Auto-Tuning of Identified Highly Sensitive Parameters for ANAMMOX System: Advanced Modeling Approach

Parameter tuning, which includes the parameter estimation of the anaerobic ammonium oxidation (ANAMMOX) process, is challenging owing to the nonlinear and complex nature of the biological structure and microbial symmetry. This article presents an approach to overcome this challenge by identifying highly sensitive parameters by performing sensitivity analysis and parameter auto-tuning under various process conditions. To clarify this, 32% of the parameters were reduced compared to the base case by auto-tuning (the modeling approach). This advanced approach searches an optimum solution under the stringent boundary condition and auto updates the known parametric value with a new optimized one. The model is coded into MATLAB R2018a and incorporated using the extended activated sludge model (Extended ASM1) process equations that are solved using ODE45 solver tools. The obtained outcomes are validated using root mean square error method, where the error gap between the actual and predicted data is minimized.