This paper concerns a real-world application of an expert system to the automation of a zinc hydrometallurgy plant. The leaching process in zinc hydrometallurgy involves dissolving zinc-bearing material in dilute sulf...
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This paper concerns a real-world application of an expert system to the automation of a zinc hydrometallurgy plant. The leaching process in zinc hydrometallurgy involves dissolving zinc-bearing material in dilute sulfuric acid to form a zinc sulfate solution. The key problems are to determine and track the optimal pHs of the overflows from the neutral and acid leaches, and to ensure the safe running of the process. This paper describes an expert control and fault diagnosis scheme that solves those problems. The expert control is based on a combination of steady-state mathematical models and rule models, and the fault diagnosis employs rule models with certainty factors and a Bayes representation. A real-world application of this scheme showed that it not only improved the control performance, but also correctly diagnosed faults.
This work deals with the developing of Adaptive control on Manifolds algorithms (ACM) designed for the accompanying quality functionals in their general form. Our point here is to apply the ACM approach and to introdu...
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This work deals with the developing of Adaptive control on Manifolds algorithms (ACM) designed for the accompanying quality functionals in their general form. Our point here is to apply the ACM approach and to introduce some practice restrictions for the nonlinear control plants in the case of the quadratic accompanying functionals (QAF). In this article framework we analyze the applicability conditions of designed algorithms and illustrate received results for the problem of adaptive control of combustion engine crankshaft rotation speed.
This paper describes preliminary results regarding the development of a B- splines neural network model of the fuel feed to shaft-speed dynamics of a twin-shaft gas turbine engine. Data recorded from practical testing...
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This paper describes preliminary results regarding the development of a B- splines neural network model of the fuel feed to shaft-speed dynamics of a twin-shaft gas turbine engine. Data recorded from practical testing of the turbine to a multisine input were employed, and models were identified at different points along the turbine operating curve. B-splines neural networks have been found to be good models of the system, delivering good results especially for long-range predictions.
ILM-RIVER is a universal tool for the task of the simulation and the control of rivers and cascades of hydropower plants. The tool consists of two libraries. One for modeling rivers and reservoirs, a second for the co...
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Voting algorithms have been widely used in the realisation of fault-tolerant systems. We introduce a new algorithm of software voting termed as adaptive majority voter. It uses the history of modules of a N-Modular Re...
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This paper presents theory, algorithms and validation results for system identification of continuous-time state-space models from finite input-output sequences. The algorithms developed are methods of subspace model ...
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Voting algorithms have been widely used in the realisation of fault-tolerant systems. We introduce a new algorithm of software voting termed as adaptive majority voter. It uses the history of modules of a N-Modular Re...
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Voting algorithms have been widely used in the realisation of fault-tolerant systems. We introduce a new algorithm of software voting termed as adaptive majority voter. It uses the history of modules of a N-Modular Redundant (NMR) system to select the result of the most reliable module if it contributes toward a majority consensus. Furthermore, a new method for on-line creation of a history record of modules in a Triple Modular Redundant, TMR, system is proposed. The history vector of modules are not only used to improve the behaviour of a wide range of traditional voters, but also can be used to identify the most erroneous/faulty modules of a system to take appropriate reconfiguration or damage preventive strategies. The empirical results show that the novel 'adaptive majority voter' has higher safety and availability levels than the traditional majority voter.
To cope with the growing demands for simulation models of ever increasing complex industrial systems, the research community effort has been mainly focused on creating different software tools which simplify the model...
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To cope with the growing demands for simulation models of ever increasing complex industrial systems, the research community effort has been mainly focused on creating different software tools which simplify the modelling task. There is a recognised necessity of modelling tools supporting libraries of non-causal models which could be coupled in the same way as physical units are assembled in a system. This work presents an object-oriented modelling language, PML, designed to support a modelling methodology where system models are described by linking system component models analogously as the system components are linked. This modelling language introduces a new modularization of physical knowledge, making a clear separation between the physical behaviour representation (declarative knowledge) and the computational aspects of model simulation (procedural knowledge).
The final step in zinc hydrometallurgy is the electrolytic process. The most important parameters to control the the concentrations of zinc and sulfuric acid in the electrolyte. This paper proposes an expert control s...
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The final step in zinc hydrometallurgy is the electrolytic process. The most important parameters to control the the concentrations of zinc and sulfuric acid in the electrolyte. This paper proposes an expert control strategy for determining and tracking the optimal concentrations, which uses neural networks, rule models and a single-loop control scheme. First, the process is described and the strategy that features an expert controller and three single-loop controllers is explained. Next, neural networks and rule models are constructed based on statistical data and empirical knowledge on the process. Then, the expert controller for determining the optimal concentrations is designed through a combination of the neural networks and rule models. The three single-loop controllers use the PI algorithm to track the optimal concentrations. Finally, the results of actual runs using the strategy are presented. They show that the strategy provides not only high-purity metallic zinc, but also significant economic benefits.
ILM-RIVER is a universal tool for the task of the simulation and the control of rivers and cascades of hydropower plants. The tool consists of two libraries. One for modeling rivers and reservoirs, a second for the co...
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ILM-RIVER is a universal tool for the task of the simulation and the control of rivers and cascades of hydropower plants. The tool consists of two libraries. One for modeling rivers and reservoirs, a second for the control of individual hydropower plants or cascades of hydropower plants. The libraries contain modules which can be associated with each other. The parameter estimation of the modules is left to the user.
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