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对参数已知的线性系统能任意极点配置的充要条件是系统能控 ,只假设系统能控来解决单输入系数未知的随机系统的极点配置问题 .系统噪声要求相互独立 ,均值为零并且二阶矩一致有界 .提供两种解决方法 :当系统的状态在固定时刻对不同反馈增益可反复量测时 ,用迭代学习方法 ;当系统的轨线满足非退化条件时 ,可用适应控制法 .两种方法都本质地基于随机逼近递推地计算反馈增益 ,但不用必然等价原则 .
The necessary and sufficient condition for any pole configuration of a given linear system with known parameters is that the system can be controlled and only the system controllable is assumed to solve the pole placement problem of stochastic systems with unknown input coefficients. The system noise requirements are independent of each other with a mean value of zero and two There are two solutions to this problem: iterative learning method is used when the state of the system can be measured repeatedly for different feedback gains at a fixed time; adaptive control method is available when the trajectory of the system satisfies non-degenerate conditions. Both approaches essentially recursively calculate the feedback gain based on stochastic approximations, but not necessarily the principle of equivalence.