Developing Control Strategies

Controls are those measures which are put in place to reduce risk arguably the most important elements of a hazard register. Although the structure of hazard registers vary, the objective should be to systematically mitigate each cause of the identified hazards. Some degree of traceability needs to be defined between the causes and controls to demonstrate completeness of this exercise. This assists in clearly establishing those causes for which controls do not exist. 

In many projects the conttols of most significance are those which traverse organisational boundaries. In other words where one party (often the software manufacturer) establishes that to mitigate the risk to acceptable levels another party (often the healthcare organisation) is reqnired to put in place certain measures. These external controls provide an ideal starling point for downstream stakeholders to begin to build their assurance strategy on top of the safety work done by the manufacturer. 

To this end, a classification system for controls and their relative effectiveness can be useful. 

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Emission inventories are often used to develop control strategies for particulate pollution, but there are difficulties... 

Developing control strategies for ozone is very different than for relatively unreactive species such as CO. In the latter case, the concentrations in air are a direct result of the emissions, and all things being equal, a reduction in emissions is expected to bring about an approximately proportional reduction in concentrations in ambient air. However, because O, is formed by chemical reactions in air, it does not necessarily respond in a proportional manner to reductions in the precursor emissions. Indeed, as we shall see, one can predict, using urban airshed or simple box models, that under some conditions, ozone levels at a particular... 

The kinetic modeling nomenclature arises from the incorporation of chemical kinetic submodels in EKMA. The empirical term comes from the use of observed 03 peaks in combination with the model-predicted ozone isopleths to develop control strategy options. Thus, the approach historically was to use the model to develop a series of ozone isopleths using conditions specific for that area. The second highest hourly observed 03 concentration and the measured... 

Models currently in use for developing control strategy options are grid-based, or Eulerian, models, the... 

Sorensen and Skogestad (1994) developed control strategies for BREAD processes by repetitive simulation strategy using a simple model in SPEEDUP package. Wilson and Martinez (1997) developed EKF (Extended Kalman Filter) based composition estimator to control BREAD processes. The estimator was found to be quite robust and was able to estimate composition within acceptable accuracy, even in the face of process/model mismatches. Balasubramhanya and Doyle III... 

The remainder of this manuscript will deal with the identification of linear empirical models and their use in developing control strategies. 

From an operational and regulatory perspective, the challenge is to develop control strategies which are effective in the field, but which are also practical to implement. For example, from a knowledge of the fundamental chemical and physical mechanisms of PCDD/F formation and their relationships to the prevailing physical and chemical conditions, it is possible to identify through laboratory experiments key operational parameters or surrogate emissions... 

In terms of developing control strategies relating to the control of PCDD/F formation and emissions, the above goals can be discussed under four headings ... 

Unsteady-state or dynamic simulation accounts for process transients, from an initial state to a final state. Dynamic models for complex chemical processes typically consist of large systems of ordinary differential equations and algebraic equations. Therefore, dynamic process simulation is computationally intensive. Dynamic simulators typically contain three units (i) thermodynamic and physical properties packages, (ii) unit operation models, (hi) numerical solvers. Dynamic simulation is used for batch process design and development, control strategy development, control system check-out, the optimization of plant operations, process reliability/availability/safety studies, process improvement, process start-up and shutdown. There are countless dynamic process simulators available on the market. One of them has the commercial name Hysis [2.3]. 

The present research deals with the control of an industrial gas-turbine spray combustor with multiple swirlers and distributed fuel injection for rapid mixing and stabilization [1]. The research focuses on investigating the mixing patterns and flame structure in a multiple-swirl stabilized combustor and develops control strategies for improved performance [2]. It is performed in collaboration with Delavan Gas Turbine Products, a division of Goodrich Aerospace. The research... 

Develop control strategies on 10 kWe fully automated fuel cell power system (FCPS) and deliver to ANL. 

Control structure 2 overcomes these problems. No reactor composition measurement is used, and throughput is directly fixed by flow-controlling the fresh feed Fqa. This control scheme is intuitively appealing and is often proposed in developing control strategies for this type of process. Unfortunately, as we demonstrated in the previous section, it does not work. 

Especially in an operating environment where quality has become more important than quantity, there is a strong desire to develop input-output models that can be used in advanced control applications, in order to develop control strategies for quality improvement. These models are usually discrete hnear transfer function (difference equation) type models, which provide a representation of the dynamic behaviour of the process at discrete sampling... 

The reactivity of hydrocarbons in the smog formation process is an important consideration in understanding the process and in developing control strategies. It is useful to know which are the most reactive hydrocarbons so that their release can be minimized. Less-reactive hydrocarbons, of which propane is a good example, may cause smog formation far downwind from the point of release. 

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