Adaptive optimal control of a Continuous Stirred Tank Bioreactor

Abstract

The paper presents a finite-memory adaptive-optimal control of a Continuous Stirred Tank Bioreactor (CSTB). In the proposed algorithm, the concentration of the inlet limiting substrate and the dilution rate are chosen such that the operating point evolves towards the optimal steady state which maximizes the CSTB productivity. This optimization process is subject to the constraint that the biomass concentration to be constant at a desired value. The optimal point is obtained making a local approximation of the steady state behaviour by a second degree hyper-surface, whose parameters are estimated with a finite-memory optimal estimator. The plant control in the proximity of each operating point is provided by a linear multivariable law whose parameters are adapted such that the eigenvalues of the closed loop linearized system belong to an invariant spectrum. The behaviour of the proposed algorithm is analysed by numerical simulation.