Get 20M+ Full-Text Papers For Less Than $1.50/day. Start a 14-Day Trial for You or Your Team.

Learn More →

A Quadratic Constraint Approach to Model Predictive Control of Interconnected SystemsQuadratic Constraint for Decentralised Model Predictive Control

A Quadratic Constraint Approach to Model Predictive Control of Interconnected Systems: Quadratic... [The asymptotically positive realness constraint (APRC) and quadratic dissipativity constraint (QDC) are introduced in this chapter as an effective tool for designing decentralised control systems, especially the decentralised model predictive control, in the discrete-time domain. We derive the convergence conditions for interconnected systems on the grounds of global system dissipation, subsystem dissipation, coupling structure, and dissipation-based constraints (APRC or QDC in the case of quadratic constraints) of all controlled subsystems. These conditions are suitable for the decentralised and distributed control of interconnected systems that prohibit artificial constraints on the unmeasurable coupling vectors. A convex quadratic constraint on the current-time control vector is subsequently developed from the dissipation-based constraint and applied to the model predictive control (MPC) as an enforced attractivity constraint. The attractivity constraints for controlled subsystems can be fully decoupled in this approach. Only linear-time-invariant (LTI) interconnected systems are under the scope of this chapter.] http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png

A Quadratic Constraint Approach to Model Predictive Control of Interconnected SystemsQuadratic Constraint for Decentralised Model Predictive Control

Loading next page...
 
/lp/springer-journals/a-quadratic-constraint-approach-to-model-predictive-control-of-WdeePEb3EJ

References (0)

References for this paper are not available at this time. We will be adding them shortly, thank you for your patience.

Publisher
Springer Singapore
Copyright
© Springer Nature Singapore Pte Ltd. 2018
ISBN
978-981-10-8407-2
Pages
31 –57
DOI
10.1007/978-981-10-8409-6_2
Publisher site
See Chapter on Publisher Site

Abstract

[The asymptotically positive realness constraint (APRC) and quadratic dissipativity constraint (QDC) are introduced in this chapter as an effective tool for designing decentralised control systems, especially the decentralised model predictive control, in the discrete-time domain. We derive the convergence conditions for interconnected systems on the grounds of global system dissipation, subsystem dissipation, coupling structure, and dissipation-based constraints (APRC or QDC in the case of quadratic constraints) of all controlled subsystems. These conditions are suitable for the decentralised and distributed control of interconnected systems that prohibit artificial constraints on the unmeasurable coupling vectors. A convex quadratic constraint on the current-time control vector is subsequently developed from the dissipation-based constraint and applied to the model predictive control (MPC) as an enforced attractivity constraint. The attractivity constraints for controlled subsystems can be fully decoupled in this approach. Only linear-time-invariant (LTI) interconnected systems are under the scope of this chapter.]

Published: Mar 7, 2018

There are no references for this article.