An adaptive output feedback control was proposed to deal with a class of nonholonomic systems in chained form with strong nonlinear disturbances and drift terms. The objective was to design adaptive nonlinear output f...An adaptive output feedback control was proposed to deal with a class of nonholonomic systems in chained form with strong nonlinear disturbances and drift terms. The objective was to design adaptive nonlinear output feedback laws such that the closed-loop systems were globally asymptotically stable, while the estimated parameters remained bounded. The proposed systematic strategy combined input-state-scaling with backstepping technique. The adaptive output feedback controller was designed for a general case of uncertain chained system. Furthermore, one special case was considered. Simulation results demonstrate the effectiveness of the proposed controllers.展开更多
Y2000-62203-3003 0015723机械臂的自适应控制(含5篇论文)=FA02:Adaptivecontrol of robotic manipulators[会,英]//1999 IEEEProceedings of American Control Conference,Vol.5 of6.—3003～3022(NiD)本部分收录5篇论文,内容涉及刚性...Y2000-62203-3003 0015723机械臂的自适应控制(含5篇论文)=FA02:Adaptivecontrol of robotic manipulators[会,英]//1999 IEEEProceedings of American Control Conference,Vol.5 of6.—3003～3022(NiD)本部分收录5篇论文,内容涉及刚性串连机械臂控制设计的基本特性,机械臂具有采样率与自由参数监督的自适应控制,水下机械臂系统的自适应控制,机械臂的综合自适应输出反馈跟踪控制器,输入含滞环系统的自适应控制。Y2000-62203-3505 0015724强非线性系统的自适应学习与鲁棒控制(含6篇论文)=FM02:Adaptive learning and robust control of Strong-ly nonlinear systems[会,英]//1999 IEEE Proceedings ofAmerican Control Conference,Vol.5 of 6.—3505～3533(NiD)本部分收录6篇论文。展开更多
Y2001-62832-3128 0116074自适应控制(含6篇文章)=FA07:Adaptive control[会,英]∥2000 IEEE American Control Conference,Vol.5.—3128～3157(NiE)本部分收录6篇论文,内容涉及一类时变非线性系统的直接与间接自适应控制,二阶系统的输...Y2001-62832-3128 0116074自适应控制(含6篇文章)=FA07:Adaptive control[会,英]∥2000 IEEE American Control Conference,Vol.5.—3128～3157(NiE)本部分收录6篇论文,内容涉及一类时变非线性系统的直接与间接自适应控制,二阶系统的输出反馈自适应稳定,不确定劳伦斯系统的无奇异点后退控制,非线性系统的自适应输出反馈神经网络控制,一类非线性系统直接自适应控制的稳定。展开更多
This paper adopts the concept of dynamic feedback systems to model the behavior of financial markets, or more specifically, the stock market from a dynamic system point of view. Based on a feedback adaptation scheme, ...This paper adopts the concept of dynamic feedback systems to model the behavior of financial markets, or more specifically, the stock market from a dynamic system point of view. Based on a feedback adaptation scheme, the authors model the movement of a stock market index within a framework that is composed of an internal dynamic model and an adaptive filter. The output-error model is adopted as the internal model whereas the adaptive filter is a time-varying state space model with instrumental variables. Its input-output behavior, and internal as well as external forces are then identified. Special attention has also been paid to the recent financial crisis by examining the movement of Dow Jones Industrial Average （DJIA） as an example to illustrate the advantage of the proposed framework. Supported by time-varying causality tests, five influential factors from economic and sentiment aspects are introduced as the input of this framework. Testing results show that the proposed framework has a much better prediction performance than the existing methods, especially in complicated economic situations. An application of this framework is also presented with focuses on forecasting the turning periods of the market trend. Realizing that a market trend is about to change when the external force begins to exhibit clear patterns in its frequency responses, the authors develop a set of rules to recognize this kind of clear patterns. These rules work well for stock indexes from US, China and Singapore.展开更多
基金Project(60704005) supported by the National Natural Science Foundation of China Project(07ZR14119) supported by Natural Science Foundation of Shanghai Science and Technology Commission Project(2009AA04Z213) supported by the National High-Tech Research and Development Program of China
文摘An adaptive output feedback control was proposed to deal with a class of nonholonomic systems in chained form with strong nonlinear disturbances and drift terms. The objective was to design adaptive nonlinear output feedback laws such that the closed-loop systems were globally asymptotically stable, while the estimated parameters remained bounded. The proposed systematic strategy combined input-state-scaling with backstepping technique. The adaptive output feedback controller was designed for a general case of uncertain chained system. Furthermore, one special case was considered. Simulation results demonstrate the effectiveness of the proposed controllers.
文摘Y2000-62203-3003 0015723机械臂的自适应控制(含5篇论文)=FA02:Adaptivecontrol of robotic manipulators[会,英]//1999 IEEEProceedings of American Control Conference,Vol.5 of6.—3003～3022(NiD)本部分收录5篇论文,内容涉及刚性串连机械臂控制设计的基本特性,机械臂具有采样率与自由参数监督的自适应控制,水下机械臂系统的自适应控制,机械臂的综合自适应输出反馈跟踪控制器,输入含滞环系统的自适应控制。Y2000-62203-3505 0015724强非线性系统的自适应学习与鲁棒控制(含6篇论文)=FM02:Adaptive learning and robust control of Strong-ly nonlinear systems[会,英]//1999 IEEE Proceedings ofAmerican Control Conference,Vol.5 of 6.—3505～3533(NiD)本部分收录6篇论文。
文摘Y2001-62832-3128 0116074自适应控制(含6篇文章)=FA07:Adaptive control[会,英]∥2000 IEEE American Control Conference,Vol.5.—3128～3157(NiE)本部分收录6篇论文,内容涉及一类时变非线性系统的直接与间接自适应控制,二阶系统的输出反馈自适应稳定,不确定劳伦斯系统的无奇异点后退控制,非线性系统的自适应输出反馈神经网络控制,一类非线性系统直接自适应控制的稳定。
文摘This paper adopts the concept of dynamic feedback systems to model the behavior of financial markets, or more specifically, the stock market from a dynamic system point of view. Based on a feedback adaptation scheme, the authors model the movement of a stock market index within a framework that is composed of an internal dynamic model and an adaptive filter. The output-error model is adopted as the internal model whereas the adaptive filter is a time-varying state space model with instrumental variables. Its input-output behavior, and internal as well as external forces are then identified. Special attention has also been paid to the recent financial crisis by examining the movement of Dow Jones Industrial Average （DJIA） as an example to illustrate the advantage of the proposed framework. Supported by time-varying causality tests, five influential factors from economic and sentiment aspects are introduced as the input of this framework. Testing results show that the proposed framework has a much better prediction performance than the existing methods, especially in complicated economic situations. An application of this framework is also presented with focuses on forecasting the turning periods of the market trend. Realizing that a market trend is about to change when the external force begins to exhibit clear patterns in its frequency responses, the authors develop a set of rules to recognize this kind of clear patterns. These rules work well for stock indexes from US, China and Singapore.
