The work done here deals with 2 methods for determining Optimal Temperature Control profile for batch Cyrstallization process.
- Deterministic Optimal Control aims at finding the an optimum temperature profile to maximise an objective function selected to achieve a desired volume of the product. Herein, the experimental kinetic parameters are employed to simulate a batch crystalllization process.
- Stochastic Optimal Control undertakes the task of quantifying the uncertainites which creep in due to experimentation. It aims to achive a maximum expected value for the desired product, simultaneously incorporating randomness in the process parameters into the model. Namely, Two methods Ito Process and Polynomial Chaos Expansions are used.
This undertakes the use of Maximum Principle using the Hamiltonian Derivative to move towards the optimum value of Temperature at each time step.
- Ito Processes are used to incorporate the uncertainities which are present in the kinetic parameters. This is used in conjuction with the Hamiltonian method employed above.
- Polynomial Chaos Expansions is a novel technique and has been rarely used in Batch Crystallization which is the main focus here.