There is an increasing demand for dynamic systems to become safer and more reliable This requirement extends beyond the normally accepted safety-critical systems such as nuclear reactors and aircraft, where safety is of paramount importance, to systems such as autonomous vehicles and process control systems where the system availability is vital It is clear that fault diagnosis is becoming an important subject in modern control theory and practice Robust Model-Based Fault Diagnosis for Dynamic Systems presents the subject of model-based fault diagnosis in a unified framework It contains many important topics and methods; however, total coverage and completeness is not the primary concern The book focuses on fundamental issues such as basic definitions, residual generation methods and the importance of robustness in model-based fault diagnosis approaches In this book, fault diagnosis concepts and methods are illustrated by either simple academic examples or practical applications The first two chapters are of tutorial value and provide a starting point for newcomers to this field The rest of the book presents the state of the art in model-based fault diagnosis by discussing many important robust approaches and their applications This will certainly appeal to experts in this field Robust Model-Based Fault Diagnosis for Dynamic Systems targets both newcomers who want to get into this subject, and experts who are concerned with fundamental issues and are also looking for inspiration for future research The book is useful for both researchers in academia and professional engineers in industry because both theory and applications are discussed Although this is a research monograph, it will be an important text for postgraduate research students world-wide The largest market, however, will be academics, libraries and practicing engineers and scientists throughout the world

Robust Model-Based Fault Diagnosis for Dynamic Systems

The use of feedback (full state, output, and constrained output) is considered as a means of shaping the transient response of linear time invariant systems. The underlying importance of the eigenstructure (eigenvalues/eigenvectors) is highlighted. Also, the important results and techniques are presented along with a brief literature review. An extensive flight control example is presented which should give direction to the application of eigenstructure assignment in diverse areas.

Eigenstructure Assignment for Linear Systems

Two new simple, complete, analytical, and restriction-free solutions with complete and explicit freedom of the matrix equation AV+BW=VF are proposed. Here (AB) is known and is controllable, and F is in the Jordan form with arbitrary given eigenvalues. Based on the proposed solutions of this matrix equation, a complete parametric approach for eigenstructure assignment in linear systems via state feedback is proposed, and two new algorithms are presented. The proposed solutions of the matrix equation and the eigenstructure assignment result are generalizations of some previous results and are simpler and more effective. >

Solutions of the equation AV+BW=VF and their application to eigenstructure assignment in linear systems

A controller design methodology to develop a robust compliant motion for robot manipulators is described. The achievement of the target dynamics (the target impedance is introduced in Part I) and preservation of stability robustness in the presence of bounded model uncertainties are the key issues in the design method. State-feedback and force-feedforward gains are chosen to guarantee the achievement of the target dynamics, while preserving stability in the presence of the model uncertainties. In general, the closed-loop behavior of a system cannot be shaped arbitrarily over an arbitrarily wide frequency range. It is proved that a special class of impedances that represent our set of performance specifications are mathematically achievable asymptotically through state-feedback and interaction-force feedforward as actuator bandwidths become large, and we offer a geometrical design method for achieving them in the presence of model uncertainties. The design method reveals a classical trade-off between a system's performance over a bounded frequency range and its stability relative to model uncertainties via multivariable Nyquits criteria. Two classes of such uncertainties are dealt with. While the first class of model uncertainties is formed from the uncertainties in the parameters of the modeled dynamics, the high-frequency unmodeled dynamics form the second class of model uncertainties. The multivariable Nyquist criterion is used to examine trade-offs in stability robustness against approximation of desired target impedances over bounded frequency ranges.

Robust compliant motion for manipulators, part II: Design method

The eigenvalue-assignment approach of Brogan [1], [2] is generalized and extended to the assignment of the entire closed-loop eigenstructure of linear multivariable systems The set of assignable eigenvectors and generalized eigenvectors emerges naturally in the solution and is given, moreover, in an explicit parametric form Two numerical examples are worked out to demonstrate the application of the procedure

http://ieeexplore.ieee.org/iel5/9/24190/01102995.pdf

J. O'Reilly

Papers

On eigenstructure assignment in linear multivariable systems