急需翻译 哪位英语大神帮帮忙啊 不要在线软件翻译的

We study the problem of receding horizon control for stochastic discrete-time systems with bounded control inputs and incomplete state information. Given a suitable choice of causal control policies, we first present a slight extension of the Kalman filter to estimate the state optimally in mean-square sense.We then showhowto augment the underlying optimization problemwith a negative drift-like constraint,yielding a second-order cone programto be solved periodically online.We prove that the receding horizon implementation of the resulting control policies renders the state of the overall system mean-square bounded under mild assumptions. We also discuss how some quantities required by the finite-horizon
optimization problem can be computed off-line, thus reducing the on-line computation.

我们研究关于滚动时域控制的随机离散时,界控制输入和状态信息不完整的问题。一个合适的因果调控政策选择,我们首先提出一个轻微的扩展卡尔曼滤波器的状态最佳估计在均方意义。然后我增加了潜在显示如何的优化问题,如约束负漂移,得到一个二阶锥程序解决定期在线。我们证明了滚动实施的调控政策使得整个系统的状态均在有界的假设条件下。我们还讨论了如何利用有限的基本的一些需要的数据。
优化问题可以离线计算,从而减少了在线计算。
温馨提示:内容为网友见解,仅供参考
无其他回答
相似回答