Adaptive networks include a set of nodes with adaptation and learning abilities for modeling various types of self-organized and complex activities encountered in the real world. This paper presents the effect of heterogeneously distributed incremental LMS algorithm with ideal links on the quality of unknown parameter estimation. In heterogeneous adaptive networks, a fraction of the nodes, defi...

This paper presents some technical solutions for monitoring of distributed parameter systems based on the new technologies of virtual instrumentation software architecture and intelligent ad-hoc wireless sensor networks. The virtual instrumentation allows the treatment of physical variables communicating with instruments as programs from a PC. The sensor networks may be placed in the areas of d...

This paper presents a finite element method based modeling and design of control for distributed parameter systems. First, models of distributed parameter systems in the form of lumped-input/distributed-output systems and structure of control loop are introduced. Next, modeling of temperature fields of the casting die as distributed parameter systems in preheating process is performed in COMSOL...

This work extends the geometric theory of output regulation to linear distributed parameter systems with bounded input and output operator, in the case when the reference signal and disturbances are generated by a finite dimensional exogenous system. In particular, it is shown that the full state feedback and error feedback regulator problems are solvable, under the standard assumptions of stab...

In this paper we consider robust output regulation of distributed parameter systems and the internal model principle. The main purpose is to generalize the internal model principle by Francis and Wonham for infinite-dimensional systems and clarify the relationships between different generalizations of the internal model. We also construct a signal generator capable of generating infinite-dimens...

The adaptive output feedback control problem of chemical distributed parameter systems is investigated while the process parameters are unknown. Such systems can be usually modeled by semilinear partial differential equations (PDEs). A combination of Galerkin’s method and proper orthogonal decomposition is applied to generate a reduced order model which captures the dominant dynamic behavior of...

-One-dimensional cable theory provides the theoretical framework to evaluate the role of linear electrical membrane properties and dendritic geometry in neuronal signal reception and processing. This article presents the basic physical principles as well as mathematical problems arising in neuronal modelling. The main types of passive dendritic neuron models are reviewed and their use in explor...

In the paper constrained controllability of distributed parameter dynamical system defined in infinitedimensional domain is considered. Using spectral theory of unbounded differential operators, necessary and sufficient conditions constrained controllability are formulated and proved. Remarks and comments on the relationships between different kinds of controllability are also given. Simple num...

We formulate an optimal design problem for the selection of best states to observe and optimal sampling times and locations for parameter estimation or inverse problems involving complex nonlinear nonlinear partial differential systems. An iterative algorithm for implementation of the resulting methodology is proposed.