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{"references": ["K. A. Puvkov, N. D. Egupov, A. M. Makarenkov, Theory and Numerical\nMethods for Studying Stochastic Systems. Moscow, Fizmatlits, 2003 (in\nRussian).", "E. V. Seregina, A . M. Makarenkov , M .A. Stepovich, \"Use of the\nprojective method for determining statistical characteristics of the\nsolution to the differential diffusion equation of minority carriers\ngenerated in a semiconductor material by a Wide Electron Beam\" in\nJournal of Surface Investigation. X-ray, Synchrotron and Neutron\nTechniques, Vol. 3, No. 3, 2009, pp. 468-482", "S. V. Lapin and N. D. Egupov, Theory of Matrix Operators and its\nApplication to Automatic Control Problems. Moscow, MGTU, 1997(in\nRussian)", "V. I. Smirnov, Course of Higher Mathematics. Moscow, Nauka, 1967(in\nRussian)", "K. A. Puvkov, N. D. Egupov, Classical and modern theory of control\nsystem. Moscow, MGTU , Vol.2 ,ch.2"]}
To increase precision and reliability of automatic control systems, we have to take into account of random factors affecting the control system. Thus, operational matrix technique is used for statistical analysis of first order plus time delay system with uniform random parameter. Examples with deterministic and stochastic disturbance are considered to demonstrate the validity of the method. Comparison with Monte Carlo method is made to show the computational effectiveness of the method.
Walsh function., Statistical analysis, First order plus dead-time, Operational matrix
Walsh function., Statistical analysis, First order plus dead-time, Operational matrix
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