Adaptive on-line steady-state optimization of slow dynamic processes

DOI10.1016/0005-1098(78)90087-0zbMath0385.49020OpenAlexW2029687122MaRDI QIDQ1249340

K. Appert

Publication date: 1978

Published in: Automatica (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/0005-1098(78)90087-0

Mathematics Subject Classification ID

System identification (93B30) Nonlinear systems in control theory (93C10) Adaptive control/observation systems (93C40) Numerical methods in optimal control (49M99)

Related Items (10)

New approach to stochastic optimizing control of steady-state systems using dynamic information ⋮ Improvements in the formulation and solution approach for stochastic optimizing control of steady state industrial processes ⋮ Asymptotic normality analysis of the estimation error of steady-state models for industrial processes: SISO case ⋮ Steady-state identification for large-scale industrial process by means of dynamic models ⋮ On an algorithm for combined system optimisation and parameter estimation ⋮ Periodic optimization of Hammerstein-type systems ⋮ Comparison of methods for estimating real process derivatives in on-line optimization ⋮ A note on dead-beat controllability of generalised Hammerstein systems ⋮ Controllability for a class of simple Wiener-Hammerstein systems ⋮ Instrumental-variable methods for identification of Hammerstein systems

Cites Work

• A theoretical analysis of recursive identification methods
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