Modeling, Analysis, and Intelligent Controller Tuning for a Bioreactor: A Simulation Study

Abstract

In this paper, a novel modeling technique has been attempted to develop the mathematical model for a bioreactor functioning at multiple operating regions. The first principle mathematical equations of the reactor are used with the POLYMATH software to generate essential data for the model development. A relative analysis is also carried out with the existing models in the literature. An optimal PID controller is then designed using a multiobjective particle swarm optimization algorithm. The controller tuning procedure is individually discussed for both the stable and unstable steady state regions. The controller tuned for each region is scheduled using a set-point scheduler to achieve a complete control over the bioreactor. The effectiveness of the proposed scheme has been confirmed through a comparative study with the controller tuning methods proposed in the literature. The results show that, the proposed method provides enhanced performance in effective reference tracking and load disturbance rejection with minimal ISE and IAE. Finally the proposed method is validated on the nonlinear bioreactor model in the presence of a measurement noise. The results testify that the PSO tuned PID performs well in tracking the change in biomass concentration at the entire operating region.

Mathematical model of CO2 release during milk fermentation using natural kefir grains

“…An optimal proportional integral derivative (PID) controller was designed using a multiobjective particle swarm optimization algorithm. The results testify that the particle swarm optimization‐tuned PID performs well in tracking the change in biomass concentration at the entire operating region …”

“…The results testify that the particle swarm optimization-tuned PID performs well in tracking the change in biomass concentration at the entire operating region. 16 The idea of this research was to analyze the CO 2 release dynamics in the case of constant and variable key process parameters (temperature and rotational frequency of the stirrer). A fermentation system is a complex nonlinear dynamical system, the conventional linear control technique may represent the basis for an advanced control system, which the authors are planning to develop in the future.…”

Optimal PID Controller Designing for Uncertain Bioreactor Using BFO Algorithm

“…Figure.1 depicts the diagram of abioreactor [1,2]. [5,6,18]. In this work, a small scale bioreactor widely analysed by the researchers is considered and the corresponding mathematical equations are represented below [3,5];…”

“…Rajinikanth and Latha proposed heuristic algorithms such as Particle Swarm Optimization (PSO) and BFO to tune the PID and modified structured PID controller for a class of unstable systems [8 -17]. A detailed modeling procedure for bioreactor is presented in the paper byRajinikanth and Latha [18]. Roeva and Slavov discussed heuristic algorithm based PID controller design for an industrial type bioreactor [19 -21].…”