Optimal Control of Mobile Agents for Monitoring of Points on a Network
V. Sgurev, S. Drangajov
Key Words:
Mobile agents' path control; network flow optimization; cycles on graphs.
Abstract:
This paper concerns the problems of finding optimal trajectories between nodes on a network, which must be periodically surveyed, and probably serviced. It is shown, that such trajectories may be generated if optimal Hamiltonian cycles are used between the separate network nodes under inspection. It is known that the Hamiltonian path problem is NP-complete, but an edge decomposition of the network is proposed. This is performed by reducing in a particular way to network flow circulations. The requirements and the equations for describing such circulation are pointed out. Defining of the optimal circulations of the mobile agents is reduced to network flow programming problems. A numerical example is presented for solving a similar class of monitoring problems by mobile agents.

A Hardware-In-The-Loop Simulation Architecture for Integration of Smart Buildings and Distributed Energy Resources in Micro Grids
G. Costanzo, L. Ferrarini, G. Mantovani, A. Krusteva, M. Georgiev, M. Antchev
Key Words:
HIL simulation; smart grids; smart buildings; renewable energy integration.
Abstract:
This paper presents the design, implementation and test of hardware in the loop simulation architecture for integration of Smart Buildings and distributed energy resources in Micro Grids. The rationale for this work is the integration of off-the-shelves devices in a HIL simulation setup within software development. The architecture and preliminary results are presented, together with a case study for integrating flexible units, such as a space heating system and Electric Vehicles in a Smart Building equipped with local solar energy production.

Adaptive Tuning Functions Tracking Control with Nonlinear Adaptive Observers
R. Mishkov, V. Petrov
Key Words:
Nonlinear systems; adaptive control; adaptive observers; adaptive parameter estimators; Lyapunov stability.
Abstract:
The paper is dedicated to the derivation of a unified approach for nonlinear adaptive closed loop system design with nonlinear adaptive state and parameter observers combined with tuning functions-based nonlinear adaptive control for trajectory tracking. The proposed approach guarantees asymptotic stability of the closed loop nonlinear adaptive system with respect to the tracking and state estimation errors and Lyapunov stability of the parameter estimator. The advantages of the approach are the lack of over-parametrization, resulting in a minimal number of estimator equations and the preservation of the overdamped performance specifications of the closed loop nonlinear adaptive system in its whole range of operation. The application of the approach to a permanent magnet synchronous motor driven inverted pendulum concludes with simulation of the closed loop nonlinear adaptive system time responses.

General Forms of a Class of Multivariable Regression Models
A. Efremov
Key Words:
MIMO model; linear parameterization; parameter matrix form; parameter vector form; stepwise regression.
Abstract:
There are two possible general forms of multiple input multiple output (MIMO) regression models, which are either linear with respect to their parameters or non-linear, but in order to estimate their parameters, at a certain stage it could be assumed that they are linear. This is in fact the basic assumption behind the linear approach for parameters estimation. There are two possible representations of a MIMO model, which at a certain level could be fictitiously presented as linear functions of its parameters. One representation is when the parameters are collected in a matrix and hence, the regressors are in a vector. The other possible case is the parameters to be in a vector, but the regressors at a given instant to be placed in a matrix. Both types of representations are considered in the paper. Their advantages and disadvantages are summarized and their applicability within the whole experimental modelling process is also discussed.

Investigation of the Indirect Hypercube as Natural Architecture for Parallel Algorithms of a Transpose Type for FFT and other Fourier-Related Transforms
Ph. Philipov, V. Lazarov
Key Words:
Parallel FFT; parallel FHT; parallel real-valued FFT; parallel FCT; indirect hypercube; high-performance computer architectures.
Abstract:
The natural architectures are architectures, derived from the signal graph of the corresponding algorithm. That is why they are considered to be the most appropriate architectures for parallel realization of this algorithm. For Fast Fourier Transform algorithm (FFT) two types of natural architectures are known – the direct and the indirect hypercube. The direct hypercube has been investigated and analyzed a long time ago. The development of the concept of Indirect Hypercube, although quite old, is too difficult, controversal and still unfinished. Fast Hartley transform (FHT)/Real-valued Fast Fourier transform (RFFT) algorithms are important Fourier-related transforms, because they lower twice the operational and memory requirements when the input data is realvalued. These types of algorithms, however, have an irregular computational structure, which makes their parallel implementation a very difficult task. The aim of this paper is, based on the results achieved so far, to present further development of the concept Indirect Hypercube. A method of parametric synthesis of an indirect hypercube is described as a model of parallel FFT algorithms of a transpose type with different granularity/radix. This method is generalized for relevant RFFT/FHT and FCT algorithms. Two types of SIMD array architectures are described (radix-2 and radix-4), based on the indirect hypercube concept. These architectures are implemented as fast FFT/RFFT/FHT processors for real time applications. The performance estimation, as well as the estimation of resource utilization is carried out.