In this paper, we present the implementation of the Benchmark Simulation Model No.1 (BSM1) on a Speedgoat Performance real-time target machine, with the aim of enabling hardware-in-the-loop (HIL) testing of advanced control strategies for wastewater treatment plants (WWTPs). Our main contribution lies in adapting the BSM1 Simulink model for execution in real-time environments. We focus on the dissolved oxygen (DO) control loop and integrate an artificial neural network (ANN)-based controller previously proposed by the authors. The required adjustments include resolving algebraic loops, handling fixed-step time constraints, and enabling real-time signal visualization through interpolation. Preliminary results confirm that the adapted BSM1 model runs reliably on the Speedgoat platform, preserving the dynamics of the original simulation and enabling future real-time control experimentation.

The decoupled control strategy is a well-established methodology in process control applications. This work-inprogress (WIP) manuscript introduces the decoupled internal model control-proportional derivative (IMC-PD) dual-loop scheme for inverse response process with dead time. The PD controller is constituted on Routh-stability guidelines with the help of Pade’s approximation method. The servo or the primary controller is designed on the IMC principle with a solitary tunable parameter. The equilibrium optimizer (EO) finally obtains the equilibrium locale (optimal controller settings) with the objective of minimizing integral square error. The suggested scheme is tested on a boiler steam level control system through simulations. It delivers appreciable enhancement in performance measures pertaining to transient and steady-state dynamics when compared with prevalent strategies.

Microalgae are attractive in wastewater treatment applications due to their capacity of growing on inorganic nutrients (e.g., nitrogen and phosphorus salts) while their biomass is used to produce biodiesel, biogas or even bioethanol. The photosynthetic growth is the most attractive mechanism, but it brings additional limitation to the open ponds or the Photobioreactors (PBRs) in which they grow. The light is thus the main factor that drives the growth of microalgae and, with the development of commercial efficient LED light sources, the indoor cultures can become more efficient. The use of artificial light creates a new class of controllers, the lumostas, by which the incident light intensity is manipulated. In this paper, an alternative proposal based on PID control acting on Biomass algae desired profile is proposed. It is seen that the generated manipulated incident light generates optimal profiles for he biomass yield on light ratio. Also, better, more efficient batches that the ones based on model prediction over all the batch are obtained. This is a preliminary result that is to be extended with biomass observers. Also, in future work, the tuning of the PID controller in a more automated way will be addressed.

This study addresses the effect of climate conditions on treatment effectiveness and energy consumption in a conventional Wastewater Treatment Plant (WWTP). It has been observed that winter temperatures below 12°C produce a deterioration of pollutants elimination and energy efficiency in the activated sludge process (ASP). Then, in this work, variations of climatological conditions are considered, and ASP control parameters are modified, to evaluate their effect into the eco-efficiency of the WWTP operation. The eco-efficiency of the operation is analyzed from a plant-wide perspective considering the effects on different units of the plant. The Benchmark Simulation Model 2 (BSM2), that represents a typical WWTP, is selected for simulations. Introduction of seasonal temperature effects on ASP control strategy are contemplated for future work.

In this paper ten control strategies are tested, starting from a default tuning of the controllers, to evaluate its results in terms of general plant performance indicators such as the effluent quality index (EQI) and the operating cost index (OCI). Using the Benchmark simulation No 1 (BSM1), many simulations are done to determine the most sensitive parameter of the proportional-integral (PI) controllers implemented. The most sensitive parameter is selected by evaluating the influence of the proportional gain (Kp) and the integral time (T) in the general performance of the plant when they are changed into the proposed ranges. From the simulation study, Ti is selected as the most sensitive parameter. A comparison between the results in terms of EQI vs OCI graphics, varying Kpand Ti and the results varying only Ti, shows similar behaviours on the plant performance for all strategies.