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Multi-objective Model Predictive Control
2018 Joint 10th International Conference on Soft Computing and Intelligent Systems (SCIS) and 19th International Symposium on Advanced Intelligent Systems (ISIS), 2009For many real-world problems, true function form cannot be given a prior. Consequently, for example, engineering design requires experiments and/or numerical simulations to evaluate objective and constraint functions as function in terms of design variables. However, those experiments/simulations are computationally expensive.
Yeboon Yun, Hirotaka Nakayama, Min Yoon
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Cooperative distributed model predictive control
Systems & Control Letters, 2010zbMATH Open Web Interface contents unavailable due to conflicting licenses.
STEWART BT +4 more
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Well-conditioned model predictive control
ISA Transactions, 2004Model-based predictive control is an advanced control strategy that uses a move suppression factor or constrained optimization methods for achieving satisfactory closed-loop dynamic responses of complex systems. While these approaches are suitable for many processes, they are formulated on the selection of certain parameters that are ambiguous and also
Rickey, Dubay +2 more
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NEURAL MODELS IN PREDICTIVE CONTROL
IFAC Proceedings Volumes, 1995Abstract Model Based Predictive Control (MBPC) has not yet been widely used biotechnology, although in other areas successful application have been reported. This mainly because accurate nonlinear models are usually not available for biotechnological processes.
H.J.L. van Can +4 more
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Model Predictive Pulse Pattern Control
IEEE Transactions on Industry Applications, 2011Industrial applications of medium-voltage drives impose increasingly stringent performance requirements, particularly with regards to harmonic distortions of the phase currents of the controlled electrical machine. An established method to achieve very low current distortions during steady-state operation is to employ offline calculated optimized pulse
Tobias Geyer +3 more
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2012
This chapter analyses the behaviour of the plant under generalised predictive control where the power plant is modelled as a MIMO linear and nonlinear system. The nonlinear model includes elastic water column effects. The response of the system with these controllers is compared with classical controllers.
German Ardul Munoz-Hernandez +2 more
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This chapter analyses the behaviour of the plant under generalised predictive control where the power plant is modelled as a MIMO linear and nonlinear system. The nonlinear model includes elastic water column effects. The response of the system with these controllers is compared with classical controllers.
German Ardul Munoz-Hernandez +2 more
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2004
Model predictive control is the most important control technique used in industry for multivariable systems. It allows to take into account constraints on the manipulated inputs, their moves and even the controlled outputs. It is described under different forms, as dynamic matrix control and quadratic dynamic matrix control.
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Model predictive control is the most important control technique used in industry for multivariable systems. It allows to take into account constraints on the manipulated inputs, their moves and even the controlled outputs. It is described under different forms, as dynamic matrix control and quadratic dynamic matrix control.
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Internal model predictive control (IMPC)
Automatica, 1995A computationally simple model predictive control algorithm incorporates the attractive features of the internal model control (IMC) law. The algorithm first computes the IMC control effort via a model state feedback implementation which automatically compensates for past control effort saturation.
Coulibaly, Eric +2 more
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Hierarchical Model Predictive Control of Wiener Models
2009A hierarchical two-layer control structure is designed with robust Model Predictive Control. The system at the upper level is described by a Wiener model, while the systems at the lower level, which represent the fast actuators dynamics, are described by general nonlinear models.
PICASSO, BRUNO +2 more
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