Data processing: generic control systems or specific application – Specific application – apparatus or process – Chemical process control or monitoring system
Reexamination Certificate
2000-09-26
2004-09-14
Picard, Leo (Department: 2125)
Data processing: generic control systems or specific application
Specific application, apparatus or process
Chemical process control or monitoring system
C435S262000, C075S712000, C700S046000
Reexamination Certificate
active
06792336
ABSTRACT:
BACKGROUND OF THE INVENTION
1. Field of the Invention
The present invention relates to process control where at least some of the controllable parameters are difficult or impossible to characterize or are unknown. More particularly, the present invention relates to process control in biotechnology. Even more particularly, the present invention relates to process control in biotechnology minerals processing. In particular, an application of the present invention relates to a Bioexpert, learning-based controller for bioprocess alteration of minerals for hydrometallurgical processing.
2. Relevant Technology
Traditional process control technology uses mathematical models based on well-defined and well-measured process states. Thereby, allowing the use of mathematical and well-understood control schemes or a series of control schemes, such as PID, Pole Placement, LQR/LTG, H
∞
, ARMA based Adaptive Control, etc., to control the processes.
The biotechnology processing industry differs greatly from the more traditional process control industry. This difference largely stems from the biological uncertainties and complexities of these systems. These uncertainties manifest themselves in a radically more complicated process mechanisms and interactions to the process operator through the process' varying, undefinable and unpredictable nature. To this end, process control engineers in the biotech industry rely upon well-defined environmental process disturbances such as temperature, pH, electrode potential, dissolved oxygen (DO), biomass density, and process flow rates to control the process. The bioprocess engineer acts to restrictively minimize the effects of environmental disturbances upon the process due to the highly complex nature of a biosystem's reaction to these environmental disturbances.
In the mining industry, it is well known that an ore body will have both gradual and radical changes in its composition throughout the ore body. As the ore is mined by the mining engineer, the process engineer must work closely with the mining engineer and the laboratory in characterizing the chemical and physical nature of the ore body. This newly developed characterization must be taken into account when the ore body is processed within the mill in order to continue the maximum production rates. Traditionally, this could involve recalculation of the process control parameters.
Additionally, a process engineer in the mining industry has the problem of transferring experience learned during the processing of one ore body to subsequent ore bodies that are to be processed. This problem is due to the fact that ore bodies are usually highly site specific, i.e. composition specific, such that an entirely different process stream, processing approach, and process control scheme must be taken.
When a process engineer integrates bioprocessing with minerals processing, the complexity of the combination often becomes greater than the sum of its parts. Particularly, a culture of minerals-processing-microorganisms designed for the ore refining/leaching process will respond in complicated and unpredictable ways to well-defined process disturbances such as temperature, pH, flow rate, and the like. It is these very facts that limits the use of mathematical model based control schemes. Added to these complications of the bioprocessing field are the site-specific nature of each ore body and the sometimes radical variations of the chemical and physical qualities of the ore within a single ore body.
Microbial treatment has been proven to be an economically viable approach for the recovery of metals from some low-grade ores. Minerals bioprocessing utilizes mixed cultures of iron- and sulfur-oxidizing acidophilic bacteria that cause the oxidation of mineral structures with the concomitant liberation of metals from the ore. During biological ore oxidation, the microbial population change, the pH of the environment can increase or decrease, temperature generally increases, dissolved O
2
and CO
2
concentrations decrease, and the concentration of metals in the leach liquor generally increases.
Due to the elevated temperatures (50 to 60° C. and higher) that can be achieved during biological heap-leaching operations, moderately thermophilic bacteria are being considered as a way to extend the operating temperature range and improve oxidation efficiency in the heaps. Moderately thermophilic bacteria have been isolated from acidic coal dumps, ore deposits, mining operations, and hot spring environments. They vary in their ability to oxidize iron, sulfur, and pyrite as well as in their ability to grow autotrophically or heterotrophically. Temperature, pH, metal concentration, O
2
, CO
2
, and pulp density are known to affect growth and mineral oxidation by acidophilic bacteria. However, in a minerals processing environment in which any number of physical and chemical parameters are changing, the extent to which these parameters interact and impact iron oxidation by moderately thermophilic bacteria is unknown.
Moreover, minerals bioprocessing comprises very complex systems. The physical, chemical and biological components for minerals bioprocessing are not well characterized. In addition, the physical, chemical and microbial populations that are most favorable for optimum yields are often unknown and are radically different from one mine site to the next. More importantly, the physical and chemical conditions and microbial populations associated with these bioprocesses change with time or, as evident in heap leaching operations, are spatially variable. The changing conditions and microbial populations make it vital that a control system be robust and able to adapt to these changes. These underlining features rule out the use of traditional knowledge-based, neural network, fuzzy logic, and model-based intelligent controllers. Furthermore, traditional process optimization procedures may be inadequate to control highly variable, uncharacterized or unknowable conditions in minerals bioprocessing.
The minerals processing engineer using a bioprocess must stand a round-the-clock watching of all process parameters in an attempt to optimize minerals recovery while providing for the needs of the microorganism culture using his heuristic process knowledge. The minerals processing engineer routinely seeks correlation between input and output in order to simplify processing decisions and to maximize recovery. Many times the possible correlations in a microorganism minerals processing system become too many, too varied, and too complex. This makes the task of tracking any possible correlations between process inputs and goals an accounting nightmare, let alone a nearly unfeasible task. Additionally, because biotechnology processes use microorganisms, the microorganism nursery itself can become the source of a processing problem wherein contamination or inoculation of a culture from other microorganisms can kill, render ineffective, or even cause an optimizing transmutation of the microorganisms that will affect the biotechnology process in question.
What is needed is a method of controlling a process that can deal with the complexity of a bio-minerals process and that adjusts to an uncharacterized and unknown set of environmental changes.
What is also needed in the art is a method of cultivating microorganisms for biotechnology minerals processing that overcomes the problems of the prior art. What is also needed in the art is a method of minerals processing by contacting and maintaining a microbial population within an ore body. Additionally, mixed culture bioprocesses, such as those found in the mining industry, need to be developed and evaluated under conditions that will address more accurately the challenges of involved in this field. Intelligent control technologies need to be designed to handle the complexities inherent when examining multi-parametric effects on growth and metabolism by bacteria or when developing control strategies that are approximate for minerals processing bioprocesses.
SUMMARY AND OBJECTS OF TH
Johnson John A.
Larsen Eric D.
Miller Karen S.
Stoner Daphne L.
Tolle Charles R.
Bechtel BWXT Idaho LLC
Picard Leo
Rao Sheela S.
Trask Britt PC
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