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High-gain extended Kalman filter for continuous-discrete systems with asynchronous measurements

机译:具有异步测量的连续离散系统的高增益扩展卡尔曼滤波器

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This paper investigates an adaptation of the high-gain Kalman filter for nonlinear continuous-discrete system with multirate sampled outputs under an observability normal form. The contribution of this article is twofold. First, we prove the global exponential convergence of this observer through the existence of bounds for the Riccati matrix. Second, we show that, under certain conditions on the sampling procedure, the observer's asynchronous continuous-discrete Riccati equation is stable and also, that its solution is bounded from above and below. An example, inspired by mobile robotics, with three outputs available is given for illustration purposes.
机译:本文研究了在可观察性正常形式下具有多速率采样输出的非线性连续离散系统的高增益卡尔曼滤波器的适应性。 这篇文章的贡献是双重的。 首先,我们通过对Riccati矩阵的存在来证明这个观察者的全球指数融合。 其次,我们表明,在采样过程的某些条件下,观察者的异步连续离散Riccati等式稳定,并且其解决方案是从上方和下方界定的。 灵感来自移动机器人的示例,有三个输出可用可用的例证目的。

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