Application of Predictive Feedforward Compensator to Microalgae Production in a Raceway Reactor: A Simulation Study

Andrzej Pawłowski,Francisco Acíen,José Guzmán,Manuel Berenguel,Sebastián Dormido

doi:10.3390/en11010123

Andrzej Pawłowski, Francisco Acíen + Show 3 more

Open Access

https://doi.org/10.3390/en11010123

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Abstract

In this work, the evaluation of a predictive feedforward compensator is provided in order to highlight its most important advantages and drawbacks. The analyzed technique has been applied to microalgae production process in a raceway photobioreactor. The evaluation of the analyzed disturbance rejection schemes were performed through simulation, considering a nonlinear process model, whereas all controllers were designed using linear model approximations resulting in a realistic evaluation scenario. The predictive feedforward disturbance compensator was coupled with two feedback control techniques, PID (Proportional-Integral-Derivative) and MPC (Model Predictive Control) that are widely used in industrial practice. Moreover, the classical feedforward approach has been used for the purpose of comparison. The performance of the tested technique is evaluated with different indexes that include control performance measurements as well as biomass production performance. The application of the analyzed compensator to microalgae production process allows us to improve the average photosynthesis rate about 6% simultaneously reducing the energy usage about 4%.

Highlights

Disturbance compensation is a very important aspect that needs to be considered in control system design for a particular process [1]
We provide a practical evaluation of a predictive disturbance compensation technique introduced in [12] in order to highlight the most important advantages and drawbacks of such a scheme
The predictive feedforward compensator was tested in simulation, where the nonlinear model described in Section 3 was used as virtual plant

Summary

Introduction

Disturbance compensation is a very important aspect that needs to be considered in control system design for a particular process [1] In such a case, the control technique should be able to maintain the controlled variable close to the reference despite the external disturbances that influence the controlled process. In many industrial applications, the control system consists of a feedback controller, since it is able to provide a set point tracking, reduces the influence of plant-model mismatch as well as compensates for process disturbances [1,3] Due to this simple structure, the control system focuses only on one of these issues and provides weak performance for the other problems [4]. This problem has been analyzed by several researchers during the past decades and drives to design more advanced tuning rules for feedforward

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