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Annual Review in Automatic Programming, 1995
Abstract Progress in the design and use of Model-Based Predictive Control is reviewed. The two-degree-of-freedom solution of many predictive algorithms enables optimal set-point response and rejection of known disturbance patterns, improves robustness against model/plant mismatch, or provides a compromise between these objectives.
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Abstract Progress in the design and use of Model-Based Predictive Control is reviewed. The two-degree-of-freedom solution of many predictive algorithms enables optimal set-point response and rejection of known disturbance patterns, improves robustness against model/plant mismatch, or provides a compromise between these objectives.
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Risk aversion predictive control
ISA Transactions, 2006A quality-controlled predictive control method, suitable for control of fast, remote systems subject to significant communication delays, is developed. Each move is quality controlled in that it independently satisfies a risk-based control performance criterion.
G C, Kember, S E, Mansour, R, Dubay
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ISA Transactions, 2003
In this work a new method for designing predictive controllers for linear single-input/single-output systems is presented. It uses only one prediction of the process output J time intervals ahead to compute the correspondent future error. Then, the predictive feedback controller is defined by introducing a filter which weights the last w predicted ...
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In this work a new method for designing predictive controllers for linear single-input/single-output systems is presented. It uses only one prediction of the process output J time intervals ahead to compute the correspondent future error. Then, the predictive feedback controller is defined by introducing a filter which weights the last w predicted ...
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Hierarchical model predictive control
2007 46th IEEE Conference on Decision and Control, 2007This paper deals with the problem of designing stable hierarchical control schemes with Model Predictive Control (MPC). Specifically, at any layer of the considered structure, a robust MPC regulator is used to compute the control variables. In turn, these variables are produced by the subsystems at lower layers and must fulfill the robustness ...
COLANERI, PATRIZIO, SCATTOLINI, RICCARDO
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Stable Constrained Predictive Control
IFAC Proceedings Volumes, 1994A multivariable linear controller based upon pole placement design is developed. This apriori assures stability of the closed-loop system. The generalized controller from the family of all stabilizing controllers satisfying given constraints on inputs and/or outputs is then searched.
M. FIKAR, J. MIKLEŠ
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Decentralized Model Predictive Control
2010Decentralized and distributed model predictive control (DMPC) addresses the problem of controlling a multivariable dynamical process, composed by several interacting subsystems and subject to constraints, in a computation and communication efficient way.
Bemporad, Alberto, Barcelli, Davide
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A DISCRETE PREDICTING CONTROLLER
British Journal of Mathematical and Statistical Psychology, 1967This paper describes an attempt to develop a control device which has some of the characteristics of human processing rather than of the lead‐lag formulations of control theory. The controller's sensory limitations, the way in which it internally represents the behaviour of the system under control, and its control strategy, are described.
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Nonlinear Model Predictive Control: Control and Prediction Horizon
IFAC Proceedings Volumes, 2000Abstract In this paper a new class of Model Predictive control algorithms for nonlinear systems is introduced. A prediction horizon longer than the control horizon is used. It is shown that in this way it is possible to enlarge the domain of attraction and to improve the performance without enlarging the dimension of the optimization space.
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