This paper proposes a new filtering scheme applied to a linearized model of a nonlinear representation for combustion systems, whose parameters are obtained by means of optical sensors. To ensure a robust representation regarding the chosen operation point and external disturbances variations, a linear parameter-varying (LPV) state-space representation is proposed in terms of noise disturbances and time-varying parameters affecting the plant (like the instrumentation noise and non-laminar air flow). Concerning the proposed filtering scheme, a new observer structure, which includes the incorporation of the control signal as an additional input of the filter, is proposed to assure improved stability margins and performance given in terms of the ${\mathcal{H}}_{\infty }$ norm. The filter design method is based on a convex optimization technique and is capable to deal with unstable dynamics. A numerical experiment, whose data were obtained from an actual combustion plant, illustrates the flexibility and advantages of the method when compared with the maximum correntropy criterion based Kalman filter, the full-order filter and the standard Luenberger observer.

本文提出了一种新的滤波方案，应用于燃烧系统非线性表示的线性化模型，其参数通过光学传感器获得。为了确保关于所选操作点和外部干扰变化的稳健表示，根据噪声干扰和影响工厂的时变参数（如仪表噪声和非层流）。关于所提出的滤波方案，提出了一种新的观察器结构，其中包括将控制信号作为滤波器的附加输入，以确保在以下方面提供改进的稳定性裕度和性能。${\mathcal{H}}_{\infty }$ 规范。滤波器设计方法基于凸优化技术，能够处理不稳定的动态。数值实验（其数据来自实际燃烧装置）与基于最大相关熵准则的卡尔曼滤波器、全阶滤波器和标准 Luenberger 观测器相比，说明了该方法的灵活性和优势。