By introducing Information fusion techniques into a control field, a new theory of information fusion control (IFC) is proposed. Based on the theory of information fusion estimation, optimal control of nonlinear dis...By introducing Information fusion techniques into a control field, a new theory of information fusion control (IFC) is proposed. Based on the theory of information fusion estimation, optimal control of nonlinear discrete control system is investi- gated. All information on control strategy, including ideal control strategy, expected object trajectory and dynamics of system, are regarded as measuring information of control strategy. Therefore, the problem of optimal control is transferred into the one of information fusion estimation. Firstly, the nonlinear information fusion estimation theorems are described. Secondly, an algorithm of nonlinear IFC theory is detailedly deduced. Finally, the simulation results of manipulator shift control are given, which show the feasibility and effectiveness of the presented algorithm.展开更多
基金Supported by the National Natural Science Foundation of China (Grant No. 60673026)
文摘By introducing Information fusion techniques into a control field, a new theory of information fusion control (IFC) is proposed. Based on the theory of information fusion estimation, optimal control of nonlinear discrete control system is investi- gated. All information on control strategy, including ideal control strategy, expected object trajectory and dynamics of system, are regarded as measuring information of control strategy. Therefore, the problem of optimal control is transferred into the one of information fusion estimation. Firstly, the nonlinear information fusion estimation theorems are described. Secondly, an algorithm of nonlinear IFC theory is detailedly deduced. Finally, the simulation results of manipulator shift control are given, which show the feasibility and effectiveness of the presented algorithm.
文摘对非线性时滞离散动态系统的最优控制,提出了一种信息融合估计(information fusion estimation,IFE)方法,把非线性控制问题的所有信息转化为关于控制量的"测量信息",从而使非线性控制问题转化为关于控制量的"非线性估计"问题.通过算例表明,IFE方法明显优于动态系统优化与参数估计的集成(dynamic integrated system optimization and parameter estimation,DISOPE)方法.