This article addresses the problem of designing a sensor fault‐tolerant controller for an observation process where a primary, controlled system observes, through a set of measurements, an exogenous system to estimate the state of this system. We consider sensor faults captured by a change in a set of sensor parameters affecting the measurements. Using this parametrization, we present a nonlinear model predictive control (NMPC) scheme to control the observation process and actively detect and estimate possible sensor faults, with adaptive controller reconfiguration to optimize the use of the remaining sensing capabilities. A key feature of the proposed scheme is the design of observability indices for the NMPC stage cost to improve the observability of both the state of the exogenous system and the sensor fault parameters. The effectiveness of the proposed scheme is illustrated through numerical simulations.

中文翻译：

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观测过程中传感器容错的非线性模型预测控制方案

本文解决了为观察过程设计传感器容错控制器的问题，在该过程中，一个主要的受控系统通过一组测量值观察一个外源系统，以估计该系统的状态。我们考虑通过影响测量的一组传感器参数的变化捕获的传感器故障。使用此参数化，我们提出了一种非线性模型预测控制（NMPC）方案来控制观察过程并主动检测和估计可能的传感器故障，并通过自适应控制器重新配置来优化剩余传感功能的使用。该方案的关键特征是为NMPC阶段成本设计可观察性指标，以提高外生系统状态和传感器故障参数的可观察性。