Nondeterministic hybrid dynamical systems

Schinkel, Michael (2002) Nondeterministic hybrid dynamical systems. PhD thesis, University of Glasgow.

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Printed Thesis Information: https://eleanor.lib.gla.ac.uk/record=b2108723

Abstract

This thesis is concerned with the analysis, control and identification of hybrid dynamical systems. The main focus is on a particular class of hybrid systems consisting of linear subsystems. The discrete dynamic, i.e., the change between subsystems, is unknown or nondeterministic and cannot be influenced, i.e. controlled, directly. However changes in the discrete dynamic can be detected immediately, such that the current dynamic (subsystem) is known.

In order to motivate the study of hybrid systems and show the merits of hybrid control theory, an example is given. It is shown that real world systems like Anti Locking Brakes (ABS) are naturally modelled by such a class of linear hybrids systems. It is shown that purely continuous feedback is not suitable since it cannot achieve maximum braking performance. A hybrid control strategy, which overcomes this problem, is presented.

For this class of linear hybrid system with unknown discrete dynamic, a framework for robust control is established. The analysis methodology developed gives a robustness radius such that the stability under parameter variations can be analysed. The controller synthesis procedure is illustrated in a practical example where the control for an active suspension of a car is designed.

Optimal control for this class of hybrid system is introduced. It is shows how a control law is obtained which minimises a quadratic performance index. The synthesis procedure is stated in terms of a convex optimisation problem using linear matrix inequalities (LMI). The solution of the LMI not only returns the controller but also the performance bound.

Since the proposed controller structures require knowledge of the continuous state, an observer design is proposed. It is shown that the estimation error converges quadratically while minimising the covariance of the estimation error. This is similar to the Kalman filter for discrete or continuous time systems. Further, we show that the synthesis of the observer can be cast into an LMI, which conveniently solves the synthesis problem.

Item Type: Thesis (PhD)
Qualification Level: Doctoral
Subjects: T Technology > TJ Mechanical engineering and machinery
Colleges/Schools: College of Science and Engineering > School of Engineering
Supervisor's Name: Hunt, Prof. Ken.
Date of Award: 2002
Depositing User: Elaine Ballantyne
Unique ID: glathesis:2002-1853
Copyright: Copyright of this thesis is held by the author.
Date Deposited: 26 May 2010
Last Modified: 10 Dec 2012 13:47
URI: https://theses.gla.ac.uk/id/eprint/1853

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