Design of feedback control strategies in a plant-wide wastewater treatment plant for simultaneous evaluation of economics, energy usage, and removal of nutrients

Simultaneous removal of nitrogen and phosphorous is a recommended practice while treating wastewater. In the present study, control strategies based on proportional-integral (PI), model predictive control (MPC), and fuzzy logic are developed and implemented on a plant-wide wastewater treatment plant. Four combinations of control frameworks are developed in order to reduce the operational cost and improve the effluent quality. As a working platform, a Benchmark simulation model (BSM2-P) is used. A default control framework with PI controllers is used to control nitrate and dissolved oxygen (DO) by manipulating the internal recycle and oxygen mass trans-fer coefficient (KLa). Hierarchical control topology is proposed in which a lower-level control framework with PI controllers is implemented to DO in the sixth reactor by regulating the KLa of the fifth, sixth, and seventh reactors, and fuzzy and MPC are used at the supervisory level. This supervisory level considers the ammonia in the last aerobic reactor as a feedback signal to alter the DO set-points. PI-fuzzy showed improved effluent quality by 21.1%, total phosphorus removal rate by 33.3% with an increase of operational cost, and a slight increase in the production rates of greenhouse gases. In all the control design frameworks, a trade-off is observed between operational cost and effluent quality

Dual substrate fermentation using palm oil and glucose for production of eco-friendly biosurfactants using P. aeruginosa NITT 6L

Studies have been conducted to improve biosurfactant (rhamnolipid) production from Pseudomonas aeruginosa NITT 6L in liquid state fermentation utilizing palm oil and glucose as substrates. The pH and minimal salt media (MSM) compositions such as KH2PO4, K2HPO4, NaNO3, MgSO4, NaCl and FeSO4 are optimized using design of experiments. One-factor-at-a-time optimization is employed to evaluate the effects of palm oil and its co-substrate glucose on biosurfactant production. The optimal levels of the aforementioned variables are (g/L) glucose 30.0, KH2PO4 2.0, K2HPO4 5.0, NaNO3 3.5, FeSO4 0.003, MgSO4 0.2, with palm oil concentration of 1.5% (v/v). The fermentation conditions viz. period of fermentation, agitation rate, aeration and concentration of inoculum are optimized by carrying out separate experimentations. The optimum period of fermentation, agitation rate, aeration and concentration of inoculum in the fermentation medium  are found to be 7 days, 150 rpm, 60% and 2% (v/v), respectively, for  maximum rhamnolipid production of about 3.73 g/RE l

Model-based analysis of the effect of temperature in biological wastewater treatment plants for simultaneous removal of organic matter, nitrogen, and phosphorous

448-458The effect of temperature on the phosphorous, nitrogen, and organic matter removal in an activated sludge system(ASS) has been assessed in this research. Benchmark Simulation Model No.1 (BSM1-P) with an ASS (ASM3bioP) is used and the temperature is chosen between 10 to 35°C. The kinetic expressions for the maximum growth rate of heterotrophic biomass, autotrophic, and phosphate accumulating organisms and their decay rates are considered. Total ammonia, nitrogen, and phosphorous in the effluent are analysed and when the range of temperature is less than 15°C and greater than 30°C, the effluent quality deviates from the legal requirements

Design and evaluation of hierarchical control strategies for wastewater treatment plants using Burger-Diehl settler model in BSM1 framework

In this paper, the well-known Benchmark Simulation Model No. 1 (BSM1) was modified with a new model for the secondary clarifier to improve its prediction capability. The Burger-Diehl settler model was integrated with the activated sludge models to represent a complete model of an activated sludge train. Based on this integrated model, twin-level control strategies were developed to enhance the model effluent quality. The secondary controllers at the lower level were proportional integral (PI) and model predictive control (MPC), and the primary controllers at the supervisory level were MPC and fuzzy controllers. The controllers were developed on the identified plant models using prediction-error methodology. Based on these, different controller combination strategies such as PI-Fuzzy, MPC-Fuzzy, PI-MPC, and MPC-MPC were evaluated. Results indicated that the Burger-Diehl settler model achieved better effluent quality than the traditional Takacs settler model due to a significant reduction in effluent violations. In terms of overall performance, the PI-Fuzzy controller combination was able to deliver improved plant performance

A hybrid model for multipoint real time potency observation in continuous direct compression manufacturing operations

The ongoing transition from batch to continuous manufacturing offers both challenges and opportunities in the field of oral solid dosage form production. In turn, Process Analytical Technology (PAT) offers a path towards the successful deployment of continuous tablet manufacturing in rotary tablet presses. One promising PAT tool for this endeavour is the NIR-derived potency measurement. However, the high degree of noise in the data may hamper the extraction of useful information. For this reason, this work focused on the implementation of an adaptive Kalman filter algorithm that incorporates and reconciles the potency prediction given by one or more NIR probes with those of a semi-mechanistic compartmental model developed for the application at hand. This approach allowed for more robust concentration estimations. Furthermore, it was observed that potency levels in multiple locations in the studied tablet press (including those in the finished tablets) could be appropriately inferred using a single in-line measurement data stream. This methodology thus opens the door to advanced process control applications