Self-optimization processes

Supported chemical reagents give opportunities for improving automation, information feedback, and self-optimization processes, especially using design of experiment... 

Modern textile machines have open interfaces, are highly flexible, and are able to adjust their status based on information provided by platforms. Textile semifinished products such as cans, bobbins, or warp beams carry the information for increased production flexibility (smart objects). By using the open interfaces of textile machines, new production planning systems for an integrative, self-optimizing process chain for multiscale and additive manufacturing of textile products can be designed. 

Closed-loop response to process disturbances and step changes in setpoint is simulated with the model of Kiparissides extended to predict the behavior of downstream reactors. Additionally, a self-optimizing control loop is simulated for conversion control of downstream reactors when the first reactor of the train is operating under closed-loop control with dead-time compensation. 

Larsson, T., Hestetun, K., Hovland, E., and Skogestad, S. (2001). Self-optimizing control of a large-scale plant the Tennessee Eastman process. Ind. Eng. Chem. Res., 40(22), 4889M901. 

In this context the supramolecular crystalline [15-22] or hybrid materials [23-35] can be prepared and constitutionally self-sorted by using an irreversible kinetic process like crystallization or sol-gel polymerization. The self-selection is based on constitutional internal interactions of library components, resulting in the dynamic amplification of self-optimized architectures, during the phase change process. With all this in mind, the second part will be devoted to sol-gel resolution of dynamic molecular supramolecular libraries, emphasizing recent developments, especially as pursued in our laboratory. 

This method of selecting catalytic sites significantly depends on spontaneous processes, in contrast to the development of artificial enzymes and catalytic antibodies. The selection process is based on self-assembly, selforganization and self-optimization. Therefore, this selection approach bears the characteristics of supramolecular chemistry. A similar concept is used in natural evolution processes, resulting in the complicated life forms we see around us today. Therefore, it is clear that we can design the self-organizational processes used in supramolecular chemistry to proceed according to the concepts followed by this natural evolutionary process. 

Vlckova et al. demonstrated single-molecule SERS in self-assembled dimers of silver nanoparticles [161]. The self-assembly process was driven by nanoparticle functionalization with a bifunctional molecular linker (4,4 -diaminoazobenzene) which forms a molecular bridge between the particles. Molecules forming the molecular bridge are then precisely positioned within the hot spot with the molecular population being controlled by careful optimization of the linker to... 

Model-based approaches allow fast derivative computation by relying on a process model, yet only approximate derivatives are obtained. In self-optimizing control [12,21], the idea is to use a plant model to select linear combinations of outputs, the tracking of which results in optimal performance, also in the presence of uncertainty in other words, these linear combinations of outputs approximate the process derivatives. Also, a way of calculating the gradient based on the theory of neighbouring extremals has been presented in [13] however, an important limitation of this approach is that it provides only a first-order approximation and that the accuracy of the derivatives depends strongly on the reliability of the plant model. 

Skogestad S. Plantwide control The search for the self-optimizing control structure . J Process Control 10 487-507, 2000. 

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