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- W2029122577 abstract "An underlying relationship between a dynamic stochastic control system and its steady-state counterpart is thoroughly investigated. A novel approach which uses both dynamic and steady-state information for solving the stochastic steady-state optimizing control problem is presented. A two-stage steady-state system identification technique is proposed and employed in the presented approach to estimate the expectation of the real process derivative. Compared with integrated system optimization and parameter estimation (ISOPE) methods, this new approach has reduced significantly the required controller set point changes and is much less sensitive when subjected to noise. Optimality of the algorithm is examined and sufficient conditions for global convergence are provided. Consistency and asymptotic behaviour of the two-stage identification method are also investigated. Computer simulations are provided and comparisons are made between the ISOPE method and the presented approach. Simulation results show that this new approach is very efficient and reliable." @default.
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- W2029122577 date "1989-12-01" @default.
- W2029122577 modified "2023-10-16" @default.
- W2029122577 title "New approach to stochastic optimizing control of steady-state systems using dynamic information" @default.
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- W2029122577 doi "https://doi.org/10.1080/00207178908953494" @default.
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