and addresses disturbances while compensating for time-delay without knowledge of the dynamics of the helicopter system.The effectiveness of the proposed method is demonstrated in a virtual platform.展开更多
Heterogeneous network(HetNet) as a promising technology to improve spectrum efficiency and system capacity has been concerned by many scholars, which brings huge challenges for power allocation and interference manage...Heterogeneous network(HetNet) as a promising technology to improve spectrum efficiency and system capacity has been concerned by many scholars, which brings huge challenges for power allocation and interference management in multicell network structures. Although some works have been done for power allocation in heterogeneous femtocell networks, most of them focus centralized schemes for single-cell network under interference constraint of macrocell user. In this paper, a sum-rate maximization based power allocation algorithm is proposed for a downlink cognitive Het Net with one macrocell network and multiple microcell networks. The original power allocation optimization problem with the consideration of cross-tier interference constraint, maximum transmit power constraint of microcell base station and inter-cell interference of microcell networks is converted into a geometric programming problem which can be solved by Lagrange dual method in a distributed way. Simulation results demonstrate the performance and effectiveness of the proposed algorithm by comparing with the equal power allocation scheme.展开更多
To enhance the effectiveness of watershed load reduction decision making, the Risk Explicit Interval Linear Programming （REILP） approach was developed in previous studies to address decision risks and system returns...To enhance the effectiveness of watershed load reduction decision making, the Risk Explicit Interval Linear Programming （REILP） approach was developed in previous studies to address decision risks and system returns. However, REILP lacks the capability to analyze the tradeoff between risks in the objective function and constraints. Therefore, a refined REILP model is proposed in this study to further enhance the decision support capability of the REILP approach for optimal watershed load reduction. By introducing a tradeofffactor （α） into the total risk function, the refined REILP can lead to different compromises between risks associated with the objective functions and the constraints. The proposed model was illustrated using a case study that deals with uncertainty- based optimal load reduction decision making for Lake Qionghai Watershed, China. A risk tradeoff curve with different values of a was presented to decision makers as a more flexible platform to support decision formulation. The results of the standard and refined REILP model were compared under 11 aspiration levels. The results demon- strate that, by applying the refined REILP, it is possible to obtain solutions that preserve the same constraint risk as that in the standard REILP but with lower objective risk, which can provide more effective guidance for decision makers.展开更多
The phases of water environmental system (WES) and their emphatic intersections areanalysed in this paper. and from the view point of system analysis , an analytical process of WES is provided. Based on the balance ne...The phases of water environmental system (WES) and their emphatic intersections areanalysed in this paper. and from the view point of system analysis , an analytical process of WES is provided. Based on the balance network of WES, a goal programming model for regional water environmentalplanning and the main computational result for a coastal city are provided , thus proving its usefulness andeffectiveness.展开更多
A simple but illustrative survey is given on various approaches of computational intelligence with their features, applications and the mathematical tools involved, among which the simulated annealing, neural networks...A simple but illustrative survey is given on various approaches of computational intelligence with their features, applications and the mathematical tools involved, among which the simulated annealing, neural networks, genetic and evolutionary programming, self-organizing learning and adapting algorithms, hidden Markov models are recommended intensively. The common mathematical features of various computational intelligence algorithms are exploited.Finally, two common principles of concessive strategies implicated in many computational intelligence algorithms are discussed.展开更多
This paper proposes an object oriented model scheduling for parallel computing in media MultiProcessors System on Chip(MPSoC).Firstly,the Coarse Grain Data Flow Graph(CGDFG) parallel programming model is used in this ...This paper proposes an object oriented model scheduling for parallel computing in media MultiProcessors System on Chip(MPSoC).Firstly,the Coarse Grain Data Flow Graph(CGDFG) parallel programming model is used in this approach.Secondly,this approach has the feature of unified abstraction for software objects implementing in processor and hardware objects implementing in ASICs,easy for mapping CGDFG programming on MPSoC.This approach cuts down the kernel overhead and reduces the code size effectively.The principle of the oriented object model,the method of scheduling,and how to map a parallel programming through CGDFG to the MPSoC are analyzed in this approach.This approach also compares the code size and execution cycles with conventional control flow scheduling,and presents respective management overhead for one application in me-dia-SoC.展开更多
An alpha-uniformized Markov chain is defined by the concept of equivalent infinitesimalgenerator for a semi-Markov decision process (SMDP) with both average- and discounted-criteria.According to the relations of their...An alpha-uniformized Markov chain is defined by the concept of equivalent infinitesimalgenerator for a semi-Markov decision process (SMDP) with both average- and discounted-criteria.According to the relations of their performance measures and performance potentials, the optimiza-tion of an SMDP can be realized by simulating the chain. For the critic model of neuro-dynamicprogramming (NDP), a neuro-policy iteration (NPI) algorithm is presented, and the performanceerror bound is shown as there are approximate error and improvement error in each iteration step.The obtained results may be extended to Markov systems, and have much applicability. Finally, anumerical example is provided.展开更多
基金co-supported by the National Natural Science Foundation of China(Nos.62022060,62073234,62073158,62373268,62373273)the Basic Research Project of Education Department of Liaoning Province,China(No.LJKZ0401).
文摘The helicopter Trailing-Edge Flaps(TEFs)technology is one of the recent hot topics in morphing wing research.By employing controlled deflection,TEFs can effectively reduce the vibration level of helicopters.Thus,designing specific vibration reduction control methods for the helicopters equipped with trailing-edge flaps is of significant practical value.This paper studies the optimal control problem for helicopter-vibration systems with TEFs under the framework of adaptive dynamic programming combined with Reinforcement Learning(RL).Time-delay and disturbances,caused by complexity of helicopter dynamics,inevitably deteriorate the control performance of vibration reduction.To solve this problem,a zero-sum game formulation with a linear quadratic form for reducing vibration of helicopter systems is presented with a virtual predictor.In this context,an off-policy reinforcement learning algorithm is developed to determine the optimal control policy.The algorithm utilizes only vertical vibration load data to achieve a policy that reduces vibration,attains Nash equilibrium,and addresses disturbances while compensating for time-delay without knowledge of the dynamics of the helicopter system.The effectiveness of the proposed method is demonstrated in a virtual platform.
基金supported by the National Natural Science Foundation of China (Grant No.61601071)the Scientific and Technological Research Program of Chongqing Municipal Education Commission (Grant No.KJ16004012)+2 种基金the Municipal Natural Science Foundation of Chongqing (Grant No.CSTC2016JCYJA2197)the Seventeenth Open Foundation of State Key Lab of Integrated Services Networks of Xidian University (Grant No.ISN17-01)the Dr. Startup Founds of Chongqing University of Posts and Telecommunications (Grant No.A2016-12)
文摘Heterogeneous network(HetNet) as a promising technology to improve spectrum efficiency and system capacity has been concerned by many scholars, which brings huge challenges for power allocation and interference management in multicell network structures. Although some works have been done for power allocation in heterogeneous femtocell networks, most of them focus centralized schemes for single-cell network under interference constraint of macrocell user. In this paper, a sum-rate maximization based power allocation algorithm is proposed for a downlink cognitive Het Net with one macrocell network and multiple microcell networks. The original power allocation optimization problem with the consideration of cross-tier interference constraint, maximum transmit power constraint of microcell base station and inter-cell interference of microcell networks is converted into a geometric programming problem which can be solved by Lagrange dual method in a distributed way. Simulation results demonstrate the performance and effectiveness of the proposed algorithm by comparing with the equal power allocation scheme.
基金This paper was supported by the National Natural Science Foundation of China （Grant No. 41222002）, Research Fund for the Doctoral Program of Higher Education of China （20100001120020） and ＂China National Water Pollution Control Program＂ （2013ZX07102-006）. Special thanks to Dr. Daniel Obenour in University of Michigan.
文摘To enhance the effectiveness of watershed load reduction decision making, the Risk Explicit Interval Linear Programming （REILP） approach was developed in previous studies to address decision risks and system returns. However, REILP lacks the capability to analyze the tradeoff between risks in the objective function and constraints. Therefore, a refined REILP model is proposed in this study to further enhance the decision support capability of the REILP approach for optimal watershed load reduction. By introducing a tradeofffactor （α） into the total risk function, the refined REILP can lead to different compromises between risks associated with the objective functions and the constraints. The proposed model was illustrated using a case study that deals with uncertainty- based optimal load reduction decision making for Lake Qionghai Watershed, China. A risk tradeoff curve with different values of a was presented to decision makers as a more flexible platform to support decision formulation. The results of the standard and refined REILP model were compared under 11 aspiration levels. The results demon- strate that, by applying the refined REILP, it is possible to obtain solutions that preserve the same constraint risk as that in the standard REILP but with lower objective risk, which can provide more effective guidance for decision makers.
文摘The phases of water environmental system (WES) and their emphatic intersections areanalysed in this paper. and from the view point of system analysis , an analytical process of WES is provided. Based on the balance network of WES, a goal programming model for regional water environmentalplanning and the main computational result for a coastal city are provided , thus proving its usefulness andeffectiveness.
文摘A simple but illustrative survey is given on various approaches of computational intelligence with their features, applications and the mathematical tools involved, among which the simulated annealing, neural networks, genetic and evolutionary programming, self-organizing learning and adapting algorithms, hidden Markov models are recommended intensively. The common mathematical features of various computational intelligence algorithms are exploited.Finally, two common principles of concessive strategies implicated in many computational intelligence algorithms are discussed.
基金Supported by National Natural Science Foundation ofChina (No.60873112)
文摘This paper proposes an object oriented model scheduling for parallel computing in media MultiProcessors System on Chip(MPSoC).Firstly,the Coarse Grain Data Flow Graph(CGDFG) parallel programming model is used in this approach.Secondly,this approach has the feature of unified abstraction for software objects implementing in processor and hardware objects implementing in ASICs,easy for mapping CGDFG programming on MPSoC.This approach cuts down the kernel overhead and reduces the code size effectively.The principle of the oriented object model,the method of scheduling,and how to map a parallel programming through CGDFG to the MPSoC are analyzed in this approach.This approach also compares the code size and execution cycles with conventional control flow scheduling,and presents respective management overhead for one application in me-dia-SoC.
文摘An alpha-uniformized Markov chain is defined by the concept of equivalent infinitesimalgenerator for a semi-Markov decision process (SMDP) with both average- and discounted-criteria.According to the relations of their performance measures and performance potentials, the optimiza-tion of an SMDP can be realized by simulating the chain. For the critic model of neuro-dynamicprogramming (NDP), a neuro-policy iteration (NPI) algorithm is presented, and the performanceerror bound is shown as there are approximate error and improvement error in each iteration step.The obtained results may be extended to Markov systems, and have much applicability. Finally, anumerical example is provided.
