Hybrid Systems and Control With Fractional Dynamics (II): Control

No mixed research of hybrid and fractional-order systems into a cohesive and multifaceted whole can be found in the literature. This paper focuses on such a synergistic approach of the theories of both branches, which is believed to give additional flexibility and help the system designer. It is part II of two companion papers and focuses on fractional-order hybrid control. Specifically, two types of such techniques are reviewed, including robust control of switching systems and different strategies of reset control. Simulations and experimental results are given to show the effectiveness of the proposed strategies. Part I will introduce the fundamentals of fractional-order hybrid systems, in particular, modelling and stability of two kinds of such systems, i.e., fractional-order switching and reset control systems.Comment: 2014 International Conference on Fractional Differentiation and its Application, Ital

What can systems and control theory do for agricultural science?

Abstract: While many professionals with a background in agricultural and bio-resource sciences work with models, only few have been exposed to systems and control theory. The purpose of this paper is to elucidate a selection of methods from systems theory that can be beneficial to quantitative agricultural science. The state space representation of a dynamical system is the corner stone in the mainstream of systems theory. It is not well known in agro-modelling that linearization followed by evaluation of eigenvalues and eigenvectors of the system matrix is useful to obtain dominant time constants and dominant directions in state space, and offers opportunities for science-based model reduction. The continuous state space description is also useful in deriving truly equivalent discrete time models, and clearly shows that parameters obtained with discrete models must be interpreted with care when transferred to another model code environment. Sensitivity analysis of dynamic models reveals that sensitivity is time and input dependent. Identifiability and sensitivity are essential notions in the design of informative experiments, and the idea of persistent excitation, leading to dynamic experiments rather than the usual static experiments can be very beneficial. A special branch of systems theory is control theory. Obviously, control plays an important part in agricultural and bio-systems engineering, but it is argued that also agronomists can profit from notions from the world of control, even if practical control options are restricted to alleviating growth limiting conditions, rather than true crop control. The most important is the idea of reducing uncertainty via feed-back. On the other hand, the systems and control community is challenged to do more to address the problems of real life, such as spatial variability, measurement delays, lacking data, environmental stochasticity, parameter variability, unavoidable model uncertainty, discrete phenomena, variable system structures, the interaction of technical ad living systems, and, indeed, the study of the functioning of life itself

Fuzzy logic applications to expert systems and control

A considerable amount of work on the development of fuzzy logic algorithms and application to space related control problems has been done at the Johnson Space Center (JSC) over the past few years. Particularly, guidance control systems for space vehicles during proximity operations, learning systems utilizing neural networks, control of data processing during rendezvous navigation, collision avoidance algorithms, camera tracking controllers, and tether controllers have been developed utilizing fuzzy logic technology. Several other areas in which fuzzy sets and related concepts are being considered at JSC are diagnostic systems, control of robot arms, pattern recognition, and image processing. It has become evident, based on the commercial applications of fuzzy technology in Japan and China during the last few years, that this technology should be exploited by the government as well as private industry for energy savings

Hybrid Systems and Control With Fractional Dynamics (I): Modeling and Analysis

No mixed research of hybrid and fractional-order systems into a cohesive and multifaceted whole can be found in the literature. This paper focuses on such a synergistic approach of the theories of both branches, which is believed to give additional flexibility and help to the system designer. It is part I of two companion papers and introduces the fundamentals of fractional-order hybrid systems, in particular, modeling and stability analysis of two kinds of such systems, i.e., fractional-order switching and reset control systems. Some examples are given to illustrate the applicability and effectiveness of the developed theory. Part II will focus on fractional-order hybrid control.Comment: 2014 International Conference on Fractional Differentiation and its Application, Ital

Quantum systems and control 1

http://www-direction.inria.fr/international/arima/009/00920.htmlInternational audienceThis paper describes several methods used by physicists for manipulations of quantum states. For each method, we explain the model, the various time-scales, the performed approximations and we propose an interpretation in terms of control theory. These various interpretations underlie open questions on controllability, feedback and estimations. For 2-level systems we consider: the Rabi oscillations in connection with averaging; the Bloch-Siegert corrections associated to the second order terms; controllability versus parametric robustness of open-loop control and an interesting controllability problem in infinite dimension with continuous spectra. For 3-level systems we consider: Raman pulses and the second order terms. For spin/spring systems we consider: composite systems made of 2-level sub-systems coupled to quantized harmonic oscillators; multi-frequency averaging in infinite dimension; controllability of 1D partial differential equation of Shrödinger type and affine versus the control; motion planning for quantum gates. For open quantum systems subject to decoherence with continuous measures we consider: quantum trajectories and jump processes for a 2-level system; Lindblad-Kossakovsky equation and their controllability.Ce papier décrit plusieurs méthodes utilisées par les physiciens pour la manipulation d’états quantiques. Pour chaque méthode, nous expliquons la modélisation, les diverses échelles de temps, les approximations faites et nous proposons une interprétation en termes de contrôle. Ces diverses interprétations servent de base à la formulation de questions ouvertes sur la commandabilité et aussi sur le feedback et l’estimation, renouvelant un peu certaines questions de base en théorie des systèmes non-linéaires. Pour les systèmes à deux niveaux, dits aussi de spin 1/2, il s’agit: des oscillations de Rabi et d’une approximation au premier ordre de la théorie des perturbations (transition à un photon); des corrections de Bloch-Siegert et d’approximation au second ordre; de commandabilité et de robustesse paramétrique pour des contrôles en boucle ouverte, robustesse liée à des questions largement ouvertes sur la commandabilité en dimension infinie où le spectre est continu. Pour les systèmes à trois niveaux, il s’agit: de pulses Raman; d’approximations au second ordre. Pour les systèmes spin/ressort, il s’agit: des systèmes composés de sous-systèmes à deux niveaux couplés à des oscillateurs harmoniques quantifiés; de théorie des perturbations à plusieurs fréquences en dimension infinie; de commandabilité d’équations aux dérivées partielles de type Schrödinger sur R et affine en contrôle; de planification de trajectoires pour la synthèse portes logiques quantiques. Pour les systèmes ouverts soumis à la décohérence avec des mesures en continu, il s’agit: de trajectoires quantiques de Monte-Carlo et de processus à sauts sur un systèmes à deux niveaux; des équations de Lindblad-Kossakovsky avec leur commandabilité