论文标题
无限马式线性 - 季度高斯控制，具有昂贵的测量
Infinite-Horizon Linear-Quadratic-Gaussian Control with Costly Measurements
论文作者
论文摘要
在本文中，我们考虑了一个无限的地平线线性 - 季度高斯控制问题，具有受控和昂贵的测量。共同设计控制策略和测量策略，以优化控制绩效，执行成本和测量成本之间的权衡。我们通过建立具有控制的LookAhead的动态编程方程来解决共同设计和合作的问题。通过利用动态编程方程式，我们可以通过分析来充分表征最佳控制策略和测量策略。最佳控制是在状态估计中线性的，该估计取决于测量策略。我们证明，最佳测量策略独立于测量状态，并且是周期性的。最佳周期长度取决于测量和系统参数的成本。我们证明了共同设计和合作问题在最佳自触发控制范式中的潜在应用。提供了两个示例，以显示最佳测量策略在减少测量开销的同时保持系统性能的有效性。
In this paper, we consider an infinite horizon Linear-Quadratic-Gaussian control problem with controlled and costly measurements. A control strategy and a measurement strategy are co-designed to optimize the trade-off among control performance, actuating costs, and measurement costs. We address the co-design and co-optimization problem by establishing a dynamic programming equation with controlled lookahead. By leveraging the dynamic programming equation, we fully characterize the optimal control strategy and the measurement strategy analytically. The optimal control is linear in the state estimate that depends on the measurement strategy. We prove that the optimal measurement strategy is independent of the measured state and is periodic. And the optimal period length is determined by the cost of measurements and system parameters. We demonstrate the potential application of the co-design and co-optimization problem in an optimal self-triggered control paradigm. Two examples are provided to show the effectiveness of the optimal measurement strategy in reducing the overhead of measurements while keeping the system performance.
