Real-Time Process Optimization

Challenges in real-time process optimization mainly arise from the inability to build and adapt accurate models for complex physico-chemical processes. This paper surveys different ways of using measurements to compensate for model uncertainty in the context of process optimization. A distinction is made between model-adaptation methods that use the measurements to update the parameters of the process model before repeating the optimization, modifier-adaptation methods that adapt constraint and gradient modifiers, and direct-input-adaptation methods that convert the optimization problem into a feedback control problem. This paper argues in favor of modifier-adaptation methods, since it uses a model parameterization, measurements, and an update criterion that are tailored to the tracking of the necessary conditions of optimality. 

Industrial process Solution of rate, diffusional, and hydrodynamic equations in space and time Yields of product Optimal conditions to operate process (e.g., time, concentrations) Real-time process control... 

The materials used in pultrusion are also expected to change with the change in developments on the materials front. Pultrusion machinery has so far evolved in terms of handling complex shapes of very large sizes. The capabilities to optimize product quality and to monitor the process in situ are also available. Further advances are still expected until a truly real-time processing product quality feedback system is achieved. 

Unconstrained Optimization Unconstrained optimization refers to the case where no inequahty constraints are present and all equahty constraints can be eliminated by solving for selected dependent variables followed by substitution for them in the objec tive func tion. Veiy few reahstic problems in process optimization are unconstrained. However, it is desirable to have efficient unconstrained optimization techniques available since these techniques must be applied in real time and iterative calculations cost computer time. The two classes of unconstrained techniques are single-variable optimization and multivariable optimization. 

In the present work it has been shown that on-line coupling of flowthrough fractionation in RCC with ICP-EAS detection enables not only the fast and efficient fractionation of trace elements (TE) in environmental solids to be achieved but allows real-time studies on the leaching process be made. A novel five-step sequential extraction scheme was tested in on-line mode. The optimal conditions for the fractionation were chosen. Investigating elution curves provides important information on the efficiency of the reagents used, the leaching time needed for the separation of each fraction, and the potential mobility of HM forms. 

The complexity and reduced time constants of modern processes imply the adoption of high performance programmable controllers. This requires not only higher processing speed but also more advanced control algorithms that can optimize the process operation in real time. 

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