"Rathousk\u00FD, Jan" . "\u0160techa, Jan" . . . . . "Anaheim" . . "P(GA102/08/0442), P(LA09012), S" . . . "Proceedings of the Third IASTED African Conference on Modelling and Simulation" . . "ACTA Press" . "2010-09-06+02:00"^^ . . "The Pontrjagin maximum principle solves the problem of optimal control of a continuous deterministic system. The discrete maximum principle solves the problem of optimal control of a discrete-time deterministic system. The maximum principle changes the problem of optimal control to a two point boundary value problem which can be completely solved only in special tasks. Optimal control of stochastic systems or even systems with probabilistic parameters is usually derived using stochastic dynamic programming. In the paper an alternative approach based on a stochastic modification of the maximum principle is presented, both for continuous and discrete-time systems. Cautious and certainty equivalent optimal control strategies are then derived using this method and the results are consistent with those achieved by stochastic dynamic programming. Finally, simulations of these optimal control strategies are presented and compared in terms of control quality."@en . "RIV/68407700:21230/10:00172801" . "Simulation of Optimal Stochastic Control Strategies by Maximum Principle"@en . "Gaborone" . "The Pontrjagin maximum principle solves the problem of optimal control of a continuous deterministic system. The discrete maximum principle solves the problem of optimal control of a discrete-time deterministic system. The maximum principle changes the problem of optimal control to a two point boundary value problem which can be completely solved only in special tasks. Optimal control of stochastic systems or even systems with probabilistic parameters is usually derived using stochastic dynamic programming. In the paper an alternative approach based on a stochastic modification of the maximum principle is presented, both for continuous and discrete-time systems. Cautious and certainty equivalent optimal control strategies are then derived using this method and the results are consistent with those achieved by stochastic dynamic programming. Finally, simulations of these optimal control strategies are presented and compared in terms of control quality." . "RIV/68407700:21230/10:00172801!RIV11-GA0-21230___" . . . "287467" . . "[71BB9429A575]" . . "2"^^ . . "Simulation of Optimal Stochastic Control Strategies by Maximum Principle"@en . . . "2"^^ . "1922-8058" . "Simulation of Optimal Stochastic Control Strategies by Maximum Principle" . "Simulation of Optimal Stochastic Control Strategies by Maximum Principle" . . . "Maximum principle; stochastic systems; LQG control; ARX model; Lyapunov and Riccati equations"@en . . . "8"^^ . "978-0-88986-848-9" . . "21230" .