Optimal quadratic control of jump linear systems with Gaussian noise in discrete-time
Optimal quadratic control of jump linear systems with Gaussian noise in discrete-time
复制标题
离散时间高斯噪声跳跃线性系统的最优二次控制
DOI：
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发表时间：
1988
期刊：
影响因子：
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通讯作者：
Y. Ji
中科院分区：
文献类型：
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作者：
H. Chizeck;Y. Ji
研究了最优离散时间跳变线性二次高斯控制问题。被控系统除随机跳变参数服从离散时间有限状态马尔可夫过程外，其余参数均为线性。对于受加性高斯输入和测量噪声影响的系统，二次期望代价最小。假设每次系统结构（即跳跃参数）是已知的。分离特性使作者能够分别设计最优JLQ控制器和最优x状态估计器。基于离散时间跳变线性系统适当的可控性和可观测性，求解了无限时界JLQG问题。最优无限时界JLQG补偿器具有稳态控制律，但不具有稳态滤波器。然后构造了一个次优JLQG补偿器，该补偿器使用收敛于稳态滤波器的滤波器
An optimal discrete-time jump linear quadratic Gaussian (JLQG) control problem is investigated. The system to be controlled is linear, except for randomly jumping parameters which obey a discrete-time finite-state Markov process. A quadratic expected cost is minimized, for systems subject to additive Gaussian input and measurement noise. It is assumed that the system structure (i.e. jumping parameters) is known at each time. A separation property enables the authors to design the optimal JLQ controller and optimal x-state estimator separately. Based on the appropriate controllability and observability properties for discrete-time jump linear systems, the infinite-time-horizon JLQG problem is solved. The optimal infinite-time-horizon JLQG compensator has a steady-state control law but does not have a steady-state filter. A suboptimal JLQG compensator, using a filter which converges to a steady-state filter, is then constructed.<<ETX>>