Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 7 of 7 for “"Chemical process control"”.
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Intelligent Parameter Adaptation for Chemical Processes
Reducing the operating costs of chemical processes is very beneficial in decreasing a company's bottom line numbers. Since chemical processes are usually run in steady-state for long periods of time, saving a few dollars an hour can have significant long term effects. However, the complexity …
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Identification and control of nonlinear processes with static nonlinearities.
Process control has been playing an increasingly important role in many industrial applications as an effective way to improve product quality, process costeffectiveness and safety. Simple linear dynamic models are used extensively in process control practice, but they are limited to the type of …
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A low latency algorithm for the simulation of a binary distillation column using a spreadsheet
Increases in the run speed of readily available computing resources has significantly improved the performance of distillation design and simulation algorithms. Presented here is an algorithm for the simulation of a binary distillation column with a near instantaneous response of the output …
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Hollow fibre liquid phase microextraction of pharmaceuticals in water and Eichhornia crassipes
Submitted in fulfilment of the requirements for the Degree of Master of Applied Sciences in Chemistry, Durban University of Technology, Durban, South Africa, 2019.
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Optimization of nanostructured materials towards gas sensing
… and monitoring. After a period of fast and uncontrolled industrial progress, we are now aware of this danger. Thus we need to monitor the environment and the changes which are happening directly or indirectly because of human presence. During the last decades, solid-state gas sensors have …
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Nonlinear adaptation of established linear and predictive control laws through safe reinforcement learning
… (RL) enables the prospect of data-driven controllers that learn to select control actions optimally purely through the feedback provided by an evaluative signal (the reward). In principle, this technology may be used to develop adaptive controllers that account for plant-model mismatches, …