The Gaussian mixture MCMC particle algorithm for dynamic cluster tracking

We present a novel filtering algorithm for tracking multiple clusters of coordinated objects. Based on a Markov chain Monte Carlo (MCMC) mechanism, the new algorithm propagates a discrete approximation of the underlying filtering density. A dynamic Gaussian mixture model is utilized for representing the time-varying clustering structure. This involves point process formulations of typical behavioral moves such as birth and death of clusters as well as merging and splitting. For handling complex, possibly large scale scenarios, the sampling efficiency of the basic MCMC scheme is enhanced via the use of a Metropolis within Gibbs particle refinement step. As the proposed methodology essentially involves random set representations, a new type of estimator, termed the probability hypothesis density surface (PHDS), is derived for computing point estimates. It is further proved that this estimator is optimal in the sense of the mean relative entropy. Finally, the algorithm's performance is assessed and demonstrated in both synthetic and realistic tracking scenarios. © 2012 Elsevier Ltd. All rights reserved.

Decentralised minimum-time consensus

We consider the discrete-time dynamics of a network of agents that exchange information according to a nearest-neighbour protocol under which all agents are guaranteed to reach consensus asymptotically. We present a fully decentralised algorithm that allows any agent to compute the final consensus value of the whole network in finite time using the minimum number of successive values of its own state history. We show that the minimum number of steps is related to a Jordan block decomposition of the network dynamics, and present an algorithm to compute the final consensus value in the minimum number of steps by checking a rank condition of a Hankel matrix of local observations. Furthermore, we prove that the minimum number of steps is related to graph theoretical notions that can be directly computed from the Laplacian matrix of the graph and from the minimum external equitable partition. © 2013 Elsevier Ltd. All rights reserved.

Synchronization in networks of identical linear systems

The paper investigates the synchronization of a network of identical linear state-space models under a possibly time-varying and directed interconnection structure. The main result is the construction of a dynamic output feedback coupling that achieves synchronization if the decoupled systems have no exponentially unstable mode and if the communication graph is uniformly connected. The result can be interpreted as a generalization of classical consensus algorithms. Stronger conditions are shown to be sufficient-but to some extent, also necessary-to ensure synchronization with the diffusive static output coupling often considered in the literature. © 2009 Elsevier Ltd. All rights reserved.

Autonomous rigid body attitude synchronization

Control laws to synchronize attitudes in a swarm of fully actuated rigid bodies, in the absence of a common reference attitude or hierarchy in the swarm, are proposed in [Smith, T. R., Hanssmann, H., & Leonard, N.E. (2001). Orientation control of multiple underwater vehicles with symmetry-breaking potentials. In Proc. 40th IEEE conf. decision and control (pp. 4598-4603); Nair, S., Leonard, N. E. (2007). Stable synchronization of rigid body networks. Networks and Heterogeneous Media, 2(4), 595-624]. The present paper studies two separate extensions with the same energy shaping approach: (i) locally synchronizing the rigid bodies' attitudes, but without restricting their final motion and (ii) relaxing the communication topology from undirected, fixed and connected to directed, varying and uniformly connected. The specific strategies that must be developed for these extensions illustrate the limitations of attitude control with reduced information. © 2008 Elsevier Ltd.

Improving the performance of low-gain designs for bounded control of linear systems

An online scheduling of the parameter ensuring in addition to closed loop stability was presented. Attention was given to saturated linear low-gain control laws. Null controllability of the considered linear systems was assumed. The family of low gain control laws achieved semiglobal stabilization.

Control limitations from distributed sensing: Theory and Extremely Large Telescope application

We investigate performance bounds for feedback control of distributed plants where the controller can be centralized (i.e. it has access to measurements from the whole plant), but sensors only measure differences between neighboring subsystem outputs. Such "distributed sensing" can be a technological necessity in applications where system size exceeds accuracy requirements by many orders of magnitude. We formulate how distributed sensing generally limits feedback performance robust to measurement noise and to model uncertainty, without assuming any controller restrictions (among others, no "distributed control" restriction). A major practical consequence is the necessity to cut down integral action on some modes. We particularize the results to spatially invariant systems and finally illustrate implications of our developments for stabilizing the segmented primary mirror of the European Extremely Large Telescope. © 2013 Elsevier Ltd. All rights reserved.

Adaptive fading Kalman filter with an application

A new adaptive state estimation algorithm, namely adaptive fading Kalman filter (AFKF), is proposed to solve the divergence problem of Kalman filter. A criterion function is constructed to measure the optimality of Kalman filter. The forgetting factor in AFKF is adaptively adjusted by minimizing the defined criterion function using measured outputs. The algorithm remains convergent and tends to be optimal in the presence of model errors. It has been successfully applied to the headbox of a paper-making machine for state estimation.

Set invariance in control

The properties of positively invariant sets are involved in many different problems in control theory, such as constrained control, robustness analysis, synthesis and optimization. In this paper we provide an overview of the literature concerning positively invariant sets and their application to the analysis and synthesis of control systems.

Rendimiento potencial en trigo : identificación de atributos ecofisiológicos favorables en líneas doble haploide

La demanda mundial de trigo crece a tasas mayores que las actuales ganancias geneticas, indicando una perdida de eficiencia en el mejoramiento tradicional que utiliza como estrategia la seleccion empírica por rendimiento per se. Para complementar dicha estrategia, se ha propuesto la utilización de atributos ecofisiológicos simples ligados funcionalmente al rendimiento como criterio de seleccion indirecto. Sin embargo, el actual cuello de botella., tanto para identificar estos atributos como para comprender sus bases geneticas, es una detallada y correcta caracterización fenotípica de poblaciones de mapeo. Esta informacion, combinada con las herramientas moleculares disponibles, permitiría establecer un modelo mas completo de la relación genotipo-fenotipo y de la interacción genotipo-ambiente. En este contexto, el objetivo de la tesis fue caracterizar fenotípicamente una población de líneas doble haploide de trigo, obtenida a partir de cultivares que generan alto rendimiento potencial a traves de una combinación diferente de número y peso de grano, e identificar atributos ecofisiológicos ligados funcionalmente con el rendimiento. La población utilizada se evaluó en dos ambientes contrastantes bajo condiciones potenciales de campo, donde se uniformó el tiempo a floración y la altura de planta, a fin de evitar las posibles confusiones en la identificacion de otros atributos claves asociados al rendimiento. Las variaciones en rendimiento fueron explicadas principalmente por cambios en la biomasa acumulada durante todo el ciclo (r2 menor a 0.80 en cada ambiente), producto de diferencias en la eficiencia en el uso de la radiacion (EUR), manteniendose el indice de cosecha relativamente contante. El número de granos por unidad de superficie, que tendió a asociarse mejor con el coeficiente de fertilidad de espiga (CFE) que con el peso seco de espigas a floración, fue el principal componente del rendimiento. Mejoras en la EUR durante el período de crecimiento de la espiga (produciría espigas más pesadas) y un mayor CFE (no asociado a reducciones en el peso potencial de grano) serían dos atributos clave para incrementar el rendimiento potencial en trigo