Optimal PID controller design based on Particle Swarm Optimization for bacterial growth bioprocess

Particle Swarm Optimization represents a heuristic approach that can be used to solve difficult optimization problems. With some relative few modifications this method can be applied to a specific problem. In this work an optimal PID control algorithm for a bacterial growth bioprocess associated with enzymatic catalysis is designed and analyzed. The controller parameters are calibrated using particle swarm optimization algorithms by the minimization of an objective function. The controller tuning problem is approached as a multi-modal numerical optimization problem. Numerical simulations are included to validate the designed controllers. Two nonlinear kinetic expressions - the Monod and Haldane equations - frequently used to define microbial growth, are tested in the model simulations.