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Research of evolution robust parametric linier-quadratic regulator design advantages with probability stabilization performance estimation
Engineering Bulletin # 02, February 2016
УДК: 004.94
This paper makes review the problem of performance optimization of linear-quadratic regulation if plant has parametric uncertain. Considered probabilistic averaging model for regulation performance estimation when distribution of uncertain parameters is known. To solve this task, the original real-coded genetic algorithm, based on introduced multycrossover operator and different kinds of microevolution, is purposed. Algorithm also uses priory mutation strategies and inner moderate diminsation algorithms. In case when low number of uncertain parameters accounted it has been shown that at reasonable time algorithm allows receive parameters of control module witch supply quality robust stabilization for width range of uncertain parameter values. The main conclusion of this paper is that quasi-optimal solution received by algorithm for low number of uncertain parameters has tend to save averaging performance – unvalued enough quality robustness reserve when additional variation of parameters is taken into consideration as shown by the linear system example but attestative tests on expanded ranges still required.
Synthesis of control in stochastic systems by generalized polynomial chaos
Engineering Education # 05, May 2012
DOI: 10.7463/0512.0410536
One of the main difficulties of analysis and synthesis of control in stochastic systems is the need of operation in multi-dimensional abstract spaces which are typically infinite-dimensional and difficult to interpret physically. A method was proposed to solve the problem of synthesis of control in stochastic systems using generalized polynomial chaos. The method allows to transform the original problem with a stochastic model into a problem with a deterministic model of high-dimensional state space of a dynamical system. This problem can be solved by known numerical methods.
77-30569/376455 Synthesis of optimal control systems for dynamic objects with random initial values
Engineering Education # 03, March 2012
 The authors formulate a problem of control systems synthesis for dynamic objects with random initial values. It was proposed for the synthesis to modify functionals of quality to form sum of values with weights for each initial value. Weights determine probabilities of initial values.  It was proposed to use the numerical network operator technique for solving the synthesis problem. An example of control system synthesis for an aircraft at the descend stage is presented in the article.
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