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Book synopsis

This book presents a data-driven approach to constrained control in the form of a subspace-based state-space system identification algorithm integrated into a model predictive controller. Previous research into this area focused on the system identification aspects resulting in an omission of many of the features that would make such a control strategy attractive to industry. These features include constraint handling, zero-offset set-point tracking and non-stationary disturbance rejection. Parameterisation with Laguerre orthonormal functions was proposed for the reduction in computational load of the controller. Simulation studies were performed using three real-world systems demonstrating: identification capabilities in the presence of white noise and non-stationary disturbances; unconstrained and constrained control; and the benefits and costs of parameterisation with Laguerre polynomials. The discussed algorithms have also been presented in Matlab code.

Book details

• Full title: Model-Free Predictive Control
• Subtitle: An Algorithmic Approach
• Author: Tim Barry
• Language: English
• Binding: Paperback
• Number of pages: 180
• EAN: 9783639227406
• ID: 06830522
• Publisher: VDM Verlag Dr. Müller
• Weight: 284 g
• Dimensions: 220 × 150 × 11 mm
• Published: 2010

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