Data-Driven Determination of the Governing Equations of the Continuously Stirred Tank Reactor

This paper presents a data-driven approach for identifying the governing equations or ODEs of a continuously stirred tank reactor (CSTR) system. The paper employs the sparse identification of nonlinear dynamics (SINDy) algorithm, a popular and versatile method used for discovering nonlinear dynamical system models from data. The SINDy-PI (parallel, implicit) framework, a robust variation of the SINDy method, is used to find the implicit dynamics and rational nonlinearities of the CSTR for both Monod and Haldane types of specific growth rates. The simulation results demonstrate the accuracy of the method in inferring the ODEs of the CSTRs using limited and noisy data. The proposed method can be used to improve our understanding of complex systems and inform the design of control strategies.