Multi-scenario robust online optimization and control of fed-batch systems via dynamic model-based scenario selection

AIChE Journal ◽  
2016 ◽  
Vol 62 (9) ◽  
pp. 3264-3284 ◽  
Author(s):  
Francesco Rossi ◽  
Gintaras Reklaitis ◽  
Flavio Manenti ◽  
Guido Buzzi-Ferraris
Keyword(s):  
Dynamic Model ◽  
Online Optimization ◽  
Fed Batch ◽  
Model Based ◽  
Batch Systems ◽  
Optimization And Control ◽  
And Control

On-line model-based optimization and control of fed-batch processes using Matlab code, OPC server, SCADA, and PLC

2012 ◽  
Vol 29 ◽  
pp. S163 ◽  
Author(s):  
Juris Vanags ◽  
Vytautas Galvanauskas ◽  
Oskars Grigs ◽  
Konstantins Dubencovs ◽  
Valerija Stepanova
Keyword(s):  
Batch Processes ◽  
Fed Batch ◽  
Line Model ◽  
Opc Server ◽  
Matlab Code ◽  
Model Based ◽  
Optimization And Control ◽  
On Line ◽  
And Control

scholarly journals Applied Model-Based Analysis and Synthesis for the Dynamics, Guidance, and Control of an Autonomous Undersea Vehicle

2010 ◽  
Vol 2010 ◽  
pp. 1-23 ◽  
Author(s):  
Kangsoo Kim ◽  
Tamaki Ura
Keyword(s):  
Dynamic Model ◽  
Equations Of Motion ◽  
Environmental Disturbances ◽  
Guidance And Control ◽  
Model Based ◽  
Optimal Guidance ◽  
Analysis And Synthesis ◽  
Undersea Vehicle ◽  
And Control ◽  
Model Based Analysis

Model-based analysis and synthesis applied to the dynamics, guidance, and control of an autonomous undersea vehicle are presented. As the dynamic model for describing vehicle motion mathematically, the equations of motion are derived. The stability derivatives in the equations of motion are determined by a simulation-based technique using computational fluid dynamics analysis. The dynamic model is applied to the design of the low-level control systems, offering model-based synthetic approach in dynamics and control applications. As an intelligent navigational strategy for undersea vehicles, we present the optimal guidance in environmental disturbances. The optimal guidance aims at the minimum-time transit of a vehicle in an environmental flow disturbance. In this paper, a newly developed algorithm for obtaining the numerical solution of the optimal guidance law is presented. The algorithm is a globally working procedure deriving the optimal guidance in any deterministic environmental disturbance. As a fail-safe tactic in achieving the optimal navigation in environments of moderate uncertainty, we propose the quasi-optimal guidance. Performances of the optimal and the quasi-optimal guidances are demonstrated by the simulated navigations in a few environmental disturbances.

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