This article presents a comprehensive review of contemporary approaches to the automation and intelligent control of wastewater biological treatment processes. Particular emphasis is placed on the digitalisation of wastewater treatment plants, ranging from the implementation of automated process control systems (APCS/SCADA-based solutions) to the application of predictive algorithms and the development of digital twins of bioreactors. Special attention is devoted to mathematical models that underpin the control of bioprocesses. The evolution of the most widely used activated sludge models—ASM1, ASM2d, and ASM3—is examined, as these models describe key processes such as microbial community growth, nitrification, denitrification, and phosphorus removal. It is shown that modern model parameter identification techniques, including extended and ensemble Kalman filters as well as Bayesian approaches, enable accurate real-time estimation of process characteristics. This, in turn, contributes to more precise and robust process control. A separate focus is placed on intelligent soft sensors that integrate physicochemical models with machine learning algorithms or neural network-based solutions. These sensors are capable of predicting key wastewater quality parameters—such as chemical oxygen demand (COD), ammonium and nitrate concentrations, and suspended solids—and play a crucial role in adaptive control frameworks. Their outputs serve as inputs for more advanced predictive controllers. In addition, the article reviews a range of intelligent control strategies, from auto-tuning PID controllers and Model Predictive Control (MPC) systems to fuzzy and neuro-fuzzy controllers, as well as approaches based on Reinforcement Learning (RL). The latter are increasingly integrated into digital twins of wastewater treatment plants, creating the foundations for fully autonomous control systems. A comparative analysis of the reviewed methods demonstrates that the application of intelligent control can reduce energy consumption for aeration by an average of 15–30%, maintain dissolved oxygen concentrations within ±0.2 mg/L, and enable adaptive adjustment of technological operating regimes without operator intervention. The review covers more than 45 scientific publications from the past decade and clearly illustrates the transition of the sector from isolated solutions towards integrated digital control platforms. Future developments are associated with the creation of hybrid models combining mechanistic principles and artificial intelligence, the implementation of economically oriented MPC systems, the deployment of learning RL agents, and ultimately the development of self-learning control systems for biological treatment processes.
| Mualliflar | М Исмаилов, Boburbek Zokirjon o'g'li Mannobjonov |
|---|---|
| Jurnal | Кимёвий технология. Назорат ва бошқарув |
| Nashr sanasi | 2026-03-03 |
| Jild | 2026 |
| Son | 1 |
| Betlar | 89-98 |
| Til | en |
| DOI | 10.59048/2181-1105.1751 |
DOI: 10.59048/2181-1105.1751 · Maqolaning asl sahifasi
The article proposes a new analytical method for investigating magnetic circuits with distributed parameters and nonlinear magnetic coupling. The method is based on introducing into the system of nonlinear differential…
Important parameters for any type of inverter – a NOT logic gate – are the power consumption during switching and the supply voltage. The proposed connection of complementary (two different types) bipolar transistors…
The work provides an analytical review of the current state of modeling and controlling the carbonization process of ammoniated brine. It analyzes modern methods of mathematical, simulation, and intelligent modeling of…
This article analyzes the use of ultrasonic sensors in measuring water flow and the main errors that may occur in this process. In the conducted scientific research, a time-pulse ultrasonic sensor was tested. The…
This study reports the results of a comprehensive physicochemical investigation of the urea–L-valine binary system, conducted to validate its potential as a modified base for liquid nitrogen fertilizers. By utilizing…
This paper considers an approach to adaptive-robust control of dynamic systems using generalized anticipation, where the object is described by a locally linearized model. Known self-tuning algorithms show insufficient…
A new design of an induction transducer has been developed for measuring linear and torsional vibrations in different directions with high sensitivity by constructing an inertial element consisting of four mutually…
This article provides a comparative analysis of the main methods of vegetable oil refining: alkaline (chemical), physical, and combined. It examines the stages of the technological process and the applicability of each…
This article presents an algorithm for simultaneously estimating the parameters and state coordinates of a multidimensional control object when some of its state variables are not directly measured. The inability to…
The article examines modern approaches to modernizing vegetable oil refining processes from the perspective of increasing energy efficiency, environmental friendliness, and final product quality. Traditional and…