Last issue
2016 (vol. 26) - Number 4


Andrzej Ruszewski:

Practical and asymptotic stability of fractional discrete-time scalar systems described by a new model



D. Krokavec, A. Filasova, P. Liscinsky:

On fault tolerant control structures incorporating fault estimation



Sundarapandian Vaidyanathan:

Hyperchaos, adaptive control and synchronization of a novel 4-D  hyperchaotic system with two quadratic nonlinearities



H. Górecki, M. Zaczyk:

Analytic solutions of transcendental equations with application to automatics



F. Mnif:

Predictor-based stabilization for chained form systems with input time delay



S. Daniar, R. Aazami, M. Shiroei:

Multivariable predictive control considering time delay for load-frequency control in multi-area power systems



T. Kaczorek:

Analysis and comparison of the stability of discrete-time and continuous-time linear systems



M. Rachik, M. Lhous:

An observer-based control of linear systems with uncertain parameters



L. Malinski:

Identification of stable elementary bilinear time-series model



V.V. Huynh:

New observer-based control design for mismatched uncertain systems with time-delay




ACS Abstract:

1999 (Volume 9)
Number 3/4
1. Problems and practice of pH process modelling and control in stirred tank reactors
2. Substrate consumption rate application for adaptive control of continuous bioreactor - noisy case study
3. Modelling and control of biological anaerobic waste waters treatment processes
4. Model Based Control of Enhanced Biological and Chemical Phosphorus Removal
5. Parameter and State Variable Estimation of Nonlinear Distributed Parameter Bioreactors
6. Mathematical model of sequentially controlled activated sludge processes
7.  Linearising Control via FEM Scheme of a Distributed Parameter Bioreactor


Problems and practice of pH process modelling and control in stirred tank reactors
Pentti Jutila, Heikki Hyötyniemi and Jean-Peter Ylén
(Helsinki University of Technology, Finland)

The control of pH processes in stirred tank reactors includes a wide variety of different types and levels of control tasks. The possible difficulties may arise from the quality of process or reagent liquids, the type and size of the mixing reactor, the accuracy of the instrumentation, the (perhaps time-variant) nonlinearity of the process, and last but not least the difficulties in the measurement of the pH value. In this paper these different aspects are discussed. The applications of pH control have a wide spectrum in different types of engineering problems. In this paper the environmental, chemical, and algorithmic aspects are given the main emphasis, and less attention is paid to the problems of device technology and pH measurement.

keywords: pH process modelling, pH process control, advanced control algorithms, model-based control.

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Substrate consumption rate application for adaptive control of continuous bioreactor - noisy case study
Jacek Czeczot
(Silesian University of Technology, Poland)

This paper deals with the model-based adaptive predictive control of the continuous fermentation process. For this system the theoretical approach to the substrate consumption rate is given and the estimation procedure with application of the recursive least-squares method is proposed. On the basis of this estimated value two nonlinear model-based adaptive predictive controllers for the substrate control are proposed: one with the dilution rate and the other with the inlet substrate concentration as the control quantities. Both estimation procedure and adaptive controllers are derived only on the basis of the simplified form of the mathematical model of the process so there is no necessity to consider the complete form of its nonlinear part. The estimation accuracy and the control performance are demonstrated by means of computer simulation both in the noiseless and noisy cases.

keywords: biotechnology, fermentation process, model-based adaptive control, recursive least-squares estimation.

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Modelling and control of biological anaerobic waste waters treatment processes
Ivan Simeonov
(Bulgarian Academy of Sciences, Bulgaria)

Biological anaerobic wastewater's treatment processes have been an active area of research and have attracted more attention in recent years. This is due to their ecological and energetical utilities. Increasingly important tools towards better understanding, improving process stability and supporting the widespread acceptance of anaerobic wastewater treatment processes became their mathematical modelling and automatic control. This paper is a review of mathematical models and control algorithms for these processes. After a short description of two of the most popular biochemical schemes different models are presented. In this field the attention is mainly focussed on models presented as a sets of non-linear ordinary differential equations. In the field of control after formulating the control problems, different algorithms are reviewed. Particular attention is stressed on the so-called "adaptive linearizing control" that is one of the most promising approaches, based on process models, for control of these processes.

keywords: anaerobic waste water treatment process, mathematical modelling, adaptive linearizing control.

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Model Based Control of Enhanced Biological and Chemical Phosphorus Removal
Dariusz Choiński
(Silesian University of Technology, Poland)

The paper deals with a process control technique for on-line adjustment of biological phosphorus removal ratio and controlling of aluminium salt participation for optimal biological and chemical removing of phosphorus. The paper presents a mathematical model of a real wastewater treatment plant with simultaneous biological removal of nitrogen and phosphorus and chemical participation of phosphorus by addition of salt. The model is based on Activated Sludge Model No. 2 and is calibrated for a real plant. Real-time simulators are used for a computer simulation of the wastewater treatment plant. Chemical participation in removing phosphorus is based on simulated effects of biological phosphorus removal and the Process-Model-Based Control (PMBC). On the basis of this method operational decisions can be evaluated.

keywords: enhanced phosphorus removal, real-time simulation, process model based control, industrial application.

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Parameter and State Variable Estimation of Nonlinear Distributed Parameter Bioreactors
Olfa Boubaker
(Ecole Nationale d'Ingénnieurs de Tunis, Tunisia)
Jean-Pierre Babary
(Centre National de la Recherche Scientifique, France)

Due to a lack of on-line reliable sensors, the measurement of biological variables such as biomass concentration and its specific growth rate, is not possible; this fact can be a difficulty, mainly when considering state feedback control problems. The aim of this paper consists of designing an estimator of biological variables and parameters in the case of a nonlinear distributed parameter bioreactor. By applying an orthogonal collocation method, the distributed parameter model is transformed into a lumped parameter model. Then, a joint estimator of time-varying parameters and state variables is designed by using asymptotic stability properties. Simulation runs show the feasibility and the robustness of the estimator designed for this nonlinear process.

keywords: parameter estimation, nonlinear systems, distributed parameter bioreactors, orthogonal collocation.

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Mathematical model of sequentially controlled activated sludge processes
Mieczysław Metzger
(Silesian University of Technology, Poland)

Reduced order model of the activated sludge process dynamics, presented in the paper, can be treated as a compromise between simplicity (needed for control purposes) and complexity (needed for process behaviour description). Proper calibration of reduced order models is a very difficult task. A new strategy of the model calibration for two different-type sequentially controlled processes (sequentially operated continuous process and sequencing batch reactor) is presented. The proposed method accepts typical values of the model parameters and is based on the fitting of the measured process responses by manipulation of only two model parameters: the initial values of heterotrophic and autotrophic biomass concentrations. Discussion of the response fitting possibilities by changes of XBH and XBA in bio-acceptable limits, as well as validation results for experimental data from two pilot plants, show very promising application of the method.

keywords: activated sludge, biomass fractions, modelling and simulation, model calibration, nitrogen removal, reduced order model, sequencing processes.

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 Linearising Control via FEM Scheme of a Distributed Parameter Bioreactor
Jean-Pierre Babary
(Centre National de la Recherche Scientifique, France)
M.T. Nihtilä, J. Tervo and J.P. Kaipio
(University of Kuopio, Finland)

Control of a distributed parameter bioreactor model is studied via linearisations and numerical approximations. Galerkin's finite element method (FEM) is applied to approximate the original nonlinear partial differential equation (PDE) model by an ordinary differential equation (ODE) system. Then linearising control which tracks a given reference is applied in the ODE system. Controllability of the original PDE system and the approximate ODE model are studied via physical considerations and linearisation pointing out a difference in the controllability properties of the two models. Some simulation results based on the FEM approximation by using realistic model parameter values illustrate feasibility of the joint FEM approximation and linearising control technique.

keywords: parameter estimation, nonlinear systems, distributed parameter bioreactors, orthogonal collocation.

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