Many industrial processes are difficult to control because the product quality cannot be measured rapidly and reliably. One solution to this problem is neural network based control, which uses an inferential estimator...
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ISBN:
(纸本)9789898111319
Many industrial processes are difficult to control because the product quality cannot be measured rapidly and reliably. One solution to this problem is neural network based control, which uses an inferential estimator (software sensor) to infer primary process outputs from secondary measurements, and control these outputs. This paper proposes the use of adaptive neural networks applied both to the prediction of product composition from temperature measurements, and to the dual control of distillate and bottom composition for a continuous high purity distillation column. Genetic algorithms are used to automatically choice of the optimum control law based on the neural network model of the plant. The results obtained have shown the proposed method gives better or equal performances over other methods such fuzzy, or adaptive control.
Two-dimensional laser radars (2D-ladars) are sensors extensively used in mobile robotics for map building, self-localization, and obstacle detection due to their accuracy and reliability. Due to their fast sampling of...
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The issues raised in advanced process control applications lead control engineers to be aware of the need of integrating advanced information processing capabilities in the process control loop. In this paper a SIMULI...
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The issues raised in advanced process control applications lead control engineers to be aware of the need of integrating advanced information processing capabilities in the process control loop. In this paper a SIMULINK based tool has been developed for analysis and design of multivariable neural based control systems. This tool has been applied to the control of a high purity distillation column also modeled in SIMULINK including non linear hydrodynamic effects. Also LabVIEW environment has been employed as a graphical user interface for monitoring the neurocontrolled distillation column, by visualizing both the closed loop performance and the user selected control conditions. The proposed control scheme offers an optimal response for both theoretical and practical challenges posed in process control task, in particular when both, the quality improvement of distillation products and the operation efficiency in economical terms are considered.
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