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  • Open Daily: 10am - 10pm
    Alley-side Pickup: 10am - 7pm

    3038 Hennepin Ave Minneapolis, MN
    612-822-4611

Open Daily: 10am - 10pm | Alley-side Pickup: 10am - 7pm
3038 Hennepin Ave Minneapolis, MN
612-822-4611
Model Predictive Control: Classical, Robust and Stochastic

Model Predictive Control: Classical, Robust and Stochastic

Kouvaritakis, Basil
Cannon, Mark

Hardcover

Series: Advanced Textbooks in Control and Signal Processing

Technology & EngineeringChemistryGeneral Science

Currently unavailable to order

ISBN10: 3319248510
ISBN13: 9783319248516
Publisher: Springer Nature
Published: Dec 11 2015
Pages: 384
Weight: 2.01
Height: 1.05 Width: 6.21 Depth: 9.54
Language: English

For the first time, a textbook that brings together classical predictive control with treatment of up-to-date robust and stochastic techniques.

Model Predictive Control describes the development of tractable algorithms for uncertain, stochastic, constrained systems. The starting point is classical predictive control and the appropriate formulation of performance objectives and constraints to provide guarantees of closed-loop stability and performance. Moving on to robust predictive control, the text explains how similar guarantees may be obtained for cases in which the model describing the system dynamics is subject to additive disturbances and parametric uncertainties. Open- and closed-loop optimization are considered and the state of the art in computationally tractable methods based on uncertainty tubes presented for systems with additive model uncertainty. Finally, the tube framework is also applied to model predictive control problems involving hard or probabilistic constraints for the cases of multiplicative and stochastic model uncertainty. The book provides:

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