In order to solve three kinds of fuzzy programming models, i.e. fuzzy expected value model, fuzzy chance-constrained programming model, and fuzzy dependent-chance pro-gramming model, a simultaneous perturbation stocha...In order to solve three kinds of fuzzy programming models, i.e. fuzzy expected value model, fuzzy chance-constrained programming model, and fuzzy dependent-chance pro-gramming model, a simultaneous perturbation stochastic approximation algorithm is proposed by integrating neural network with fuzzy simulation. At first, fuzzy simulation is used to generate a set of input-output data. Then a neural network is trained according to the set. Finally, the trained neural network is embedded in simultaneous perturbation stochastic approximation algorithm. Simultaneous perturbation stochastic approximation algorithm is used to search the optimal solution. Two numerical examples are presented to illustrate the effectiveness of the proposed algorithm.展开更多
This paper considers adaptive control of parallel manipulators combined with fuzzy-neural network algorithms （FNNA）. With this algorithm, the robustness is guaranteed by the adaptive control law and the parametric u...This paper considers adaptive control of parallel manipulators combined with fuzzy-neural network algorithms （FNNA）. With this algorithm, the robustness is guaranteed by the adaptive control law and the parametric uncertainties are eliminated. FNNA is used to handle model uncertainties and external disturbances. In the proposed control scheme, we consider modifying the weight of fuzzy rules and present these rules to a MIMO system of parallel manipulators with more than three degrees-of-freedom （DoF）. The algorithm has the advantage of not requiring the inverse of the Jacobian matrix especially for the low DoF parallel manipulators. The validity of the control scheme is shown through numerical simulations of a 6-RPS parallel manipulator with three DoF.展开更多
This paper combines image processing with 3D magnetic tracking method to develop a scalpel for haptic simulation in surgical cutting. First, a cutting parameter acquisition setup is presented and the performance is va...This paper combines image processing with 3D magnetic tracking method to develop a scalpel for haptic simulation in surgical cutting. First, a cutting parameter acquisition setup is presented and the performance is validated from soft tissue cutting. Then, based on the acquired input-output data pairs, a method for fuzzy system modeling is presented, that is, after partitioning each input space equally and giving the premises and the total number of fuzzy rules, the consequent parameters and the fuzzy membership functions (MF) of the input variables are learned and optimized via a neurofuzzy modeling technique. Finally, a haptic scalpel implemented with the established cutting model is described. Preliminary results show the feasibility of the haptic display system for real-time interaction.展开更多
在三种常规控制器的基础上,采用 BP 网络设计了三种神经网络控制器,即神经自校正控制器,神经网络 PID 控制器和神经模型参考自适应控制器,并都通过 BP 算法进行训练,针对三个仿真实例用 MATLAB 软件工具进行了仿真,仿真结果证明了方案...在三种常规控制器的基础上,采用 BP 网络设计了三种神经网络控制器,即神经自校正控制器,神经网络 PID 控制器和神经模型参考自适应控制器,并都通过 BP 算法进行训练,针对三个仿真实例用 MATLAB 软件工具进行了仿真,仿真结果证明了方案的可行性。展开更多
基金National Natural Science Foundation of China (No.70471049)China Postdoctoral Science Foundation (No. 20060400704)
文摘In order to solve three kinds of fuzzy programming models, i.e. fuzzy expected value model, fuzzy chance-constrained programming model, and fuzzy dependent-chance pro-gramming model, a simultaneous perturbation stochastic approximation algorithm is proposed by integrating neural network with fuzzy simulation. At first, fuzzy simulation is used to generate a set of input-output data. Then a neural network is trained according to the set. Finally, the trained neural network is embedded in simultaneous perturbation stochastic approximation algorithm. Simultaneous perturbation stochastic approximation algorithm is used to search the optimal solution. Two numerical examples are presented to illustrate the effectiveness of the proposed algorithm.
基金This work was supported by the National Natural Science Foundation of China (No. 50375001)
文摘This paper considers adaptive control of parallel manipulators combined with fuzzy-neural network algorithms （FNNA）. With this algorithm, the robustness is guaranteed by the adaptive control law and the parametric uncertainties are eliminated. FNNA is used to handle model uncertainties and external disturbances. In the proposed control scheme, we consider modifying the weight of fuzzy rules and present these rules to a MIMO system of parallel manipulators with more than three degrees-of-freedom （DoF）. The algorithm has the advantage of not requiring the inverse of the Jacobian matrix especially for the low DoF parallel manipulators. The validity of the control scheme is shown through numerical simulations of a 6-RPS parallel manipulator with three DoF.
基金Supported by National Natural Science Foundation of P. R. China (60273028)
文摘This paper combines image processing with 3D magnetic tracking method to develop a scalpel for haptic simulation in surgical cutting. First, a cutting parameter acquisition setup is presented and the performance is validated from soft tissue cutting. Then, based on the acquired input-output data pairs, a method for fuzzy system modeling is presented, that is, after partitioning each input space equally and giving the premises and the total number of fuzzy rules, the consequent parameters and the fuzzy membership functions (MF) of the input variables are learned and optimized via a neurofuzzy modeling technique. Finally, a haptic scalpel implemented with the established cutting model is described. Preliminary results show the feasibility of the haptic display system for real-time interaction.
