Stochastic modeling of a non isothermal chemical reactor

What is it about?

Industrial chemical process systems operate subjected to persistent fluctuations, which are due to variations around mean values of actuators, measurements, and high-frequency parasitic dynamics. Since the fluctuation frequencies are faster than the deterministic dynamics, they can be modeled as an exogenous stochastic noise input for the deterministic system. Depending on the system and its operating condition, the stochastic and deterministic modeling approaches can yield similar or considerably different results.

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Why is it important?

The proposed stochastic modeling approach is a point of departure to tractably address problems of chemical processes with complex deterministic nonlinear dynamics, among them are: (i) systems with multiplicative (structured) noise, that can create or destroy PDF extrema, (i) safe process design, (ii) global-nonlinear stochastic PDF (Kushner) observers, (iii) the development of the FP-based version of the local MC-based fault detection approach, (iv) global state-control PDF pair-based functioning assessment of conventional linear PID controllers, (v) HJI PDE-based nonlinear optimal controllers with complete state-control PDF pair description trough a combined FP-HJI PDE approach, (vi) stochastic economic model predictive control, and (vii) energy (or Lyapunov) function construction for dynamics (or control) analysis (or design), as a complementary alternative to the thermodynamic approach.