This paper presents fuzzy-based design for the control of overhead crane. Instead of analyzing the complex nonlinear crane system, the proposed approach uses simple but effective way to control the crane. There are tw...This paper presents fuzzy-based design for the control of overhead crane. Instead of analyzing the complex nonlinear crane system, the proposed approach uses simple but effective way to control the crane. There are twin fuzzy controllers which deal with the feedback information, the position of trolley crane and the swing angle of load, to suppress the sway and accelerate the speed when the crane transports the heavy load. This approach simplifies the designing procedure of crane controller; besides, the twin controller method reduces the rule number when fulfilling the fuzzy system. Finally, experimental results through the crane model demonstrate the effectiveness of the scheme.展开更多
In this paper, a new adaptive hierarchical sliding mode control scheme for a 3D overhead crane system is proposed. A controller is first designed by the use of a hierarchical structure of two first-order sliding surfa...In this paper, a new adaptive hierarchical sliding mode control scheme for a 3D overhead crane system is proposed. A controller is first designed by the use of a hierarchical structure of two first-order sliding surfaces represented by two actuated and un-actuated subsystems in the bridge crane. Parameters of the controller are then intelligently estimated, where uncertain parameters due to disturbances in the 3D overhead crane dynamic model are proposed to be represented by radial basis function networks whose weights are derived from a Lyapunov function. The proposed approach allows the crane system to be robust under uncertainty conditions in which some uncertain and unknown parameters are highly difficult to determine. Moreover, stability of the sliding surfaces is proved to be guaranteed. Effectiveness of the proposed approach is then demonstrated by implementing the algorithm in both synthetic and reallife systems, where the results obtained by our method are highly promising.展开更多
Solving the controller placement problem (CPP) in an SDN architecture with multiple controllers has a significant impact on control overhead in the network, especially in multihop wireless networks (MWNs). The generat...Solving the controller placement problem (CPP) in an SDN architecture with multiple controllers has a significant impact on control overhead in the network, especially in multihop wireless networks (MWNs). The generated control overhead consists of controller-device and inter-controller communications to discover the network topology, exchange configurations, and set up and modify flow tables in the control plane. However, due to the high complexity of the proposed optimization model to the CPP, heuristic algorithms have been reported to find near-optimal solutions faster for large-scale wired networks. In this paper, the objective is to extend those existing heuristic algorithms to solve a proposed optimization model to the CPP in software-<span>defined multihop wireless networking</span><span> (SDMWN).</span>Our results demonstrate that using ranking degrees assigned to the possible controller placements, including the average distance to other devices as a degree or the connectivity degree of each placement, the extended heuristic algorithms are able to achieve the optimal solution in small-scale networks in terms of the generated control overhead and the number of controllers selected in the network. As a result, using extended heuristic algorithms, the average number of hops among devices and their assigned controllers as well as among controllers will be reduced. Moreover, these algorithms are able tolower<span "=""> </span>the control overhead in large-scale networks and select fewer controllers compared to an extended algorithm that solves the CPP in SDMWN based on a randomly selected controller placement approach.展开更多
The control of underactuated mechanical systems is very complex for the loss of its control inputs. The model of underactuated mechanical systems in a potential field is built with Lagrangian method and its structural...The control of underactuated mechanical systems is very complex for the loss of its control inputs. The model of underactuated mechanical systems in a potential field is built with Lagrangian method and its structural properties are analyzed in detail. A stable control approach is proposed for the class of underactuated mechanical systems. This approach is applied to an underactuated double-pendulum-type overhead crane and the simulation results illustrate the correctness of dynamics analysis and validity of the proposed control algorithm.展开更多
移动自组网(Mobile Ad Hoc Network, MANET)主要应用于军事活动、灾后救援等大规模的活动中,随着节点数的增加、移动速度的加快,网络拓扑变得更加复杂,网络稳定性和性能也随之下降。频繁的网络拓扑变化会导致簇结构变得不稳定并且控制...移动自组网(Mobile Ad Hoc Network, MANET)主要应用于军事活动、灾后救援等大规模的活动中,随着节点数的增加、移动速度的加快,网络拓扑变得更加复杂,网络稳定性和性能也随之下降。频繁的网络拓扑变化会导致簇结构变得不稳定并且控制开销也会增加。为了解决这一问题,提出了一种改进的加权分簇算法,通过仿真表明,该算法可以有效地提高大规模移动自组网的性能。展开更多
基金This work was supported bythe National Science Council ofthe Republic of China (No .NSC-91-2213-E-231-007) .
文摘This paper presents fuzzy-based design for the control of overhead crane. Instead of analyzing the complex nonlinear crane system, the proposed approach uses simple but effective way to control the crane. There are twin fuzzy controllers which deal with the feedback information, the position of trolley crane and the swing angle of load, to suppress the sway and accelerate the speed when the crane transports the heavy load. This approach simplifies the designing procedure of crane controller; besides, the twin controller method reduces the rule number when fulfilling the fuzzy system. Finally, experimental results through the crane model demonstrate the effectiveness of the scheme.
文摘In this paper, a new adaptive hierarchical sliding mode control scheme for a 3D overhead crane system is proposed. A controller is first designed by the use of a hierarchical structure of two first-order sliding surfaces represented by two actuated and un-actuated subsystems in the bridge crane. Parameters of the controller are then intelligently estimated, where uncertain parameters due to disturbances in the 3D overhead crane dynamic model are proposed to be represented by radial basis function networks whose weights are derived from a Lyapunov function. The proposed approach allows the crane system to be robust under uncertainty conditions in which some uncertain and unknown parameters are highly difficult to determine. Moreover, stability of the sliding surfaces is proved to be guaranteed. Effectiveness of the proposed approach is then demonstrated by implementing the algorithm in both synthetic and reallife systems, where the results obtained by our method are highly promising.
文摘Solving the controller placement problem (CPP) in an SDN architecture with multiple controllers has a significant impact on control overhead in the network, especially in multihop wireless networks (MWNs). The generated control overhead consists of controller-device and inter-controller communications to discover the network topology, exchange configurations, and set up and modify flow tables in the control plane. However, due to the high complexity of the proposed optimization model to the CPP, heuristic algorithms have been reported to find near-optimal solutions faster for large-scale wired networks. In this paper, the objective is to extend those existing heuristic algorithms to solve a proposed optimization model to the CPP in software-<span>defined multihop wireless networking</span><span> (SDMWN).</span>Our results demonstrate that using ranking degrees assigned to the possible controller placements, including the average distance to other devices as a degree or the connectivity degree of each placement, the extended heuristic algorithms are able to achieve the optimal solution in small-scale networks in terms of the generated control overhead and the number of controllers selected in the network. As a result, using extended heuristic algorithms, the average number of hops among devices and their assigned controllers as well as among controllers will be reduced. Moreover, these algorithms are able tolower<span "=""> </span>the control overhead in large-scale networks and select fewer controllers compared to an extended algorithm that solves the CPP in SDMWN based on a randomly selected controller placement approach.
基金Supported by National Natural Science Foundation of P.R.China (60575047)
文摘The control of underactuated mechanical systems is very complex for the loss of its control inputs. The model of underactuated mechanical systems in a potential field is built with Lagrangian method and its structural properties are analyzed in detail. A stable control approach is proposed for the class of underactuated mechanical systems. This approach is applied to an underactuated double-pendulum-type overhead crane and the simulation results illustrate the correctness of dynamics analysis and validity of the proposed control algorithm.
文摘移动自组网(Mobile Ad Hoc Network, MANET)主要应用于军事活动、灾后救援等大规模的活动中,随着节点数的增加、移动速度的加快,网络拓扑变得更加复杂,网络稳定性和性能也随之下降。频繁的网络拓扑变化会导致簇结构变得不稳定并且控制开销也会增加。为了解决这一问题,提出了一种改进的加权分簇算法,通过仿真表明,该算法可以有效地提高大规模移动自组网的性能。
