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摘要: 对于普遍存在的具有未知参数的随机最优控制问题，本文提出了一种具有学习特点的控制器设计算法.该算法用Kalman滤波估计系统的未知参数，在滚动优化机制下用动态规划获取控制增益，为了赋予控制器的学习特点，在LQG控制律中附加使下一时刻估计方差最小的学习控制分量.仿真结果表明了算法的有效性.Abstract: A new controller design algorithm with learning characteristic is proposed for the ubiquitous stochastic optimal control problem with unknown parameters. This algorithm estimates system unknown parameters by Kalman filter and obtains control gains by dynamic programming and continuous rolling optimization mechanism. In order to endow the controller with learning characteristics a learning control component which minimizes next moment estimated variance is attached to the LQG control law. Simulation results show the effectiveness of the algorithm.
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Key words:
- Adaptive control /
- uncertainty systems /
- LQG problem /
- Kalman filter
1) 本文责任编委 方海涛 -
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