Explicit nonlinear model predictive control : theory and applications
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The work Explicit nonlinear model predictive control : theory and applications represents a distinct intellectual or artistic creation found in Boston University Libraries. This resource is a combination of several types including: Work, Language Material, Books.
The Resource
Explicit nonlinear model predictive control : theory and applications
Resource Information
The work Explicit nonlinear model predictive control : theory and applications represents a distinct intellectual or artistic creation found in Boston University Libraries. This resource is a combination of several types including: Work, Language Material, Books.
 Label
 Explicit nonlinear model predictive control : theory and applications
 Title remainder
 theory and applications
 Statement of responsibility
 Alexandra Grancharova and Tor Arne Johansen
 Subject

 Predictive control
 Systems theory.
 Nonlinear control theory
 Ingénierie
 Complexity
 Electronic books
 Systems Theory, Control
 Nonlinear control theory
 Nonlinear Dynamics
 Nonlinear control theory
 Electronic resources
 Predictive control
 Systems Theory, Control.
 Nonlinear Dynamics.
 Complexity.
 Predictive control
 Predictive control
 Engineering.
 Control.
 Nonlinear control theory
 Control
 Language
 eng
 Summary
 Nonlinear Model Predictive Control (NMPC) has become the accepted methodology to solve complex control problems related to process industries. The main motivation behind explicit NMPC is that an explicit state feedback law avoids the need for executing a numerical optimization algorithm in real time. The benefits of an explicit solution, in addition to the efficient online computations, include also verifiability of the implementation and the possibility to design embedded control systems with low software and hardware complexity. This book considers the multiparametric Nonlinear Programming (mpNLP) approaches to explicit approximate NMPC of constrained nonlinear systems, developed by the authors, as well as their applications to various NMPC problem formulations and several case studies. The following types of nonlinear systems are considered, resulting in different NMPC problem formulations: Ø Nonlinear systems described by firstprinciples models and nonlinear systems described by blackbox models; Ø Nonlinear systems with continuous control inputs and nonlinear systems with quantized control inputs; Ø Nonlinear systems without uncertainty and nonlinear systems with uncertainties (polyhedral description of uncertainty and stochastic description of uncertainty); Ø Nonlinear systems, consisting of interconnected nonlinear subsystems. The proposed mpNLP approaches are illustrated with applications to several case studies, which are taken from diverse areas such as automotive mechatronics, compressor control, combustion plant control, reactor control, pH maintaining system control, cart and spring system control, and diving computers
 Cataloging source
 GW5XE
 Image bit depth
 0
 LC call number
 TJ217.6
 LC item number
 .G73 2012
 Literary form
 non fiction
 Nature of contents
 dictionaries
 Series statement
 Lecture Notes in Control and Information Sciences,
 Series volume
 429
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