Robust control system design with proportional integral observer

Beale, S.; Shafai, B.

doi:10.1109/cdc.1988.194372

Cited by 31 publications

(32 citation statements)

References 18 publications

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“…However, it may also be considered as sensor failure signal in the context of fault analysis. The original structure of P I 0 in [7] is defined as (4) and the error dynamics would have the expression It is evident that the disturbance, v(t), is multiplied by the proportional gain Kp. Therefore, if Kp is a high gain then the disturbance will be amplified.…”

Section: Proportional Integral Observermentioning

confidence: 99%

Simultaneous disturbance attenuation and fault detection using proportional integral observers

Shafai

Nork

2002

Proceedings of the 2002 American Control Conference (IEEE Cat. No.CH37301)

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This paper considers the design of a proportional integral observer (PIO) for simultaneous disturbance attenuation and fault detection. Unlike a proportional observer, an integral observer alone suffices to achieve good convergence and filtering properties when sensor noise is present in the system. On the other hand, a proportional integral observer makes it possible to decouple the modeling uncertainties while estimating states and faults with satisfactory convergence properties. We show that a generalized P I 0 structure, a proportional integral fading observer (PIFO), facilitates the design procedure for achieving the above goal.

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Section: Proportional Integral Observermentioning

confidence: 99%

Simultaneous disturbance attenuation and fault detection using proportional integral observers

Shafai

Nork

2002

Proceedings of the 2002 American Control Conference (IEEE Cat. No.CH37301)

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“…Consider the following proportional-integral (PI) observer [24] which is a modified version of [25]:…”

Section: April 1994mentioning

confidence: 99%

Magnetic bearing control systems and adaptive forced balancing

1994

IEEE Control Syst.

125

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ctive magnetic bearing (AMB) actuators support rotors with-A0 ut friction but require feedback control for stabilization and performance. We address the application of modem control techniques such as LQGLTR, H , and Q l T to AMB systems. We also introduce a novel method called adaptiveforced balancing (AFB) which solves the problem of synchronous vibration caused by mass unbalance. Simulation and experimental results are included to show the performance of AFB as applied to single-end AMB suspensions (SISO systems). Finally, AFB with frequency tracking and its generalization for double-end AMB suspensions (MIMO systems) are briefly explored.Peter J. LaRocca received B.S. degrees in both electrical engineering and computer science from the University of Connecticut in 1984 and the S.M. degree in aeronautics and astronautics from the Massachusetts Institute of Technology, Cambridge, MA, in 1988. He joined the C.S. Draper Laboratory, Cambridge, MA, in 1984 and is currently a Senior Member of the Technical Staff. He has designed digital control systems for inertial instruments, magnetic bearing systems, and micromechanical inertial instruments. His current interests include the design and implementation of control systems and adaptive algorithms using DSP hardware. He has designed analog and digital control systems for guidance system applications for over 25 years. Currently he is involved with control system design for magnetic bearing systems and micromechanical instruments.

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“…Hence, proportional integral observer-based implementations are characterized by the following important property: Full-state feedback robustness is not fully recovered in the transient but is asymptotically obtained in the steady-state (Beale, S., and Shafai, B., 1989).…”

Section: General Designmentioning

confidence: 99%

Uncertain Models and Robust Control

Weinmann¹

1991

312

126

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PrefaceControl system analysis and design are important fields in the engineering sciences. Process identification and optimum design have developed rapidly over the past decades and resulted in great engineering progress. However, many results have suffered from considerable dependence on uncertainties, mainly incorporated in the plant, in actuators and sensors, and released by other internal disturbances.More and more, methods tackling uncertainties form a central and important issue in designing feedback control systems. Choosing appropriate design methods, the influence of uncertainties on the closed-loop behaviour can be reduced to a large extent. Control systems particularly designed to manage uncertainties are called robust control systems. Robust control theory provides a design philosophy with respect to perturbed or uncertain parts of the system. This monograph is devoted to plants and their approximate models and to the discussion of their uncertainties. The thrust of the book is on systematic representation of methods for robust control.Most of the important areas of robust control are covered. The aim is to provide an introduction to the theory and methods of robust control system design, to present a coherent body of knowledge, to clarify and unify presentation, and to streamline derivations and proofs in the field of uncertainties and robust control. The book contains a thorough treatment of important material which is scattered throughout the literature.The primary goal of the text is to present significant derivations and proofs. As far as less significant proofs or lengthy derivations are concerned, only the results are outlined and the reader is referred to the literature relevant to this subject. In a few cases, some topics are set forth only as a suggestion for further reading.Some important problems treated in this book are:• How is uncertainty described and bounded when applying methods of differential equations, transfer functions or transfer matrices, state-space algorithms or some approximating calculus?• Which uncertainty or which perturbation in some special system description forces the system to instability? This question arises both for open-loop and for closed-loop systems.• Which kind of controller is able to tolerate maximum uncertainty?2In most cases stability robustness is applied but performance robustness is also a very important subject, e.g., determining the regions in the parameter space of controllers which place all the closed-loop eigenvalues into a desired region, thus satisfying the design specifications in the face of uncertain but bounded plant parameters.The book is intended specifically for practicing but mathematically inclined engineers, for postgraduate students and engineers on master's level. Moreover, the book is intended for those readers who wish to apply robust design principles and theories to real-life applications and problems.Emphasis is put on practical considerations and on applicability at the expense of extensive proofs and mathematical rigor.The ...

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Robust control system design with proportional integral observer

Cited by 31 publications

References 18 publications

Simultaneous disturbance attenuation and fault detection using proportional integral observers

Simultaneous disturbance attenuation and fault detection using proportional integral observers

Magnetic bearing control systems and adaptive forced balancing

Uncertain Models and Robust Control

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