Evolutionary Strategy for Feeding Trajectory Optimization of Fed-batch Reactors

Safe and optimal operation of complex production processes is one of the mostimportant research and development problems in process engineering. This problem is themost relevant at the design of the optimal feeding profile of fed-batch chemical reactorsdue to the nonlinear and unstable dynamical behavior of the processes. This paper showsthat how the optimal feeding policy can be determined in fed-batch reactors by sequentialquadratic programming, classical evolutionary strategy (ES) and the advanced version ofES that is based on covariance matrix adaptation. A multi-objective function was createdand the search space was constrained in case of all of the three applied algorithms. Theswitching times between states in the feeding trajectory and the feed rates in each statewere manipulated to find the global minima of the objective function. To obtain the optimalfeeding policy the first-principle model of a pilot fed-batch reactor was implemented inMATLAB and applied as a dynamic simulator of the process. Off-line optimization processwas carried out in case of different dosing time distribution. As the results show asignificant improvement can be achieved in process performance applying advanced ESbased optimization algorithms to generate feeding trajectories.