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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
Robust and Adaptive Model Predictive Control of Nonlinear Systems

Robust and Adaptive Model Predictive Control of Nonlinear Systems

Guay, Martin
Adetola, Veronica
DeHaan, Darryl

Hardcover

Series: Control, Robotics and Sensors

Technology & Engineering

ISBN10: 1849195528
ISBN13: 9781849195522
Publisher: Institution Of Engineering & T
Published: Nov 13 2015
Pages: 272
Weight: 1.20
Height: 0.80 Width: 6.40 Depth: 9.40
Language: English

Most physical systems possess parametric uncertainties or unmeasurable parameters and, since parametric uncertainty may degrade the performance of model predictive control (MPC), mechanisms to update the unknown or uncertain parameters are desirable in application. One possibility is to apply adaptive extensions of MPC in which parameter estimation and control are performed online. This book proposes such an approach, with a design methodology for adaptive robust nonlinear MPC (NMPC) systems in the presence of disturbances and parametric uncertainties. One of the key concepts pursued is the concept of set-based adaptive parameter estimation, which provides a mechanism to estimate the unknown parameters as well as an estimate of the parameter uncertainty set. The knowledge of non-conservative uncertain set estimates is exploited in the design of robust adaptive NMPC algorithms that guarantee robustness of the NMPC system to parameter uncertainty.

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