MIMO floor vibration controller design

The MIMO controller proposed in the paper simultaneously determines optimal placements for multiple actuators, sensors and appropriate output feedback gains. The controller design is carried out in the digital domain hence typically lower sampling rates can be used at the implementation stage. A method of exponentially penalizing the persistent states of the system is used to obtain faster settling times in the presence of external disturbances. The nonlinearities associated with actuator saturation due to force/stroke limitation is considered explicitly in the optimization. The algorithm does not require closed form expressions for modal shapes. Hence it is applicable to a wider class of 2D structures that do not readily fall into any regular geometric shape

Resource management of task oriented distributed sensor networks

In this paper we provide a foundation for a unified analysis of both the decision fusion and congestion avoidance aspects of a task-oriented distributed sensor network (DSN). Such a framework allows network resource management to be carried out in a manner that is sensitive to the overall objectives of the DSN rather than decoupling them via perhaps simple fairness strategies. The proposed approach associates importance measures related to the degradation and relevance of incoming data lines at each network node. These are then used to carry out intelligent resource management and avoid congestion in a manner which is implicitly related to the decision objectives of the DSN and explicitly related to the resource availability. To achieve this, we propose a 'per-flow' technique that decouples data flow among nodes at different hierarchical levels of the DSN. The resulting framework allows seamless integration of the importance measures providing resource management decisions that are sensitive to the overall DSN objectives

An exhaustive search algorithm for checking limit cycle behavior of digital filters

In this paper, an algorithm that can be utilized to determine the presence or absence of limit cycles in fixed-point implementation of digital filters is given. It is applicable for filters in state-space formulation (and hence, application to the corresponding direct form follows as a special case), and is independent of the order, type of quantization, and whether the accumulator is single- or double-length. Bounds on the amplitude and period of possible limit cycles are presented. The robustness of the algorithm in terms of limit cycle performance with respect to filter coefficient perturbations is verified. The algorithm is then used to obtain regions in the coefficient space where a filter of given order is limit cycle free. In this process, we have obtained limit cycle free regions that were previously unknown for the two's complement case

Conditioning and updating evidence

A new interpretation of Dempster–Shafer conditional notions based directly upon the mass assignments is provided. The masses of those propositions that may imply the complement of the conditioning proposition are shown to be completely annulled by the conditioning operation; conditioning may then be construed as a re-distribution of the masses of some of these propositions to those that definitely imply the conditioning proposition. A complete characterization of the propositions whose masses are annulled without re-distribution, annulled with re-distribution and enhanced by the re-distribution of masses is provided. A new evidence updating strategy that is composed of a linear combination of the available evidence and the conditional evidence is also proposed. It enables one to account for the ‘integrity’ and ‘inertia’ of the available evidence and its ‘flexibility’ to updating by appropriate selection of the linear combination weights. Several such strategies, including one that has a probabilistic interpretation, are also provided

Modelling and Fusion of Imperfect Implication Rules

In this paper, we develop a method to find the uncertain consequent by fusing the uncertain antecedent and the uncertain implication rule. In particular with Dempster-Shafer theoretic models utilized to capture the uncertainty intervals associated with the antecedent and the rule itself, we derive bounds on the confidence interval associated with the rule consequent. We derive inequalities for the belief and plausibility values of the consequent and with least commitment choice they become equations. We also demonstrate the consistency of our model with probability and classical logic