In today industry the demand for higher performances under economic and environmental constraints cannot be satisfied by simple upgrade of previous components. New phenomena related to handling systems heterogeneity and number of components have recently opened a broad domain of investigations on phenomena related to this new structure. Because both power and information fluxes are now concerned, different problems are identified concerning internal system coordination and control, information flux handling and communication between a networked cluster of systems. Analysis of passage to complex stage shows that previous steps defined for simpler system situation have to be reassessed for meeting the new requirements imposed by complex status. In particular for power flux it is mandatory that asymptotic stability be satisfied inside a robustness ball of at least the size of system uncertainty. So, following bottom-up approach described here, classical trajectory system control should be upgraded to more adapted task control.
Michel Cotsaftis made a research on the toward global complex systems control the autonomous intelligence challenge, and the research result published on the journal of autonomous intelligence.
In this paper,the construction of new controller is made possible in two steps by developing an explicit trajectory control of functional nature, which is asymptotically stable and robust enough to cover the manifold of possible trajectories. Second, by introducing the concept of “useful” information, a task functional expressed in terms of system parameters is set up which defines compatible trajectory manifold. From them a double loop is written giving the system the possibility to accomplish the task for any allowed trajectory by determining its path from its own elements.
The result turns out to better perform than (also explicit) extension of Popov criterion to more general nonlinear monotonically upper bounded potentials bounding system dynamics discussed here. An interesting observation is that when correctly amended as proposed here, complex systems are not as commonly believed a counterexample to reductionism so strongly influential in Science with Cartesian method supposedly only valid for complicated systems.
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