More and more nonlinear distributed parameter model described by partial differential equations have been directly adopted in advanced control strategies to improve control performance.However,some model parameter is highly sensitive to the operating condition that regularly changes.A novel characteristics based identification algorithm was proposed for estimating the time-varying parameter for a class of hyperbolic distributed model.Based on the method of characteristics,the partial differential equation (PDE) was transformed into a system of ordinary differential equations (ODEs).According to the analytical expression of the state variable,the model parameter was optimized and updated iteratively based on the latest measurable data sequence.Simulation results showed that the proposed identification algorithm achieved good performance and the time-varying parameters could rapidly converge to its true values.The experimental application on a circulating fluidized bed scrubber achieved an average prediction error within ± 6.5 ％,which provided the basis to implement advanced control strategies with mechanism model described by partial differential equations.
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