About the Choice of State Space Basis in Combined Deterministic-stochastic Subspace Identiication 1 Technology and Culture. the Scientiic Responsibility Rests with Its Authors
نویسنده
چکیده
This paper describes how the state space basis of models identi ed with subspace identi cation algorithms can be determined. It is shown that this basis is determined by the input spectrum and by user de ned input and output weightings. Through the connections between subspace identi cation and frequency weighted balancing, the state space basis of the subspace identi ed models is shown to coincide with a frequency weighted balanced basis.
منابع مشابه
Algorithms and Lapack-based Software for Subspace Identification
Basic algorithms and LAPACK-based Fortran software for multivariable system identiication by subspace techniques are brieey described. Deterministic and combined deterministic-stochastic identiication problems are dealt with using two approaches. A state space model is computed from input-output data sequences. Multiple data sequences, collected by possibly independent identiication experiments...
متن کاملMulti-choice stochastic bi-level programming problem in cooperative nature via fuzzy programming approach
In this paper, a Multi-Choice Stochastic Bi-Level Programming Problem (MCSBLPP) is considered where all the parameters of constraints are followed by normal distribution. The cost coefficients of the objective functions are multi-choice types. At first, all the probabilistic constraints are transformed into deterministic constraints using stochastic programming approach. Further, a general tran...
متن کاملA novel bi-level stochastic programming model for supply chain network design with assembly line balancing under demand uncertainty
This paper investigates the integration of strategic and tactical decisions in the supply chain network design (SCND) considering assembly line balancing (ALB) under demand uncertainty. Due to the decentralized decisions, a novel bi-level stochastic programming (BLSP) model has been developed in which SCND problem has been considered in the upper-level model, while the lower-level model contain...
متن کاملNonlinear System Identification Using Hammerstein-Wiener Neural Network and subspace algorithms
Neural networks are applicable in identification systems from input-output data. In this report, we analyze theHammerstein-Wiener models and identify them. TheHammerstein-Wiener systems are the simplest type of block orientednonlinear systems where the linear dynamic block issandwiched in between two static nonlinear blocks, whichappear in many engineering applications; the aim of nonlinearsyst...
متن کاملSplittable stochastic project scheduling with constrained renewable resource
This paper discusses the problem of allocation of constrained renewable resource to splittable activities of a single project. If the activities of stochastic projects can be split, these projects may be completed in shorter time when the available resource is constrained. It is assumed that the resource amount required to accom-plish each activity is a discrete quantity and deterministic. The ...
متن کامل