State estimation of output-decoupled complex systems with application to fluid pipeline

Most industrial processes are complex systems, characterized by nonlinearity, high order, and even implicit dynamics. The design of a Luenberger-type observer or an extended Kalman filter for state estimation of such systems presents, in general, considerable difficulties. The authors show that a state estimator can be designed and implemented very easily if the system is output-decoupled, as is often the case in process monitoring and control applications. Simulation study and experiments on an experimental water pipeline show that the proposed estimator works very well. Its estimation accuracy is nearly the same as that of an extended Kalman filter, while its computational expenditure is almost as small as the real-time system model.<
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