Model predictive control and stabilisation of interconnected systems

Tran, TC

Model predictive control and stabilisation of interconnected systems

Tran, TC

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Publication Type:: Thesis
Issue Date:: 2011

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Field	Value	Language
dc.contributor.author	Tran, TC
dc.date.accessioned	2012-10-05T03:45:36Z
dc.date.accessioned	2012-12-15T03:53:49Z
dc.date.available	2012-10-05T03:45:36Z
dc.date.available	2012-12-15T03:53:49Z
dc.date.issued	2011
dc.identifier.uri	http://hdl.handle.net/10453/20431
dc.description	University of Technology, Sydney. Faculty of Engineering and Information Technology.
dc.description.abstract	The attraction of having higher efficiency and quality, as well as increasing reliability and flexibility for industrial plants and network systems has created opportunities for new research in the control and optimisation fields. Among various design methods, model predictive control (MPC) strategies have proved to be effective in industrial applications. Whilst found widespread used with stand-alone controllers in the refining and many other industries, the field of orchestrating non-centralised MPCs and distributed MPCs is evaluated as still in its infancy. The work in this thesis is concerned with stabilising methods for the control of complex interconnected systems with mixed connection configurations employing distributed and decentralised model predictive control schemes. Inheriting the advantage of the MPC strategy, the control and state constraints are naturally dealt with by the employed methods. As a result, the novel concept of asymptotically positive realness constraint (APRC) and the segregation and integration constructive methods for the constrained stabilisation of interconnected systems are introduced and developed. The MPC is formulated with state space models and stabilising constraints within the open-loop paradigm in this thesis. By having the control inputs entirely decoupled between subsystems and no additional constraints imposed on the interactive variables rather than the coupling constraint itself, the proposed approaches outreach various types of systems and applications. For parallel connections that emulate parallel redundant structures and have unknown splitting ratios, a fully decentralised control strategy is developed as an alternative to the hybrid approaches. For the semi-automatic control systems, which is involved with both closed-loop and humanin- the-loop regulatory controls, the stability-guaranteed method of decentralised stabilising agents which are interoperable with different control algorithms is germinated and implemented for each single subsystem.	en_US
dc.format	Thesis (PhD)	en_US
dc.language.iso	en	en_US
dc.relation	https://opus.lib.uts.edu.au/bitstream/10453/20431/2/02Whole.pdf
dc.relation.replaces	http://hdl.handle.net/2100/1384
dc.rights	au.edu.uts.lib/ppc
dc.rights	The author owns the copyright in this thesis including all reproduction and reuse rights for the work. The work may not be altered without the permission of the copyright owner. Attribution is essential when quoting or paraphrasing from this thesis.
dc.rights	info:eu-repo/semantics/openAccess
dc.subject	Model predictive control.	en
dc.subject	Large scale systems.	en
dc.subject	Stability.	en
dc.subject	Constraints.	en
dc.title	Model predictive control and stabilisation of interconnected systems	en_US
dc.type	Thesis
utslib.copyright.status	open_access

Abstract:

The attraction of having higher efficiency and quality, as well as increasing reliability and flexibility for industrial plants and network systems has created opportunities for new research in the control and optimisation fields. Among various design methods, model predictive control (MPC) strategies have proved to be effective in industrial applications. Whilst found widespread used with stand-alone controllers in the refining and many other industries, the field of orchestrating non-centralised MPCs and distributed MPCs is evaluated as still in its infancy. The work in this thesis is concerned with stabilising methods for the control of complex interconnected systems with mixed connection configurations employing distributed and decentralised model predictive control schemes. Inheriting the advantage of the MPC strategy, the control and state constraints are naturally dealt with by the employed methods. As a result, the novel concept of asymptotically positive realness constraint (APRC) and the segregation and integration constructive methods for the constrained stabilisation of interconnected systems are introduced and developed. The MPC is formulated with state space models and stabilising constraints within the open-loop paradigm in this thesis. By having the control inputs entirely decoupled between subsystems and no additional constraints imposed on the interactive variables rather than the coupling constraint itself, the proposed approaches outreach various types of systems and applications. For parallel connections that emulate parallel redundant structures and have unknown splitting ratios, a fully decentralised control strategy is developed as an alternative to the hybrid approaches. For the semi-automatic control systems, which is involved with both closed-loop and humanin- the-loop regulatory controls, the stability-guaranteed method of decentralised stabilising agents which are interoperable with different control algorithms is germinated and implemented for each single subsystem.

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http://hdl.handle.net/10453/20431