Automated tuning of large-scale multivariable model predictive controllers for spatially-distributed processes

2006 ◽  
Author(s):  
Junqiang Fan ◽  
G.E. Stewart
Keyword(s):  
Large Scale ◽  
Multivariable Model ◽  
Distributed Processes ◽  
Spatially Distributed ◽  
Model Predictive Controllers ◽  
Predictive Controllers ◽  
Automated Tuning

Performance indexes for assistance in retuning multivariable model predictive controllers

2014 ◽  
Author(s):  
Paulo Eduardo Falleiros Cortez ◽  
Agustinho Plucenio ◽  
Daniel Miranda Cruz ◽  
Julio Elias Normey-Rico ◽  
Luis Paulo S. Vasconcellos
Keyword(s):  
Multivariable Model ◽  
Performance Indexes ◽  
Model Predictive Controllers ◽  
Predictive Controllers

scholarly journals Coordinating multiple model predictive controllers for the management of large-scale water systems

2012 ◽  
Vol 15 (2) ◽  
pp. 293-305 ◽  
Author(s):  
Abhay Anand ◽  
Stefano Galelli ◽  
Lakshminarayanan Samavedham ◽  
Sitanandam Sundaramoorthy
Keyword(s):  
Large Scale ◽  
Numerical Study ◽  
Water Reservoir ◽  
Multiple Model ◽  
Reservoir Water ◽  
Systems Model ◽  
Tank System ◽  
Decentralized Controllers ◽  
Model Predictive Controllers ◽  
Predictive Controllers

The optimal management of multi-purpose water reservoir networks is a challenging control problem, because of the simultaneous presence of multiple objectives, the uncertainties associated with the inflow processes and the several interactions between the subsystems. For such systems, model predictive control (MPC) is an attractive control strategy that can be implemented in both centralized and decentralized configurations. The latter is easy to implement and is characterized by reduced computational requirements, but its performance is sub-optimum. However, individual decentralized controllers can be coordinated and driven towards the performance of a centralized configuration. Coordination can be achieved through the communication of information between the subsystems, and the modification of the local control problems to ensure cooperation between the controllers. In this work the applicability of coordination algorithms for the operation of water reservoir networks is evaluated. The performance of the algorithms is evaluated through numerical simulation experiments on a quadruple tank system and a two reservoir water network. The analysis also includes a numerical study of the trade-off between the algorithms' computational burden and the different levels of cooperation. The results show the potential of the proposed approach, which could provide a viable alternative to traditional control methods in real-world applications.

scholarly journals Tuning of multivariable model predictive controllers through expert bandit feedback

2020 ◽  
pp. 1-9
Author(s):  
Alex S. Ira ◽  
Chris Manzie ◽  
Iman Shames ◽  
Robert Chin ◽  
Dragan Nešić ◽  
...  
Keyword(s):  
Multivariable Model ◽  
Model Predictive Controllers ◽  
Predictive Controllers

Application of Generalized Predictive Control to a Fractional Order Plant

2007 ◽  
Author(s):  
Miguel Romero ◽  
A´ngel P. de Madrid ◽  
Carolina Man˜oso ◽  
Roberto Herna´ndez
Keyword(s):  
Fractional Order ◽  
Predictive Control ◽  
Large Scale ◽  
Generalized Predictive Control ◽  
Discrete Approximations ◽  
Stability Performance ◽  
Industry Standard ◽  
Constraints Handling ◽  
Model Predictive Controllers ◽  
Predictive Controllers

This paper deals with the use of model predictive controllers (MPC) for controlling fractional order plants. MPC is an industry standard due to its intrinsic ability to handle input and state constraints for large scale multivariable plants. The method is illustrated with Generalized Predictive Control (GPC) and two low order discrete approximations of the fractional order plant (the so-called Chebyshev-Pade´ and Rational Chebyshev approximations) as model. It is shown how stability, performance and constraints handling can be achieved with ease when dealing with fractional order plants. It is also shown how robustness can be improved by means of a prefilter.

scholarly journals Imposed dynamic irradiation to intensify photocatalytic reactions

2021 ◽  
Author(s):  
Fabian Guba ◽  
Florian Gaulhofer ◽  
Dirk Ziegenbalg
Keyword(s):  
Large Scale ◽  
Reaction Rate ◽  
Photochemical Reactions ◽  
Test Reaction ◽  
Light Emitting ◽  
Photochemical Processes ◽  
Spatially Distributed ◽  
Photocatalytic Reactions ◽  
The Impact ◽  
Photonic Efficiency

AbstractDynamic irradiation is a potent option to influence the interaction between photochemical reactions and mass transport to design high performant and efficient photochemical processes. To systematically investigate the impact of this parameter, the photocatalytic reduction of nitrobenzene was conducted as a test reaction. Dynamic irradiation was realized through provoked secondary flow patterns, multiple spatially distributed light emitting diodes (LEDs) and electrical pulsation of LEDs. A combined experimental and theoretical approach revealed significant potential to enhance photochemical processes. The reaction rate was accelerated by more than 70% and even more important the photonic efficiency was increased by more than a factor of 4. This renders imposed dynamic irradiation an innovative and powerful tool to intensify photoreactions on the avenue to large scale sustainable photochemical processes.

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