Stochastic Optimization of Linear Dynamic Systems with Parametric Uncertainties
Vadim Yatsenko (State Design Office Yuzhnoye, Ukraine)
TL;DR
This paper introduces a tensor-based stochastic optimization method for linear dynamic systems with parametric uncertainties, addressing prediction, data processing, and optimal control.
Contribution
It presents a novel tensor formalism approach to model parametric uncertainties in stochastic optimization of linear systems.
Findings
Effective in modeling parametric uncertainties
Improves prediction and control accuracy
Demonstrated through simulation results
Abstract
This paper describes a new approach to solving some stochastic optimization problems for linear dynamic system with various parametric uncertainties. Proposed approach is based on application of tensor formalism for creation the mathematical model of parametric uncertainties. Within proposed approach following problems are considered: prediction, data processing and optimal control. Outcomes of carried out simulation are used as illustration of properties and effectiveness of proposed methods.
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Taxonomy
TopicsSimulation Techniques and Applications