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The biological treatment of industrial waste is a priority theme for the sustainable development of any society. In recent years, there has been a significant increase in the study of the efficiency and reduction of the energy costs of this process, as active sludge treatment plants are characterized by a high cost of aeration. This study aims at modeling an active sludge treatment plant based on...
Most of the chemical processes are multivariable in nature. Control of multivariable industrial processes becomes a challenge due to the inherent interactions among variables, modelling uncertainty and various disturbances. The objective of this paper is to design a PI controller for CSTR process with decoupler to meet the desired transient response specifications. Stability of the proposed system...
A dynamic real-time optimization (D-RTO) methodology has been developed and applied to a batch reactor where polymer grafting reactions take place. The objective is to determine the on-line reactor temperature profile that minimizes the batch time while meeting terminal constraints on the overall conversion rate and grafting efficiency. The methodology combines a constrained dynamic optimization method...
This paper presents the design of a Dynamic Matrix of Control “DMC” to control exothermic processes, multi-stages type, in batch reactors in order to enhance the production quality. To reach these aims, a set of mathematics models based on the Volterra Series and Laguerre functions are introduced. The obtained results suggest that these systems identified based on mathematical criteria together with...
The control of fed-batch bioprocess is a current challenge. Mathematical models are highly rigid systems of nonlinear differential equations with strict physical limitations. In this paper a simple and efficient technique for tracking optimal profiles with minimal error is developed. It is based on linear algebra for the calculation of control actions, by solving a system of linear equations. The...
In the article the methods of solution quality evaluation in context of optimal control were presented and discussed. The quality of the solution plays a key role in control of nonlinear processes with descriptor constraints. The multiple shooting method enables us to transform the optimal control problem into a nonlinear optimization task. Therefore, the well adjusted quality evaluation function...
In recent years, soft sensors have been established as a valuable alternative to the traditional hardware sensors for the acquisition of critical information regarding "difficult-to-measure" process variables and/or parameters in chemical process monitoring and control. Soft-sensors can also be modified as a novel process identification tool for process monitoring and model based control...
In the present work, an adaptive Artificial Neural Network (ANN) model based Generic Model Control (GMC) [ANNGMC] scheme is proposed for nonlinear processes. The proposed scheme consists of online parameter estimation of a purely data driven ANN model based on past measurements using Extended Kalman Filter, and control computation based on minimizing the deviation of predicted model output derivative...
This paper presents an application of self-tuning Fuzzy PI controller (STFPIC) in velocity form (VF) and position form (PF) to control the jacketed Continuous Stirred Tank Reactor (CSTR) in a cascade configuration. CSTR is a highly non-linear process and requires non-conventional intelligent control techniques for stable and efficient operations. Self-tuning fuzzy logic controllers are one such option,...
Predictive control is one of the most spread advanced control algorithms in industrial application field. Extended Prediction Self-Adaptive Control (EPSAC) is a part of this family of algorithms and is suitable for wastewater treatment plants control. The main goal of those industrial processes is to fulfil effluent water quality legal provisions with minimal energy consumption. In order to achieve...
In this paper, we propose to control the quantity and quality of the produced biogas from the anaerobic digestion of organic matter, digested in either a continuous stirred tank reactor or a fixed bed digester. This is motivated by the aim of providing the power grid with a stable amount of energy despite fluctuations in the treated waste concentration and composition. Therefore, we apply the linearizing...
In the paper several approaches to building the real-time basic principle simulators of nuclear reactor processes are presented and their characteristics are analyzed. The characteristics of developed simulators for MATLAB/Simulink including their limitations, and the idea of a cross-platform simulator independent of specific hardware or software are presented. Mathematical models of selected nuclear...
The paper presents a comparison of tuning procedures for a multi-region fuzzy-logic controller used for nonlinear process control. This controller is composed of local PID controllers and fuzzy-logic mechanism that aggregates local control signals. Three off-line tuning procedures are presented. The first one focuses on separate tuning of local PID controllers gains in the case when the parameters...
This paper presents results obtained by simulations of the exothermic semi-batch chemical reactor. The task was to suite chemical reactor dimensions to a specific process in such way, so that the process could run most effectively. An objective function which included also the reactor mathematical model was defined. The objective function was than modified to find even better results and necessary...
In this paper we consider the control of the methane flow rate in biogas production using a continuous stirred tank reactor or a fixed bed digester. The goal is to regulate the methane flow rate in order to match an energy demand in spite of variations in the waste concentrations. For this purpose, a two step (acidogenesis-methanogenesis) nonlinear mass balance model is considered. Due to the costs...
The accelerated advancement of Process Control Systems (PCS) transformed the traditional and completely isolated systems view into a networked inter-connected “system of systems” perspective, where off-the-shelf Information and Communication Technologies (ICT) are deeply embedded into the heart of PCS. This has brought significant economical and operational benefits, but it also provided new opportunities...
This paper is the second in a series of two dealing with the spatial optimization of the heat exchanger temperature profiles of exothermic tubular reactors under the assumption of steady-state and plug flow characteristics. The minimum principle of Pontryagin (optimal control theory) is applied in a straightforward, analytical sense. To enable a trade-off between process performance and global heat...
This series of two papers deals with the spatial optimization of the heat exchanger temperature profile of an exothermic tubular reactor under the assumption of steady state and plug flow characteristics. The minimum principle of Pontryagin (optimal control theory) is applied in a straightforward, analytical sense. To enable a trade-off between process performance and heat loss a combined cost criterion...
Highly nonlinear and open-loop unstable processes pose serious difficulties to the implementation of optimal control solutions, such as Model Predictive Control (MPC). An example of such processes is the Tennessee Eastman model. Here we show that by proper combination of the optimization algorithm with additional intermediate layers of control, most of the ill-conditioning can be avoided, without...
An adaptive iterative learning control based on unfalsified strategy is proposed to solve high precision temperature tracking of the Chylla-Haase reactor, in which iterative learning is the main control method and the unfalsified strategy is adapted to adjust the learning rate adaptively. It is encouraged that the unfalsified control strategy is extended from time domain to iterative domain, and the...
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