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Control of uncertain processes: applied theory and algorithms. (English) Zbl 0607.93070
Kybernetika 22, Suppl. No. 3-6, 72 pp. (1986).
Summary: Some advances in digital control of continuous linear stochastic processes with unknown parameters are reported. The theory is developed with emphasis on algorithmic and numerical aspects. Stochastic input- output models of ARMA form, contingently multivariate and with time delay, are used to represent the process to be controlled but, for numerical reasons in cases of fast sampling rates, also the theoretically equivalent Delta models are considered in parallel. PASCAL procedures, suitable for real time computation and microprocessor implementation, are given for the main resulting algorithms.
This paper is a report on some recent advances in the research on industrial process control carried out at the Institute of Information Theory and Automation of the Czechoslovak Academy of Sciences. It can be considered as a self-contained continuation of the survey of earlier results presented by the author’s colleagues [M. Kárný, A. Halousková, J. Böhm, R. Kulhavý and P. Nedoma, ibid. 21, Suppl. No. 3-6 (1985; Zbl 0586.93040)].

MSC:
93E20 Optimal stochastic control
93C57 Sampled-data control/observation systems
93E25 Computational methods in stochastic control (MSC2010)
62M10 Time series, auto-correlation, regression, etc. in statistics (GARCH)
65C99 Probabilistic methods, stochastic differential equations
68U99 Computing methodologies and applications
93C05 Linear systems in control theory
Full Text: EuDML
References:
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