Reach a nonlinear consensus for MAS via doubly stochastic quadratic operators

This technical note addresses the new nonlinear protocol class of doubly stochastic quadratic operators (DSQOs) for coordination of consensus problem in multi-agent systems (MAS). We derive the conditions for ensuring that every agent reaches consensus on a desired rate of the group’s decision where the group decision value in its agent’s initial statuses varies. Besides that, we investigate a non-linear protocol sub-class of extreme DSQO (EDSQO) to reach a consensus for MAS to a common value with nonlinear low-complexity rules and fast time convergence if the interactions for each agent are not selfish. In addition, to extend the results to reach a consensus and to avoid the selfish case we specify a general class of DSQO for reaching a consensus under any given case of initial states. The case that MAS reach a consensus by DSQO is if each member of the agent group has positive interactions of DSQO (PDSQO) with the others. The convergence of both EDSQO and PDSQO classes is found to be directed towards the centre point. Finally, experimental simulations are given to support the analysis from theoretical aspect

Fractional Order PID Controller Tuning by Frequency Loop-Shaping: Analysis and Applications

abstract: The purpose of this dissertation is to develop a design technique for fractional PID controllers to achieve a closed loop sensitivity bandwidth approximately equal to a desired bandwidth using frequency loop shaping techniques. This dissertation analyzes the effect of the order of a fractional integrator which is used as a target on loop shaping, on stability and performance robustness. A comparison between classical PID controllers and fractional PID controllers is presented. Case studies where fractional PID controllers have an advantage over classical PID controllers are discussed. A frequency-domain loop shaping algorithm is developed, extending past results from classical PID’s that have been successful in tuning controllers for a variety of practical systems.Dissertation/ThesisDoctoral Dissertation Electrical Engineering 201

An integrated control strategy to solve the disturbance decoupling problem for max-plus linear systems with applications to a high throughput screening system

International audienceThis paper presents the new investigations on the disturbance decoupling problem (DDP) for the geometric control of max-plus linear systems. The classical DDP concept in the geometric control theory means that the controlled outputs will not be changed by any disturbances. In practical manufacturing systems, solving for the DDP would require further delays on the output parts than the existing delays caused by the system breakdown. The new proposed modified disturbance decoupling problem (MDDP) in this paper ensures that the controlled output signals will not be delayed more than the existing delays caused by the disturbances in order to achieve the just-in-time optimal control. Furthermore, this paper presents the integration of output feedback and open-loop control strategies to solve for the MDDP, as well as for the DDP. If these controls can only solve for the MDDP, but not for the DDP, an evaluation principle is established to compare the distance between two output signals generated by controls solving for the MDDP and DDP, respectively. This distance can be interpreted as the number of tokens or firings that are needed in order for the controls to solve for the DDP. Moreover, another alternative approach is finding a new disturbance mapping in order to guarantee the solvability of the DDP by the same optimal control for the MDDP. The main results of this paper are illustrated by using a timed event graph model of a high throughput screening system in drug discovery.</p

An adaptive autopilot design for an uninhabited surface vehicle

An adaptive autopilot design for an uninhabited surface vehicle Andy SK Annamalai The work described herein concerns the development of an innovative approach to the design of autopilot for uninhabited surface vehicles. In order to fulfil the requirements of autonomous missions, uninhabited surface vehicles must be able to operate with a minimum of external intervention. Existing strategies are limited by their dependence on a fixed model of the vessel. Thus, any change in plant dynamics has a non-trivial, deleterious effect on performance. This thesis presents an approach based on an adaptive model predictive control that is capable of retaining full functionality even in the face of sudden changes in dynamics. In the first part of this work recent developments in the field of uninhabited surface vehicles and trends in marine control are discussed. Historical developments and different strategies for model predictive control as applicable to surface vehicles are also explored. This thesis also presents innovative work done to improve the hardware on existing Springer uninhabited surface vehicle to serve as an effective test and research platform. Advanced controllers such as a model predictive controller are reliant on the accuracy of the model to accomplish the missions successfully. Hence, different techniques to obtain the model of Springer are investigated. Data obtained from experiments at Roadford Reservoir, United Kingdom are utilised to derive a generalised model of Springer by employing an innovative hybrid modelling technique that incorporates the different forward speeds and variable payload on-board the vehicle. Waypoint line of sight guidance provides the reference trajectory essential to complete missions successfully. The performances of traditional autopilots such as proportional integral and derivative controllers when applied to Springer are analysed. Autopilots based on modern controllers such as linear quadratic Gaussian and its innovative variants are integrated with the navigation and guidance systems on-board Springer. The modified linear quadratic Gaussian is obtained by combining various state estimators based on the Interval Kalman filter and the weighted Interval Kalman filter. Change in system dynamics is a challenge faced by uninhabited surface vehicles that result in erroneous autopilot behaviour. To overcome this challenge different adaptive algorithms are analysed and an innovative, adaptive autopilot based on model predictive control is designed. The acronym ‘aMPC’ is coined to refer to adaptive model predictive control that is obtained by combining the advances made to weighted least squares during this research and is used in conjunction with model predictive control. Successful experimentation is undertaken to validate the performance and autonomous mission capabilities of the adaptive autopilot despite change in system dynamics.EPSRC (Engineering and Physical Sciences Research Council

Controle via busca extremal da produção de petróleo em poços operando com elevação artificial por injeção de gás

Este trabalho aborda a utilização de metodologias de controle via busca extremal a produção de petróleo em poços que operam por elevação artificial por injeção de gás. O objetivo é manter a produção de óleo nesses poços em torno de seu ponto ótimo em relação a Curva de Performance de Produção. É realizada uma revisão bibliográfica da literatura de engenharia de petróleo e métodos de controle ótimo. São analisados o modelo de poço utilizados nas simulações computacionais. É identificado um modelo simplificado para representar a dinâmica do poço. Descreve-se a metodologia empregada no desenvolvimento da solução de controle por busca extremal. As simulações ocorreram em uma interface entre o software de simulação dinâmica EMSO ( Emvironment for Modeling, Simulation and Optimization) e o Matlab. Finalmente, são apresentados os resultados das simulações e as conclusões sobre a importância do trabalho para a indústria de Óleo e Gás

Determinação da região robusta de estabilidade e de desempenho inspirada nos princípios da estatística clássica.

Este trabalho trata do desenvolvimento de uma metodologia baseada nos conceitos clássicos de estatística e probabilidade para a análise e avaliação da robustez da estabilidade e do desempenho de sistemas de controle, particularmente àqueles que usam o PID (Proporcional, Integral, Derivativo) como lei de controle. Visando estabelecer as condições para a aplicação da metodologia, um sistema de identificação do processo foi desenvolvido de forma recursiva, no qual modelos de convolução e fenomenológico foram empregados como representação do modelo e processo, agrupado a um procedimento de auto sintonia, necessário para considerar os parâmetros de sintonia como variáveis aleatórias e, por conseguinte as raízes da equação característica do sistema em malha fechada.O mapeamento da região de robustez tem sido realizado a partir das raízes da equação característica, considerando a distância estatística como a métrica representativa da robustez da estabilidade a qual permite estabelecer a região com certo grau de significância.Os resultados obtidos demonstram o potencial analítico exigido pela metodologia, permitindo também a análise online, com baixo esforço computacional e operacional mostrando ser um poderoso instrumento de avaliação de sistema de controle.This study discusses the development of a methodology based on classical concepts of statistics and probability to analyze and evaluate the robustness of the stability and performance of the control system, particularly those that use the PID as control law. To establish the conditions for the application of the methodology, a recursive system identification method process was developed, in which convolution and phenomenological models were used to represent model and process, together with a self-tuning procedure that is necessary to consider tuning parameters as random variables, and hence the roots of the characteristic equation of the closed loop system. The mapping of the region of robustness has been achieved from the roots of the characteristic equation, considering the statistical distance as the metric represented to the robustness of stability which allows the region to establish a degree of significance. The results obtained demonstrate the potential analytical and evaluation required by the methodology, allowing such analysis also "online" with low computational effort and operational proving to be a powerful tool in the analysis of control system

Desktop microfactory

Micro technology is continuously progressing towards smaller, smarter and reliable forms. Consequently, demand for such miniature and complex systems is arising rapidly in various fields such as industry, medicine, aerospace and automotive. Such fast development of micro technology is achieved thanks to improvements in micromanufacturing tools and techniques. Miniaturization of the machinery and manufacturing equipment is emerging to be an attractive idea that would eventually solve many of the issues existing in conventional micro-manufacturing. This work presents a modular and reconfigurable desktop microfactory for high precision assembly and machining of micro mechanical parts as proof of concept inspired by the downsizing trend of the production tools. The system is constructed based on primary functional and performance requirements such as miniature size, operation with sub-millimeter precision, modular and reconfigurable structure, parallel processing capability, ease of transportation and integration. Proposed miniature factory consists of downsized functional modules such as two parallel kinematic robots for manipulation and assembly, galvanometric laser beam scanning system for micromachining, high precision piezoelectric positioning stage, camera system for detection and inspection, and a rotational conveyor system. Each of the listed modules is designed and tested for fine precision tasks separately and results are presented. Design comprises development of mechanics, electronics and controller for the modules individually. Once stand-alone operation of each unit is achieved further assembly to a single microfactory system is considered. The overall mechanical structure of the proposed microfactory facilitates parallel processing, flexible rearrangement of the layout, and ease of assembling and disassembling capabilities. These important steps are taken to investigate possibilities of a microfactory concept for production of microsystems in near future

Commande prédictive nonlinéaire d'un système de freinage hybride électro-hydraulique régénératif

Le contexte de cette étude porte sur l’implémentation d’une stratégie de commande collaborative entre le système de freinage électro-hydraulique d’un véhicule récréatif trois-roues à propulsion électrique et son système de freinage régénératif. Grâce à l’établissement d’une méthode originale d’allocation des efforts de freinage aux roues avant / arrière, la stratégie développée permet de spécifier la consigne d’effort de freinage « idéale » à la roue arrière en fonction du freinage hydraulique à l’avant. Une commande prédictive nonlinéaire a été développée pour répartir cette consigne entre le frein électro-hydraulique et le frein régénératif en temps réel. Cette stratégie de contrôle consiste à trouver la commande optimale à appliquer sur un horizon de temps glissant à durée finie. La commande est la solution d’un problème d’optimisation sous contraintes dures, dont le processus a été implémenté en-ligne avec la prise en charge directe d’un modèle de prédiction nonlinéaire des dynamiques rapides du système de freinage hybride. L’identification paramétrique et la validation de ce modèle ont été réalisées expérimentalement sous diverses conditions. L’analyse des résultats de la commande prédictive, tirés de simulations ainsi que d’expérimentations sous forme d’essais routiers montre des résultats conformes aux comportements attendus. En effet, la stratégie permet de maximiser le couple de freinage régénératif lors d’un freinage nécessitant l’utilisation collaborative des deux systèmes de frein tout en respectant la consigne de freinage. De plus, on observe des propriétés de robustesse à l’incertitude paramétrique. Finalement, les résultats expérimentaux démontrent qu’avec la croissance de la puissance de calcul embarquée, la commande prédictive nonlinéaire devient envisageable pour de nombreuses applications temps-réel à dynamique rapide

Fault Detection and Isolation in Attitude Control Subsystem of Spacecraft Formation Flying using Extended Kalman Filters

In this thesis, the problem of fault detection and isolation in the attitude control subsystem of spacecraft formation flying is considered. For this purpose, first the attitude dynamics of a single spacecraft is analyzed and a nonlinear model is defined for our problem. This is followed up by generating the model of the spacecraft formation flight using the attitude model and controlling the formation based on virtual structure control scheme. In order to design the fault detection method, an extended Kalman filter is utilized which is a nonlinear stochastic state estimation method. Three fault detection architectures, namely, centralized, decentralized, and semi-decentralized are designed based on extended Kalman filters. Moreover, the `residual generation and threshold selection techniques are proposed for these architectures. The capabilities of the architectures for fault detection are studied through extensive numerical simulations. Using a confusion matrix evaluation system, it is shown that the centralized architecture can achieve the most reliable results relative to the semi-decentralized and decentralized architectures. Furthermore, the results confirm that the fault detection in formations with angular velocity measurements achieve higher level of accuracy, true faulty, and precision, along with lower level of false healthy misclassification as compared to the formations with only attitude measurements. In order to isolate the faults, structured residuals are designed for the decentralized, semi-decentralized, and centralized architectures. By using the confusion matrix tables, the results from each isolation technique are presented for different fault scenarios. Finally, based on the comparisons made among the architectures, it is shown that the centralized architecture has the highest accuracy in isolating the faults in the formations. Furthermore, the results confirm that fault isolation in formations with angular velocity measurements achieve higher level of accuracy when compared to formations with only attitude measurements