Daytime/Nighttime Event-Based PI Control for the pH of a Microalgae Raceway Reactor

Influence of pH and dissolved oxygen control strategies on the performance of pilot-scale microalgae raceways using fertilizer or wastewater as the nutrient source

Dissolved oxygen concentration and pH are controllable and cost-effective variables that determine the success of microalgae-related processes. The present study compares different control strategies for pH and dissolved oxygen in pilot-scale microalgae production systems. Two 80 m2 raceway reactors were used, one operated with freshwater plus fertilizer and the other with wastewater as the nutrient source. Both were in semi-continuous mode at a fixed dilution rate of 0.2 day-1. A comparison between the classical On-Off and more advanced pH control strategies, such as PI and Event-based control, was performed, focusing on biomass productivity and the influence of all the process parameters on microalgae growth; "No control" of pH was also assayed. The results show that Event-based control was the best algorithm when using freshwater plus fertilizer. In contrast, no significant differences were observed using the different control strategies when wastewater was the nutrient source. These experiments were performed through selective control strategy, prioritizing pH over dissolved oxygen; however, it was demonstrated that they did not allow to achieve satisfactory dissolved oxygen removal results, especially for the fertilizer system. After modifying the gas diffuser configuration and improving the mass transfer, independent on-off strategies have been developed, permitting effective control of both variables and increasing productivity by up to 20% in both systems. Concluding, a detailed analysis of the energy demand for each strategy implemented in terms of gas consumption and gas flow to biomass ratio is provided.

Special Issue on “Advances in Condition Monitoring, Optimization and Control for Complex Industrial Processes”

Complex industrial automation systems and processes, such as chemical processes, manufacturing systems, wireless network systems, power and energy systems, smart grids and so forth, have greatly contributed to our daily life [...]

Modelado y control de la producción de microalgas en fotobiorreactores industriales

<p>Este artículo presenta una visión general sobre el proceso de producción de microalgas desde un punto de vista de modelado y control de procesos. En primer lugar se exponen las ventajas y el potencial de este tipo de microorganismos, así como los distintos tipos de reactores que se suelen utilizar para su producción. Posteriormente, se analiza el comportamiento dinámico de este tipo de procesos, el cual es muy complejo y cambiante debido a variaciones en las condiciones ambientales tanto diarias como anuales, y se presentan los distintos balances que permiten describir la evolución de las principales variables del sistema. Se exponen distintos tipos de modelos a nivel biológico y a nivel estructural que han sido validados a escala industrial. Tras analizar su comportamiento dinámico, se motivan los distintos problemas de control existentes en este tipo de sistemas y se resume una amplia batería de estrategias de control que han sido evaluadas con éxito en fotobiorreactores industriales. Finalmente, se concluye el trabajo con un balance de los aspectos más importantes expuestos a lo largo del mismo.</p>

Event-based fractional order control

The present study provides a generalization of event-based control to the field of fractional calculus, combining the benefits brought by the two approaches into an industrial-suitable control strategy. During recent years, control applications based on fractional order differintegral operators have gained more popularity due to their proven superior performance when compared to classical, integer order, control strategies. However, the current industrial setting is not yet prepared to fully adapt to complex fractional order control implementations that require hefty computational resources; needing highly-efficient methods with minimum control effort. The solution to this particular problem lies in combining benefits of event-based control such as resource optimization and bandwidth allocation with the superior performance of fractional order control. Theoretical and implementation aspects are developed in order to provide a generalization of event-based control into the fractional calculus field. Different numerical examples validate the proposed methodology, providing a useful tool, especially for industrial applications where the event-based control is most needed. Several event-based fractional order implementation possibilities are explored, the final result being an event-based fractional order control methodology.

Diurnal and nocturnal pH control in microalgae raceway reactors by combining classical and event-based control approaches

The pH control in raceway reactors is crucial for an optimal performance of the system. Classical pH control is exclusively performed during the daytime period for cost saving reasons. This paper demonstrates that pH can be controlled 24 hours a day by using both a continuous-based and an event-based control approach, being able to improve the system's performance and reducing costs at the same time. Thus, experimental tests on a raceway reactor for several days are presented to show a comparison between traditional control algorithms during the daytime period versus an event-based control approach operating during both daytime and night-time periods. As a result, the combination of classical PI control for the daytime period and the event-based control for the night-time period is presented as a promising pH control architecture in raceway reactors.

Decoupling Adaptive Smith Prediction Model of Flatness Closed-Loop Control and Its Application

Flatness control system is characterized by multi-parameters, strong coupling, pure time delay, which complicate the establishment of an accurate mathematical model. Therefore, a control scheme that combines dynamic decoupling, PI (Proportion and Integral) control and adaptive Smith predictive compensation is proposed. To this end, a dynamic matrix is used to decouple the control system. A multivariable coupled pure time-delay system is transformed into several independent generalized single-loop pure time-delay systems. Then, a PI-adaptive Smith predictive controller is constructed for the decoupled generalized single-loop pure time-delay system. Simulations show that the scheme has a simple and feasible structure, and good control performance. When the mathematical model of the control system is inaccurate, the control performance of adaptive Smith control method is evidently better than that of the ordinary Smith control method. The model is successfully applied to the cold rolling production site through LabVIEW, and the control accuracy is within 5I. This study reveals a new solution to the problem of coupled pure time-delay in flatness control system.

Automatic Hybrid Attack Graph (AHAG) Generation for Complex Engineering Systems

Complex Engineering Systems are subject to cyber-attacks due to inherited vulnerabilities in the underlying entities constituting them. System Resiliency is determined by its ability to return to a normal state under attacks. In order to analyze the resiliency under various attacks compromising the system, a new concept of Hybrid Attack Graph (HAG) is introduced. A HAG is a graph that captures the evolution of both logical and real values of system parameters under attack and recovery actions. The HAG is generated automatically and visualized using Java based tools. The results are illustrated through a communication network example.