Sensor based state estimation for: Stirred tank reactors in chemical industry and for PMUs in angle controlled power systems

Abstract

The problem of state estimation has great relevance in the chemical industry, since many chemical processes involve state variables that are difficult to measure online. This paper compares four different state estimation techniques applied to the model of a continuous stirred tank reactor with three state variables. The estimators employed are an extended Luenberger observer, an extended Kalman filter, a nonlinear sliding mode observer, and a nonlinear sliding mode observer with Kalman-filtered feed. The similarity of the models, for the state estimators, could allow applying them, to perform angular control of power systems with phasor measurement unit sensors (PMUs). The Matlab tool has being used to estimate the dynamic response of the estimated variables and the measurement error.