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State and Output Estimations for a Class of Nonlinear Dynamic Systems With Highly Cross-Sensitive Output Measurements

While various industries heavily rely on electrochemical sensors for air and liquid quality monitoring and control, many electrochemical sensors are cross-sensitive to one or more interfering gases in addition to the target component, which may cause incorrect readings and lead to improper control measures. In this study, we proposed a direct algebraic approach-based state estimation and output decomposition algorithm which is suitable for state estimation for a class of nonlinear dynamic systems with output measurements that are highly cross-sensitive to multiple interfering gases. Using the cross-sensitive sensor measurement and its successive time derivatives, the proposed methodology can provide a closed-form solution for the actual system state estimation in a systematic way. The established state estimation algorithm was successfully validated in a numeric example. The proposed state estimation and output decomposition algorithm is applicable to a broad class of nonlinear dynamic systems which use sensors that are cross-sensitive to multiple interfering gases in order to improve the performance of the systems.