Self adaptation

In addition to their role in composites, high performance fibers are also found in coated and laminated textile products, three-dimensional fabric stmctures, multifunctional property improvement, and intelligent or self-adaptive materials. 

The subject of adaptive control is one of current interest. New algorithms are presently under development, but these need to be field-tested before industrial acceptance can be expected. It is clear, however, that digital computers will be required for implementation of self-adaptive controllers due to their complexity. An adaptive controller is inherently nonlinear and therefore more complicated than the conventional PID controller. 

Design of self-adapting N-heteroaromatic-substituted claw ligands as E /M" " (E = p-block element, M = main group metal)chargedspacers 97CB1365. 

Optimization sequence (experimental data, arbitrary units) Runs 1 and 2 are initial experiments. From run 3 to run 6 the amounts of A, B, G, and feed rate of G are fixed. These constraints are relaxed for runs 7 and 8. (Reprinted from Marchal-Brassely et al. (1992), Optimal operation of a semi-batch reactor by self-adaptive models for temperature and feed profiles . Copyright (1992), with permission from Elsevier Science). 

The above example illustrates the self adaptive capacity of the Kalman filter. The large interferences introduced at the wavelengths 26 and 28 10 cm have not really influenced the end result. At wavelengths 26 and 28 10 cm , the innovation is large due to the interfered. At 30 10 cm the innovation is high because the concentration estimates obtained in the foregoing step are poor. However, the observation at 30 10 cm is unaffected by which the concentration estimates are restored within the true value. In contrast, the OLS estimates obtained for the above example are inaccurate (j , = 0.148 and JCj = 0.217) demonstrating the sensitivity of OLS for model errors. 

Wehrens R, Lucasius C, Buydens LMC, Kateman G (1993a) HIPS, a hybrid self-adapting expert system for NMR spectrum interpretation using genetic algorithms. Anal Chim Acta 277 313... 

The growing cell structure algorithm is a variant of a Kohonen network, so the GCS displays several similarities with the SOM. The most distinctive feature of the GCS is that the topology is self-adaptive, adjusting as the algorithm learns about classes in the data. So, unlike the SOM, in which the layout of nodes is regular and predefined, the GCS is not constrained in advance to a particular size of network or a certain lattice geometry. 

The interface may be self-adaptive, noting the identity of the user each time they log in to use the system and tracking the interactions that follow, learning about the level of expertise of the user, and building up a personal profile of them so that the approach of the ES can be tailored to them individually. This is sometimes apparent in the Help system on a PC, which is usually based around a type of ES. Since the level of knowledge, experience, and confidence among PC users varies widely, if a Help system is to be of the greatest value, it is wise to construct it so that it can adjust its approach and presentation to match the level of expertise of the user. 

Therefore, a key goal for future research is to establish a clear methodology by which self-adapting computational organisms can adapt, both shortterm and long-term, in order to enhance their survivability, in a changing competitive world. 

The combined features of structural adaptation in a specific hybrid nanospace and of a dynamic supramolecular selection process make the dynamic-site membranes, presented in the third part, of general interest for the development of a specific approach toward nanomembranes of increasing structural selectivity. From the conceptual point of view these membranes express a synergistic adaptative behavior the addition of the most suitable alkali ion drives a constitutional evolution of the membrane toward the selection and amplification of a specific transport crown-ether superstructure in the presence of the solute that promoted its generation in the first place. It embodies a constitutional selfreorganization (self-adaptation) of the membrane configuration producing an adaptative response in the presence of its solute. This is the first example of dynamic smart membranes where a solute induces the preparation of its own selective membrane. 

A generalized model of an oscillator, subjected to the influence of external waves is considered. It is shown that the systems of diverse physical background which this model encompasses by their nature should belong to the broader class of kick-excited self-adaptive dynamical systems . 

A class of kick-excited self-adaptive dynamical systems is formed and proposed. The class is characterized by a nonlinear (inhomogeneous) external periodic excitation (as regards the coordinates of the excited system) and is remarkable for the occurrence of the following objective regularities the phenomenon of discrete oscillation excitation in macro-dynamical systems having multiple branch attractors and strong self-adaptive stability. 

A striking example of the so formed class of kick-excited self-adaptive dynamical phenomena and systems is the model of a pendulum influenced by quasi-periodic short-term actions, as considered in papers (Damgov, 2004) - (Damgov and Trenchev, 1999). 

We emphasize the link with the name of the already formed class of kick-excited self-adaptive systems and phenomena the external force is linked, through the function e(x), with the motion coordinate in an adaptive mode, and at the same time it exerts action in the form of short impulses much shorter than the oscillation period of the system. 

General characteristic features of the class of kick-excited self-adaptive dynamical systems, conclusions... 

Damgov, V. and Trenchev PI. Class of Kick-Excited Self-Adaptive Dynamical Systems Quantized Oscillation Excitation. - Chaos, Solitons and Fractals . Oxford, Vol. 17, No 1, P. 11, (2003)... 

Damgov, V. N. Quantized Oscillations and Irregular Behaviour of a Class of Kick-Excited Self-Adaptive Dynamical Systems. Progress of Theoretical Physics Suppl, Kyoto, Japan, No. 139, P. 344 (2000)... 

The ES used here is the mixed-integer ES for bounded search spaces [23]. It can operate on a general mixed-integer search space. The ES uses a population size of /i, with X offspring per generation. Self-adaptation is realized by extending... 

A very popular sequence of inputs is the pseudorandom binary sequence (PRBS). It is easy to generate and has some attractive statistical properties. See System Identification For Self-Adaptive Control, W. D. T. Davies, London, Wiley-Iflterscience, 1970. 

The last twenty years of the last millennium are characterized by complex automatization of industrial plants. Complex automatization of industrial plants means a switch to factories, automatons, robots and self adaptive optimization systems. The mentioned processes can be intensified by introducing mathematical methods into all physical and chemical processes. By being acquainted with the mathematical model of a process it is possible to control it, maintain it at an optimal level, provide maximal yield of the product, and obtain the product at a minimal cost. Statistical methods in mathematical modeling of a process should not be opposed to traditional theoretical methods of complete theoretical studies of a phenomenon. The higher the theoretical level of knowledge the more efficient is the application of statistical methods like design of experiment (DOE). 

It is suggested that a CCN displays the following attributes Development-ally it is self-organized and self-adapting and, in the sense that it is epigenet-ically regulated, it is untrained. Operationally it is a stable, dynamic system, whose oscillatory behavior permits feedback in this regard, it is noted that a CCN operates in a noisy, non-stationary environment, and that it also employs useful and necessary inhibitory inputs. 

G. Karer, I. Skjjanc, and B. Zupancic. Self-adaptive predictive functional control of the temperature in an exothermic batch reactor. Chemical Engineering Processing Process Intensification, 47 2379-2385, 2008. 

Pattern recognition self-adaptive controllers exist that do not explicitly require the modeling or estimation of discrete time models. These controllers adjust their tuning based on the evaluation of the system s closed-loop response characteristics (i.e., rise time, overshoot, settling time, loop damp-... 

When the process changes cannot be measured or predicted, the adaptive control strategy must be implemented in a feedback manner. Many such controllers are referred to as self-tuning controllers, or self-adaptive controllers, and a typical block diagram is shown in Figure 13. 

The most unique and valuable feature of Probability Based Matching, when applied to biological extracts, is its ability to automatically detect the existence of contaminations in a GC peak and to eliminate their interferences. This unusual feat can be accomplished because PBM is a "self-adapting" SIM technique i.e. the computer decides which ions in the contracted spectrum contain valid data and concurrently rejects ions that are contaminated due to the presence of impurities. 

The countercurrent fixed-bed reactor is obviously self-adaptive in that it establishes the necessary temperature level for the respective reaction, whereas in the standard type the temperature level is directly proportional to the slope of the temperature front in the heat exchanger section, dT/dz, which in turn is proportional to the adiabatic temperature rise Taj. 

Complex dynamic and positive feedback between molecular/supramolecular partners in dynamic combinatorial libraries (DCLs) gives rise to emergent functional systems with a collective behavior. From the conceptual point of view, these systems express a synergistic constitutional self-reorganization (self-adaptation) of their configuration, producing an adaptive response in the presence of internal or external structural factors. 

---