Passification-based decentralized adaptive synchronization of dynamical networks with time-varying delays

This paper is aimed at application of the passification based adaptive control to decentralized synchronization of dynamical networks. We consider Lurie type systems with hyper-minimum-phase linear parts and two types of nonlinearities: Lipschitz and matched. The network is assumed to have both instant and delayed time-varying interconnections. Agent model may also include delays. Based on the speed-gradient method decentralized adaptive controllers are derived, i.e. each controller measures only the output of the node it controls. Synchronization conditions for disturbance free networks and ultimate boundedness conditions for networks with disturbances are formulated. The proofs are based on Passification lemma in combination with Lyapunov–Krasovskii functionals technique. Numerical examples for the networks of 4 and 100 interconnected Chua systems are presented to demonstrate the efficiency of the proposed approach

Historical overview of the passification method and its applications to nonlinear and adaptive control problems

The present survey paper provides a historical overview of the method of passification and its applications to nonlinear and adaptive control problems from 1980 to present days

Assessment Study of the State of the Art in Adaptive Control and its Applications to Aircraft Control

Many papers relevant to reconfigurable flight control have appeared over the past fifteen years. In general these have consisted of theoretical issues, simulation experiments, and in some cases, actual flight tests. Results indicate that reconfiguration of flight controls is certainly feasible for a wide class of failures. However many of the proposed procedures although quite attractive, need further analytical and experimental studies for meaningful validation. Many procedures assume the availability of failure detection and identification logic that will supply adequately fast, the dynamics corresponding to the failed aircraft. This in general implies that the failure detection and fault identification logic must have access to all possible anticipated faults and the corresponding dynamical equations of motion. Unless some sort of explicit on line parameter identification is included, the computational demands could possibly be too excessive. This suggests the need for some form of adaptive control, either by itself as the prime procedure for control reconfiguration or in conjunction with the failure detection logic. If explicit or indirect adaptive control is used, then it is important that the identified models be such that the corresponding computed controls deliver adequate performance to the actual aircraft. Unknown changes in trim should be modelled, and parameter identification needs to be adequately insensitive to noise and at the same time capable of tracking abrupt changes. If however, both failure detection and system parameter identification turn out to be too time consuming in an emergency situation, then the concepts of direct adaptive control should be considered. If direct model reference adaptive control is to be used (on a linear model) with stability assurances, then a positive real or passivity condition needs to be satisfied for all possible configurations. This condition is often satisfied with a feedforward compensator around the plant. This compensator must be robustly designed such that the compensated plant satisfies the required positive real conditions over all expected parameter values. Furthermore, with the feedforward only around the plant, a nonzero (but bounded error) will exist in steady state between the plant and model outputs. This error can be removed by placing the compensator also in the reference model. Design of such a compensator should not be too difficult a problem since for flight control it is generally possible to feedback all the system states

Commande variant dans le temps pour le contrôle d'attitude de satellites

Cette thèse porte sur la commande variant dans le temps avec comme fil directeur l application au contrôle d attitude de satellites. Nous avons étudié trois types de commande: une commande à commutation, une commande LPV et une commande adaptative directe. Pour cette dernière nous avons proposé des résultats théoriques nouveaux portant sur la structuration du gain et de l adaptation. Les résultats ont été validés en simulation et sont testés à bord d un satellite. En partant de la loi à commutation actuellement utilisée sur les satellites Myriade, une première partie de nos travaux est dédiée à la commande LPV. Notre approche, basée sur la spécification des objectifs de commande à travers un modèle de référence LPV, permet d'obtenir de nouveaux algorithmes exprimés dans ce formalisme. Testées en simulation, ces lois de commande répondent à la problématique de notre application. Toutefois, le choix du modèle de référence LPV s'avère délicat. Cette difficulté a été levée en utilisant la commande adaptative. Dans cette approche, les spécifications sur le comportement temps-variant sont traduites par des contraintes au niveau des lois d'adaptation des gains de commande. Nous introduisons ainsi une nouvelle méthode de synthèse de lois adaptatives structurées. Les preuves de stabilité établies s'appuient sur des outils de la théorie de Lyapunov. Les résultats obtenus sur un simulateur complet montrent l'intérêt de tels algorithmes adaptatifs. Ils permettent en particulier de modifier la dynamique du satellite selon les capacités disponibles des actionneurs. Sur la base de ces résultats, une campagne d essai en vol sur le satellite PICARD est actuellement en cours.This manuscript considers time varying control, with a strong emphasis on a satellite attitude control application. Three types of control structures have been studied: a switch-based approach, LPV control and direct adaptive control. In this last field we have introduced new theoretical results which allow structuring the gain and the adaptation law. The results have been validated in simulation and are currently tested on board a satellite. Starting from the switch-based control law currently implemented on the Myriade satellites, a first part of our work isdedicated to LPV control. Based on the specification of the control objectives by using of an LPV reference model, our approach allows obtaining new control algorithms expressed within this framework. The simulations carried out with theLPV algorithms obtained by using this method show that they meet the needs of our application. Nonetheless, the choice of a reference model proves to be difficult. This obstacle has been surpassed by using direct adaptive control. In this approach, specifications regarding the timevarying behaviour are added through constraints on the laws defining the control gains adaptation. We thus introduce anew synthesis method, based on which structured adaptive control laws are obtained. Stability proofs are established based on tools of the Lyapunov theory.The results obtained on a complete simulator show the interest of using such adaptive algorithms, which allow in particular to modify the satellite dynamics depending on the available capacity of the actuators. Based on these positive results, a fight-test campaign on the PICARD satellite is underway.TOULOUSE-ISAE (315552318) / SudocSudocFranceF

Output Feedback Adaptive Control of Non-Minimum Phase Systems Using Optimal Control Modification

This paper describes output feedback adaptive control approaches for non-minimum phase SISO systems with relative degree 1 and non-strictly positive real (SPR) MIMO systems with uniform relative degree 1 using the optimal control modification method. It is well-known that the standard model-reference adaptive control (MRAC) cannot be used to control non-SPR plants to track an ideal SPR reference model. Due to the ideal property of asymptotic tracking, MRAC attempts an unstable pole-zero cancellation which results in unbounded signals for non-minimum phase SISO systems. The optimal control modification can be used to prevent the unstable pole-zero cancellation which results in a stable adaptation of non-minimum phase SISO systems. However, the tracking performance using this approach could suffer if the unstable zero is located far away from the imaginary axis. The tracking performance can be recovered by using an observer-based output feedback adaptive control approach which uses a Luenberger observer design to estimate the state information of the plant. Instead of explicitly specifying an ideal SPR reference model, the reference model is established from the linear quadratic optimal control to account for the non-minimum phase behavior of the plant. With this non-minimum phase reference model, the observer-based output feedback adaptive control can maintain stability as well as tracking performance. However, in the presence of the mismatch between the SPR reference model and the non-minimum phase plant, the standard MRAC results in unbounded signals, whereas a stable adaptation can be achieved with the optimal control modification. An application of output feedback adaptive control for a flexible wing aircraft illustrates the approaches

Experimental Nonlinear Control for Flutter Suppression in a Nonlinear Aeroelastic System

Experimental implementation of input–output feedback linearization in controlling the dynamics of a nonlinear pitch–plunge aeroelastic system is presented. The control objective is to linearize the system dynamics and assign the poles of the pitch mode of the resulting linear system. The implementation 1) addresses experimentally the general case where feedback linearization-based control is applied using as the output a degree of freedom other than that where the physical nonlinearity is located, using a single trailing-edge control surface, to stabilize the entire system; 2) includes the unsteady effects of the airfoil’s aerodynamic behavior; 3) includes the embedding of a tuned numerical model of the aeroelastic system into the control scheme in real time; and 4) uses pole placement as the linear control objective, providing the user with flexibility in determining the nature of the controlled response. When implemented experimentally, the controller is capable of not only delaying the onset of limit-cycle oscillation but also successfully eliminating a previously established limit-cycle oscillation. The assignment of higher levels of damping results in notable reductions in limit-cycle oscillation decay times in the closed-loop response, indicating good controllability of the aeroelastic system and effectiveness of the pole-placement objective. The closed-loop response is further improved by incorporating adaptation so that assumed system parameters are updated with time. The use of an optimum adaptation parameter results in reduced response decay times

Design of feedforward and feedback position control for passive bilateral teleoperation with delays

Bilateral teleoperation systems connected to computer networks such as the internet must be able to operate with varying time delays since such systems can easily become unstable. A passivity concept has been used as the framework to solve the stability problem in the bilateral control of teleoperation systems. Passivity and tracking performance are recovered using a control architecture that incorporates time varying gains into the transmission path, feedforward, and feedback position control. The proposed architecture has an inner component that can accommodate any configuration but still remain stable and passive even with varying time delay. The simulation results for a single degree of freedom master/slave system demonstrate the performance of the proposed control architecture

Adaptive Control

Adaptive control has been a remarkable field for industrial and academic research since 1950s. Since more and more adaptive algorithms are applied in various control applications, it is becoming very important for practical implementation. As it can be confirmed from the increasing number of conferences and journals on adaptive control topics, it is certain that the adaptive control is a significant guidance for technology development.The authors the chapters in this book are professionals in their areas and their recent research results are presented in this book which will also provide new ideas for improved performance of various control application problems

Identificacion y control de sistemas estocasticos con observaciones incompletas mediante modelos neurodifusos

En la práctica, los sistemas físicos obedecen a una dinámica multivariada e interactuante, que fácilmente es influenciada, perturbada o integrada por incertidumbres de diversas clases, las cuales inducen naturaleza estocástica al proceso global y algunas veces llegan a afectar la completitud de los datos. En esta tesis se presenta una metodología para la identificación y control de sistemas estocásticos con observaciones incompletas mediante modelos neuro-difusos. En particular, se desarrolla el análisis de la dinámica de un vehículo operado remotamente (ROV, Remotely Operated Vehicle) para aplicaciones submarinas, con el fin de determinar el modelo matemático y obtener simulaciones de la respuesta natural del sistema. Adicionalmente, se emplea un mecanismo de identificación del proceso mediante un modelo neuronal y otro neuro-difuso, los cuales se integran con un esquema de reducción de perturbaciones estocásticas para sobreponer las observaciones incompletas que residan en el proceso operativo. Finalmente, se propone un modelo neuro-difuso (ANFIS, Adaptive neuro fuzzy inference system) para controlar el sistema y se compara con el desempeño de una red neuronal con múltiples elementos Adaline (MADALINE, Multiple Adaline) con el fin de analizar las ventajas que ofrece la inclusión de conocimiento mediante reglas de inferencia difusa. Los resultados experimentales mostraron que se logró la controlabilidad del sistema llevándolo a un estado globalmente atractivo en el sentido de Lyapunov. Se pudo concluir que gracias a la capacidad de adaptación y contenencia de conocimiento lingüístico de los modelos neuro-difusos, el desempeño de control tuvo mayor rendimiento en términos de precisión y robustez, al compararlo con el modelo neuronal en aplicaciones operativas del ROV. Se destaca además la facilidad que tienen los modelos neuro-difusos para ser ampliamente potenciados mediante la integración de otros esquemas de procesamiento, dados los asuntos que quedaron pendientes en relación al error de estado estable y las perturbaciones ocasionadas por la interacción de los componentes.Magister en Automatización y Contro