Adaptive Parameter Estimation in Systems described by Irrational TransferFunctions

Predmet istraživanja je identifikaciji i adaptivna estimacija parametara široke klase linearnih sistema. Predloženi algoritmi za adaptivnu estimaciju parametara su primenjivi na sisteme koji se opisuju funkcijama prenosa proizvoljnog oblika, što uključuje sisteme sa kašnjenjem, distribuiranim parametrima, frakcione sisteme i druge sisteme opisane iracionalnim funkcijama prenosa. Na posletku, dat je algoritam za identifikaciju CNG sistema koji se ne izvršava u realnom vremenu i pretpostavlja da struktura modela nije poznata unapred.The subject of this research is the system identification and adaptive parameter estimation in wide class of linear processes. Proposed approaches for adaptive parameter estimation can be applied to systems described by transfer functions of arbitrary form, including systems with delay, distributed-paratemeter systems, fractional order systems, and other system described by irrational transfer functions. In the final part, an offline algorithm for identification of CNG system which does not assume any a priori known model structure is proposed

Adaptive Parameter Estimation in Systems described by Irrational TransferFunctions

Predmet istraživanja je identifikaciji i adaptivna estimacija parametara široke klase linearnih sistema. Predloženi algoritmi za adaptivnu estimaciju parametara su primenjivi na sisteme koji se opisuju funkcijama prenosa proizvoljnog oblika, što uključuje sisteme sa kašnjenjem, distribuiranim parametrima, frakcione sisteme i druge sisteme opisane iracionalnim funkcijama prenosa. Na posletku, dat je algoritam za identifikaciju CNG sistema koji se ne izvršava u realnom vremenu i pretpostavlja da struktura modela nije poznata unapred.The subject of this research is the system identification and adaptive parameter estimation in wide class of linear processes. Proposed approaches for adaptive parameter estimation can be applied to systems described by transfer functions of arbitrary form, including systems with delay, distributed-paratemeter systems, fractional order systems, and other system described by irrational transfer functions. In the final part, an offline algorithm for identification of CNG system which does not assume any a priori known model structure is proposed

An approach to optimal architectural and urban design from the energy efficiency point of view

This paper presents a new approach to architecture and urban design that results in an increase of the energy efficiency of buildings set close to each other, which is set as the optimization problem. The main goal is to maximize the sunlight impact on objects, in a way to minimize inter-object shading on each building. The problem is solved by the PSO (Particle Swarm Optimization) algorithm and its modifications, as well as the application of PSO algorithm with niches, which makes it possible to find a large number of local optima. It turned out that the PSO algorithm with niches is especially suitable for solving the described problems. The proposed methodology is illustrated by a few examples

Towards a Flexible Smart Factory with a Dynamic Resource Orchestration

Amid the current industrial revolution, a total disruption of the existing production lines may seem to be the easiest approach, as the potential possibilities seem limitless when starting from the ground up. On the business side, an adaptation of existing production lines is always a preferred option. In support of adaptation as opposed to disruption, this paper presents a new approach of using production process orchestration in a smart factory, discussed in an industrial case-study example. A proposed smart factory has the Orchestrator component in its core, responsible for complete semantical orchestration of production processes on one hand, and various factory resources on the other hand, in order to produce the desired product. The Orchestrator is a complex, modular, highly scalable, and pluggable software product responsible for automatised planning, scheduling, and execution of the complete production process. According to their offered capabilities, non-smart and smart resources—machines, robots, humans—are simultaneously and dynamically assigned to execute their dedicated production steps

Adaptive Parameter Estimation in LTI Systems

An adaptive algorithm solving the on-line parameter estimation problem for a broad class of linear systems is proposed. The approach can be applied to systems with delay, distributedparameter systems, fractional-order systems, and others that are stable or stabilized by linear feedback. The proposed scheme can be applied to simultaneously track sufficiently slow changes in process gains, delays, time constants, diffusivity, and other parameters. The proposed method is gradient-based, and it yields a relatively efficient numerical implementation. Convergence and robustness of the algorithm are investigated through Lyapunov analysis, yielding explicit convergence conditions that generalize the well-known “persistence of excitation” and identifiability requirements arising in conventional adaptive estimation. The method is illustrated by several examples

Complex-Order Models: A System Identification Point of View

The present paper proposes a framework for the systematic and fruitful application of complex-order operators for modeling and control applications. We emphasize that special care must be taken when using complex-order elements to ensure that their responses to real-valued stimuli are real-valued themselves. The proposed complex-order real-valued elements enable the seamless generalization of their conventional real and integer-order counterparts. We further demonstrate how any linear operator can be extended in much the same way as the differintegral, by “raising” it to a power of a complex order, while ensuring that its kernel remains real-valued. The applicability of our considerations is demonstrated by a model of a compressed natural gas injection system

Complex-Order Models: A System Identification Point of View

The present paper proposes a framework for the systematic and fruitful application of complex-order operators for modeling and control applications. We emphasize that special care must be taken when using complex-order elements to ensure that their responses to real-valued stimuli are real-valued themselves. The proposed complex-order real-valued elements enable the seamless generalization of their conventional real and integer-order counterparts. We further demonstrate how any linear operator can be extended in much the same way as the differintegral, by “raising” it to a power of a complex order, while ensuring that its kernel remains real-valued. The applicability of our considerations is demonstrated by a model of a compressed natural gas injection system