To coordinate the various access technologies in the 4G communication system,intelligent vertical handoff algorithms are required.This paper mainly deals with a novel vertical handoff decision algorithm based on fuzzy...To coordinate the various access technologies in the 4G communication system,intelligent vertical handoff algorithms are required.This paper mainly deals with a novel vertical handoff decision algorithm based on fuzzy logic with the aid of grey theory and dynamic weights adaptation.The grey prediction theory(GPT) takes 4 sampled received signal strengths as input parameters,and calculates the predicted received signal strength in order to reduce the call dropping probability.The fuzzy logic theory based quantitative decision algorithm takes 3 quality of service(QoS)metric,received signal strength(RSS),available bandwidth(BW),and monetary cost (MC)of candidate networks as input parameters.The weight of each QoS metrics is adjusted along with the networks changing to trace the network condition.The final optimized vertical handoff decision is made by comparing the quantitative decision values of the candidate networks.Simulation results demonstrate that the proposed algorithm provides high performance in heterogeneous as well as homogeneous network environments.展开更多
Sensorial information is very difficult to elicit, to represent and to manage because of its complexity. Fuzzy logic provides an interesting means to deal with such information, since it allows us to represent impreci...Sensorial information is very difficult to elicit, to represent and to manage because of its complexity. Fuzzy logic provides an interesting means to deal with such information, since it allows us to represent imprecise, vague or incomplete descriptions, which are very common in the management of subjective information. Aggregation methods proposed by fuzzy logic are further useful to combine the characteristics of the various components of sensorial information.展开更多
A novel fuzzy sliding mode control (FSMC) strategy is proposed to enhance the robustness and stability of position control for underactuated quadrotor unmanned aerial vehicles (UAVs) in the presence of external distur...A novel fuzzy sliding mode control (FSMC) strategy is proposed to enhance the robustness and stability of position control for underactuated quadrotor unmanned aerial vehicles (UAVs) in the presence of external disturbances and model uncertainties. To realize the adaptive ability and robustness of the system in complex dynamic environments, an intelligent two-dimensional fuzzy controller is designed based on traditional sliding mode control (SMC) to adjust SMC parameters in real time, thereby adapting to the variable structure parameters of the system. First, based on the designed filter variables regarding errors, traditional SMC is used to reduce tracking errors. Then, the fuzzy logic module (FLM) combined with SMC, i.e., the self-learning module (FLM+SMC), is developed based on the filter variables and their rate of change to adjust the two parameters of the above SMC. Subsequently, the output signals of the FLM are fed back into the SMC module, and then a closed-loop tuning system using FSMC is developed for the UAVs. Moreover, the stability of the FSMC is rigorously verified using the Lyapunov theory. Finally, comprehensive simulations demonstrate that the designed FSMC not only offers accurate trajectory precision but also has robustness and disturbance rejection, and comparative simulations using SMC and adaptive radial basis function neural network control (RBFNNC) are used to validate the result.展开更多
For enhancing the control effectiveness,we firstly design a fuzzy logic based sliding mode controller(FSMC)for nonlinear crane systems.On basis of overhead crane dynamic characteristic,the sliding mode function with r...For enhancing the control effectiveness,we firstly design a fuzzy logic based sliding mode controller(FSMC)for nonlinear crane systems.On basis of overhead crane dynamic characteristic,the sliding mode function with regard to trolley position and payload angle.Additionally,in order to eliminate the chattering problem of sliding mode control,the fuzzy logic theory is adopted to soften the control performance.Moreover,aiming at the FSMC parameter setting problem,a DE algorithm based optimization scheme is proposed for enhancing the control performance.Finally,by implementing the computer simulation,the DE based FSMC can effectively tackle the overhead crane sway problem and avoid unexpected accident greatly.展开更多
基金the National Natural Science Foundation of China(Nos.60832009,60872017 and 60772100)
文摘To coordinate the various access technologies in the 4G communication system,intelligent vertical handoff algorithms are required.This paper mainly deals with a novel vertical handoff decision algorithm based on fuzzy logic with the aid of grey theory and dynamic weights adaptation.The grey prediction theory(GPT) takes 4 sampled received signal strengths as input parameters,and calculates the predicted received signal strength in order to reduce the call dropping probability.The fuzzy logic theory based quantitative decision algorithm takes 3 quality of service(QoS)metric,received signal strength(RSS),available bandwidth(BW),and monetary cost (MC)of candidate networks as input parameters.The weight of each QoS metrics is adjusted along with the networks changing to trace the network condition.The final optimized vertical handoff decision is made by comparing the quantitative decision values of the candidate networks.Simulation results demonstrate that the proposed algorithm provides high performance in heterogeneous as well as homogeneous network environments.
文摘Sensorial information is very difficult to elicit, to represent and to manage because of its complexity. Fuzzy logic provides an interesting means to deal with such information, since it allows us to represent imprecise, vague or incomplete descriptions, which are very common in the management of subjective information. Aggregation methods proposed by fuzzy logic are further useful to combine the characteristics of the various components of sensorial information.
基金supported by the National Natural Science Foundation of China(Nos.61971120,62171285,62033009,and 62327807)the National Key Research and Development Program of China(No.2021YFC2801300)。
文摘A novel fuzzy sliding mode control (FSMC) strategy is proposed to enhance the robustness and stability of position control for underactuated quadrotor unmanned aerial vehicles (UAVs) in the presence of external disturbances and model uncertainties. To realize the adaptive ability and robustness of the system in complex dynamic environments, an intelligent two-dimensional fuzzy controller is designed based on traditional sliding mode control (SMC) to adjust SMC parameters in real time, thereby adapting to the variable structure parameters of the system. First, based on the designed filter variables regarding errors, traditional SMC is used to reduce tracking errors. Then, the fuzzy logic module (FLM) combined with SMC, i.e., the self-learning module (FLM+SMC), is developed based on the filter variables and their rate of change to adjust the two parameters of the above SMC. Subsequently, the output signals of the FLM are fed back into the SMC module, and then a closed-loop tuning system using FSMC is developed for the UAVs. Moreover, the stability of the FSMC is rigorously verified using the Lyapunov theory. Finally, comprehensive simulations demonstrate that the designed FSMC not only offers accurate trajectory precision but also has robustness and disturbance rejection, and comparative simulations using SMC and adaptive radial basis function neural network control (RBFNNC) are used to validate the result.
基金This work is supported by the Natural Science Foundation of Jiangsu Province(No.BK20160913)the Natural Science Foundation of the Jiangsu Higher Education Institutions of China(No.18KJB520035)+4 种基金the High Level Teacher Research Foundation of Nanjing University of Posts and Telecommunications(No.NY2016021)the Incubation Foundation of Nanjing University of Posts and Telecommunications(No.NY217055)Postdoctoral Foundation of Jiangsu Province(No.1701016A)Natural Science Foundation of China(No.61602259,No.61373135 and No.61672299)National Engineering Laboratory for Logistics Information Technology,YuanTong Express Co.LTD.
文摘For enhancing the control effectiveness,we firstly design a fuzzy logic based sliding mode controller(FSMC)for nonlinear crane systems.On basis of overhead crane dynamic characteristic,the sliding mode function with regard to trolley position and payload angle.Additionally,in order to eliminate the chattering problem of sliding mode control,the fuzzy logic theory is adopted to soften the control performance.Moreover,aiming at the FSMC parameter setting problem,a DE algorithm based optimization scheme is proposed for enhancing the control performance.Finally,by implementing the computer simulation,the DE based FSMC can effectively tackle the overhead crane sway problem and avoid unexpected accident greatly.
