Nonlinear Industrial Control Systems Optimal Polynomial Systems and State-Space Approach
Fr. 277.00
inkl. gesetzl. MwSt.,
Beschreibung
Produktdetails
Einband
Gebundene Ausgabe
Erscheinungsdatum
20.05.2020
Abbildungen
XXX, 305 illus., 274 illus. in color. With online files/update., farbige Illustrationen, schwarz-weiss Illustrationen
Verlag
Springer LondonSeitenzahl
764
Maße (L/B/H)
24.1/16/4.8 cm
Gewicht
1330 g
Auflage
1st ed. 2020
Sprache
Englisch
ISBN
978-1-4471-7455-4
Nonlinear Industrial Control Systems presents a range of mostly optimisation-based methods for severely nonlinear systems; it discusses feedforward and feedback control and tracking control systems design. The plant models and design algorithms are provided in a MATLAB® toolbox that enable both academic examples and industrial application studies to be repeated and evaluated, taking into account practical application and implementation problems.
The text makes nonlinear control theory accessible to readers having only a background in linear systems, and concentrates on real applications of nonlinear control. It covers:
- different ways of modelling nonlinear systems including state space, polynomial-based, linear parameter varying, state-dependent and hybrid;
- design techniques for nonlinear optimal control including generalised-minimum-variance, model predictive control, quadratic-Gaussian, factorised and H ∞ design methods;
- design philosophies that are suitable for aerospace, automotive, marine, process-control, energy systems, robotics, servo systems and manufacturing;
- steps in design procedures that are illustrated in design studies to define cost-functions and cope with problems such as disturbance rejection, uncertainties and integral wind-up; and
- baseline non-optimal control techniques such as nonlinear Smith predictors, feedback linearization, sliding mode control and nonlinear PID.
Nonlinear Industrial Control Systems is valuable to engineers in industry dealing with actual nonlinear systems. It provides students with a comprehensive range of techniques and examples for solving real nonlinear control design problems.
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