The objective of this paper is to apply a closed-loop identification to actual dissolved oxygen control system in the coke wastewater treatment plant. It approximates the dissolved oxygen dynamics to a high order mode...
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The objective of this paper is to apply a closed-loop identification to actual dissolved oxygen control system in the coke wastewater treatment plant. It approximates the dissolved oxygen dynamics to a high order model using the integral transform method and reduces it to the first-order plus time delay (FOPTD) or second-order plus time delay (SOPTD) for the PID controller tuning. To experiment the process identification on the real plant, a simple set-point change of the speed of surface aerator under the closed-loop control without any mode change was used as an activation signal of the identification. The full-scale experimental results show a good identification performance and a good tracking ability for set-point change. As a result of improved control performance, the fluctuation of dissolved oxygen concentration variation has been decreased and the electric power saving has been accomplished.
A conditional fuzzy c-means (CFCM)-based fuzzy adaptive neuro-fuzzy system (ANFS) by on-line learning is proposed in this paper. In the structure identification, the optimal or near optimal number of fuzzy rules is de...
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ISBN:
(纸本)0780370902
A conditional fuzzy c-means (CFCM)-based fuzzy adaptive neuro-fuzzy system (ANFS) by on-line learning is proposed in this paper. In the structure identification, the optimal or near optimal number of fuzzy rules is determined by a CFCM clustering with TSK-type fuzzy rules based on the criterion. In the parameter identification. The consequent parameters are tuned by least squares estimator (LSE) and the premise parameters are tuned by back-propagation algorithm in off-line learning. Then on-line learning by recursive least squares estimator (RLSE) and back-propagation algorithm is used to cope with time varying plant dynamics. Finally, we show its capability for a CFCM-based on-line ANFS to control the temperature of a water path.
An incremental cause-effect type of dynamical model is proposed for use in a predictive control scheme. The model parameters comprise of a scaling factor, a memory length and the shape of a specially introduced member...
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An incremental cause-effect type of dynamical model is proposed for use in a predictive control scheme. The model parameters comprise of a scaling factor, a memory length and the shape of a specially introduced membership function. This function represents the normalized degrees of the cause-effect relationships between the past time changes of the control input and the current change of the plant output. The model of the plant dynamics can be identified from the experimental data by the least mean squares (LMS) algorithm. A special algorithm for reduced size identification that uses tuning of a 1D Takagi-Sugeno fuzzy model by the LMS algorithm is shown. An improved version of the predictive control scheme is also introduced that leads to a reduction of the prediction errors caused by the inaccuracy of the plant model. Finally, numerical simulations are shown to illustrate the performance of proposed control algorithm that lead to a conclusion for applicability of the method.
This paper presents an overview of the recent advances in deterministic global optimization approaches and their applications in the areas of process Design and control. The focus is on global optimization methods for...
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This paper presents an overview of the recent advances in deterministic global optimization approaches and their applications in the areas of process Design and control. The focus is on global optimization methods for (a) twice-differentiable constrained nonlinear optimization problems, Cb) mi?;ed-integer nonlinear optimization problems, and (c) locating all solutions of nonlinear systems of equations. Theoretical advances and computational studies on process design, batch design under uncertainty, phase equilibrium, location of azeotropes, stability margin, process synthesis, and parameter estimation problems are discussed. (C) 2000 IFAC. Published by Elsevier Science Ltd. All rights reserved.
A general, rigorous dynamic model is described for studying the interactions of design and control in a double-effect distillation system. Two approaches are adopted. In the first, the steady-state process design and ...
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A general, rigorous dynamic model is described for studying the interactions of design and control in a double-effect distillation system. Two approaches are adopted. In the first, the steady-state process design and the control system are optimized sequentially;potential operability bottlenecks are identified and the economic advantage of double-effect systems over conventional single column systems is demonstrated. In the second approach, the process design and the control system are optimized simultaneously leading to a more economically beneficial system than that obtained using the sequential approach. (C) 2000 IFAC. Published by Elsevier Science Ltd. All rights reserved.
Dynamic simulation of complex industrial systems is discussed, and a summary is presented of over a decade of work in the modelling, simulation and control of cryogenic separation and liquefaction processes. The work ...
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Dynamic simulation of complex industrial systems is discussed, and a summary is presented of over a decade of work in the modelling, simulation and control of cryogenic separation and liquefaction processes. The work includes not only successful applications but also the development of tools to facilitate the construction of the simulation flowsheets and their effective use in control system analysis and design. The use of these tools and of two commercial dynamic simulation packages is reviewed. The question of what is a required level of modelling detail in dynamic simulation applications is addressed. (C) 2000 IFAC. Published by Elsevier Science Ltd. All rights reserved.
In this paper, the extension to tubular reactors of asymptotic observers originally developed for STR is first discussed and illustrated with real-life data on an non-isothermal fixed bed reactor. Then it will be show...
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In this paper, the extension to tubular reactors of asymptotic observers originally developed for STR is first discussed and illustrated with real-life data on an non-isothermal fixed bed reactor. Then it will be shown how to design exponential observers, which are also independent of the process kinetics but for which the rate of convergence may be arbitrarily fixed (unlike the asymptotic observers for which the rate of convergence depends on the operating conditions). (C) 2000 IFAC. Published by Elsevier Science Ltd. All rights reserved.
In this paper we consider a bilinear matrix inequality (BMI) based method, which provides an ellipsoidal estimate of the region of attraction, for nonlinear constrained robust stabilization. Robustness against model u...
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In this paper we consider a bilinear matrix inequality (BMI) based method, which provides an ellipsoidal estimate of the region of attraction, for nonlinear constrained robust stabilization. Robustness against model uncertainty is handled. The method is based on an uncertain multi-model representation of the plant parameterized by affine local models and their respective supports in the state space. and an associated piecewise affine state-feedback: structure. We show that the method is applicable to uncertain constrained systems that are partially uncontrollable and open-loop unstable. (C) 2000 IFAC. Published by Elsevier Science Ltd. All rights reserved.
For the polymer production industries, the competitive edge will come from the technology that excels in controlling the polymer properties in a consistent way over the entire plant and in maximizing the production pe...
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For the polymer production industries, the competitive edge will come from the technology that excels in controlling the polymer properties in a consistent way over the entire plant and in maximizing the production performance while keeping safety regulations. Based on the experience in applying advanced processcontrol and scheduling schemes to industrial polyolefin polymerization plants, the state of the art in quality controlsystems for providing the polymer production plant with an enlarged capacity for product discrimination and flexibility is reviewed. On-line soft-sensing and optimal grade changeover control problems are the main focus of this paper. A quality control system for polymer production plants, which integrates optimal control with on-line sensing and scheduling techniques, is discussed making reference to an application of a prototype system to an industrial plant. (C) 2000 IFAC. Published by Elsevier Science Ltd. All rights reserved.
Multi-scale models of processing systems offer an attractive alternative to models defined in the time- or frequency-domain. They are defined on dyadic or higher-order trees, whose nodes are used to index the values o...
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Multi-scale models of processing systems offer an attractive alternative to models defined in the time- or frequency-domain. They are defined on dyadic or higher-order trees, whose nodes are used to index the values of any variable, localised in both time and scale (range of frequencies). This dual localisation is particularly attractive in solving estimation and control problems, in this paper, multiscale models are used to design model-predictive controllers (MPC), resulting in design techniques with several important advantages, such as;(a) natural depiction of performance characteristics and treatment of output constraints. (b) fast algorithms for establishing the constrained control policies over long prediction/control horizons, (c) rich depiction of feedback errors at several scales, and (d) optimal fusion of multi-rate measurements and control actions. (C) 2000 IFAC. Published by Elsevier Science Ltd. All rights reserved.
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