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An enhanced L_2 state estimation for linear parabolic PDE systems with mobile sensors

机译:具有移动传感器的线性抛物线PDE系统的增强L_2状态估计

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摘要

This paper studies an enhanced L2 state estimation problem of distributed parameter processes modeled by a linear parabolic partial differential equation using mobile sensors. The proposed estimation scheme contains a state estimator and the guidance of mobile sensors, where the spatial domain is decomposed into multiple subdomains according to the number of sensors and each sensor is capable of moving within the respective subdomain. The state estimator is desired to make the state estimation error system exponentially stable while providing an L2 performance bound. The mobile sensor guidance is used to enhance the transient performance of the error system. By the Lyapunov direct technique, an integrated design of state estimator and mobile sensor guidance laws is developed in the form of bilinear matrix inequalities (BMIs) to meet the desired design objectives. Moreover, to make the L2 performance bound as small as possible, a suboptimal enhanced L2 state estimation problem is formulated as a BMI optimization one, which can be solved via an iterative linear matrix inequality algorithm. Finally, numerical simulations are given to show the effectiveness of the proposed method.
机译:本文研究了使用移动传感器的线性抛物型偏微分方程建模的分布参数过程的增强L2状态估计问题。所提出的估计方案包含状态估计器和移动传感器的指导,其中根据传感器的数量将空间域分解为多个子域,并且每个传感器都能够在各自的子域内移动。期望状态估计器在提供L2性能限制的同时使状态估计误差系统呈指数稳定。移动传感器指导用于增强错误系统的瞬态性能。通过Lyapunov直接技术,以双线性矩阵不等式(BMI)的形式开发了状态估计器和移动传感器制导律的集成设计,以满足所需的设计目标。此外,为了使L2性能限制尽可能小,将次优的增强L2状态估计问题公式化为BMI优化问题,可以通过迭代线性矩阵不等式算法解决。最后,数值模拟表明了该方法的有效性。

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