There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality.

Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

I and i

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Convex Analysisの二,三の進展について

We introduce flat systems, which are equivalent to linear ones via a special type of feedback called endogenous. Their physical properties are subsumed by a linearizing output and they might be regarded as providing another nonlinear extension of Kalman's controllability. The distance to flatness is measured by a non-negative integer, the defect. We utilize differential algebra where flatness- and defect are best defined without distinguishing between input, state, output and other variables. Many realistic classes of examples are flat. We treat two popular ones: the crane and the car with n trailers, the motion planning of which is obtained via elementary properties of plane curves. The three non-flat examples, the simple, double and variable length pendulums, are borrowed from non-linear physics. A high frequency control strategy is proposed such that the averaged systems become flat.

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Flatness and defect of non-linear systems: introductory theory and examples

to be done in this area. Face recognition is a problem that scarcely clamoured for attention before the computer age but, having surfaced, has involved a wide range of techniques and has attracted the attention of some fine minds (David Mumford was a Fields Medallist in 1974). This singular application of mathematical modelling to a messy applied problem of obvious utility and importance but with no unique solution is a pretty one to share with students: perhaps, returning to the source of our opening quotation, we may invert Duncan's earlier observation, 'There is an art to find the mind's construction in the face!'.

Linear and nonlinear waves, by G. B. Whitham. Pp.636. £50. 1999. ISBN 0 471 35942 4 (Wiley).

The Theory of Matrices. By F R. Gantmacher. Two volumes, pp. 374 and 276. 1959. (Translated from the Russian by K. A. Hirsch; Chelsea Publishing Company, New York)

Chapter 1. Dynamical Models of Bioreactors. Introduction. The basic dynamics of microbial growth in stirred tank reactors. Extensions to the basic dynamics. Models of the specific growth rate. The reaction scheme of a biotechnological process. General dynamical model of bioreactors. Examples of state space models. A basic structural property of the general dynamical model. Reduction of the general dynamical model. Stability analysis. Extending the general dynamical model. References and bibliography. Chapter 2. Kinetic Modelling, Estimation and Control in Bioreactors: An Overview. Introduction. Difficulties in modelling the reactor kinetics. Minimal modelling of reaction kinetics. Software sensors for bioreactors. Adaptive control of bioreactors. Conclusions and perspectives. References and bibliography. Chapter 3. State and Parameter Estimation with Known Yield coefficients. Introduction. On state observation in bioreactors. Extended Luenberger and Kalman observers. Asymptotic observers for state estimation when the reaction rates are unknown. On-line estimation of reaction rates. References and bibliography. Chapter 4. State and Parameter Estimation with unknown yield coefficients. Introduction. On-line estimation of the specific reaction rates. Joint estimation of yield coefficients and specific reaction rates. Adaptive observers. Estimation of yield coefficients. Other parameter estimation issues in bioreactors. References and bibliography. Chapter 5. Adaptive Control of Bioreactors. Introduction. Principle of linearizing control and remarks on closed loop stability. Singular perturbation design of linearizing controllers. Adaptive linearizing control (known yield coefficients). A general solution to the linearizing control problem for a class of CST bioreactors. Adaptive linearizing control (unknown yield coefficients). Practical aspects of implementation. Case study: Adaptive linearizing control of fed-batch reactors. Case study: Adaptive control of the gaseous production rate of a synthesis product. References and bibliography. Appendix 1. Models of the Specific Growth Rate. Appendix 2. Elements of Stability Theory. Appendix 3. Persistence of excitation. Convergence of Adaptive Estimators. Nomenclature. Index.

On-Line Estimation and Adaptive Control of Bioreactors

Part 1 Rigid manipulators: modelling and identification joint space control task space control motion and force control. Part 2 Flexible manipulators: elastic joints flexible links. Part 3 Mobile robots: modelling and structural properties feedback linearization nonlinear feedback control. Appendix: control background.

Theory of Robot Control

The structure of the kinematic and dynamic models of wheeled mobile robots is analyzed. It is shown that, for a large class of possible configurations, they can be classified into five types, characterized by generic structures of the model equations. For each type of model the following questions are addressed: (ir)reducibility and (non)holonomy, mobility and controllability, configuration of the motorization, and feedback equivalence.

Structural properties and classification of kinematic and dynamic models of wheeled mobile robots

An adaptive observer/identifier for single input/single output observable nonlinear systems that can be transformed to a certain observable canonical form is described. Sufficient conditions for stability of this observer are provided. These conditions are in terms of the structure of the system and canonical form, the boundedness of the parameter variations, and the sufficient richness of some signals. The scope of the canonical form and the use of the observer/identifier is motivated by the presentation of applications to time-invariant bilinear systems, nonlinear systems in phase-variable form a biotechnological process, and a robot manipulator. In each case, the specific stability conditions are presented. >

Stable adaptive observers for nonlinear time-varying systems

This monograph explores the modeling of conservation and balance laws of one-dimensional hyperbolic systems using partial differential equations. It presents typical examples of hyperbolic systems for a wide range of physical engineering applications, allowing readers to understand the concepts in whichever setting is most familiar to them. With these examples, it also illustrates how control boundary conditions may be defined for the most commonly used control devices.
The authors begin with the simple case of systems of two linear conservation laws and then consider the stability of systems under more general boundary conditions that may be differential, nonlinear, or switching. They then extend their discussion to the case of nonlinear conservation laws and demonstrate the use of Lyapunov functions in this type of analysis. Systems of balance laws are considered next, starting with the linear variety before they move on to more general cases of nonlinear ones. They go on to show how the problem of boundary stabilization of systems of two balance laws by both full-state and dynamic output feedback in observer-controller form is solved by using a “backstepping” method, in which the gains of the feedback laws are solutions of an associated system of linear hyperbolic PDEs. The final chapter presents a case study on the control of navigable rivers to emphasize the main technological features that may occur in real live applications of boundary feedback control.
Stability and Boundary Stabilization of 1-D Hyperbolic Systems will be of interest to graduate students and researchers in applied mathematics and control engineering. The wide range of applications it discusses will help it to have as broad an appeal within these groups as possible.

Georges Bastin

Papers

On-Line Estimation and Adaptive Control of Bioreactors

Theory of Robot Control

Structural properties and classification of kinematic and dynamic models of wheeled mobile robots

Stable adaptive observers for nonlinear time-varying systems

Stability and Boundary Stabilization of 1-D Hyperbolic Systems