The cable-driven mechanism is usually used in robotic systems for the efficient transmission of forces or torques from actuators to the end-effector. However, the control design is challenging for these systems due to...
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This paper provides a necessary and sufficient condition for the compositional verification of a continuous system with additively separable barrier functions. The compositional safety verification enables the verific...
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ISBN:
(纸本)9781467320658
This paper provides a necessary and sufficient condition for the compositional verification of a continuous system with additively separable barrier functions. The compositional safety verification enables the verification of an inter-connection of subsystems. The idea behind the compositional analysis is to allow the verification of systems with a high dimension, by the verification of multiple lower dimensional subproblems. In the compositional safety analysis, a particular structure is imposed on the barrier certificate, restricting the applicability of the method. We show an example of a system that cannot be verified using the compositional method, but can be verified using a centralized method. This example highlights how not to decompose systems, and should be used to guide the decomposition of a system into appropriate subsystems. Finally, we provide a second condition for the compositional safety analysis that enables the verification of the counterexample, by imposing a less restrictive structure of the barrier function. This shows that the counterexample can be solved with a compositional method, but at an increased computational complexity.
Distributed generation (DG) of power has played an ever-increasing role in a smart power system, often termed as a smart grid. Their use can, however, cause more risk to the entire system since their power outputs are...
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Distributed generation (DG) of power has played an ever-increasing role in a smart power system, often termed as a smart grid. Their use can, however, cause more risk to the entire system since their power outputs are often affected by uncontrollable environments, e.g., weather. Power flow problems as a nonlinear optimization one become much more challenging when one or more distributed generators fail to achieve their desired performance levels. This work formulates a particle swarm optimization method to solve them by considering controllable and uncontrollable distributed generators in a smart grid. Such a method is often sensitive to the initialization conditions and weighting factors. This work presents several typical different initialization strategies and decides the most suitable weighting factors. They are comprehensively investigated via an IEEE 14-bus system subject to the failure of uncontrollable distributed generators.
We have previously shown that, with the help of peer-assessment and of a finite-domain constraint-based model of the student's decisions, the teacher could have a complete assessment of the answers to open-ended q...
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We have previously shown that, with the help of peer-assessment and of a finite-domain constraint-based model of the student's decisions, the teacher could have a complete assessment of the answers to open-ended questions, by grading just a subset of the answers (as low as half of the lot) and having the rest of the grading inferred by the supporting system. In this paper we present a probabilistic version of the earlier model, using Bayesian networks instead than constraints. Our aims are both defining the approach and prepare its validation: 1) modeling the peer-assessment activity of a student that evaluates others' answers, 2) using peer-assessment to help the teacher with a faster/shorter assessment process, 3) inferring the student's level of competence and ability to judge, from peer-assessment and from (partial) teacher-assessment, 4) learning the conditional probabilistic tables (CPTs) of the model from student data, and 5) comparing the probability distribution of competences in the class at different course phases. The model is under development and test with real data. We are developing a web-based interface to deliver open-answer and peer-assessment questionnaires and to assist the teacher-assessment.
Filter circuits are mainly used to constraint the signal frequency bandwidth, separate signals from disturbance frequencies, and fast sharp pulse. However, in previous studies, the problems are analyzed mostly from th...
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It is an interesting topic to study decentralized control algorithms for a group of agents to achieve a class of collective circular motion, or called torus. An algorithm was proposed in [1] where no global beacon inf...
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ISBN:
(纸本)9781467325813
It is an interesting topic to study decentralized control algorithms for a group of agents to achieve a class of collective circular motion, or called torus. An algorithm was proposed in [1] where no global beacon information is required, however, the agents are homogeneous. In particular, it was assumed that the agents have a common nominal rotation radius and share a common reference frame. In this paper, an improved algorithm is proposed on heterogeneous agents by removing the two assumptions.
In this paper, we present an approach towards autonomous grasping of objects according to their category and a given task. Recent advances in the field of object segmentation and categorization as well as task-based g...
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This paper presents a distributed event-based control approach to cope with communication delays and packet losses affecting a networked dynamical system consisting of N linear time-invariant coupled systems. Two comm...
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This paper presents a distributed event-based control approach to cope with communication delays and packet losses affecting a networked dynamical system consisting of N linear time-invariant coupled systems. Two communication protocols are proposed to deal with these communication effects. It is shown that both protocols preserve the system stability in the sense that the state of every subsystem converges to a small region around the origin if the delay and the number of packet losses are bounded. Analytical expressions for the delay bound and the maximum number of consecutive packet losses are derived. Simulations illustrate the results.
There is increasing interest in the use of Autonomous Underwater Vehicles (AUVs) to substantially improve the means available for ocean exploration and exploitation. A key element in the operation of certain classes o...
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There is increasing interest in the use of Autonomous Underwater Vehicles (AUVs) to substantially improve the means available for ocean exploration and exploitation. A key element in the operation of certain classes of AUVs is the availability of good underwater positioning systems to localize one or more vehicles simultaneously based on information received on-board a support ship or a set of autonomous surface vehicles. In an interesting operational scenario, the set of autonomous surface vehicles carries a network of acoustic units that measure the elevation and azimuth angles between the target and each of the receivers. Motivated by these considerations, in this paper we address the problem of determining the optimal geometric configuration of an acoustic sensor network at the ocean surface that will maximize the angle-related information available for underwater target positioning. It is assumed that the angle measurements are corrupted by white Gaussian noise, the variance of which is distance-dependent. Using the Cramer-Rao lower bound inequality, the trace of the inverse of the Fisher Information matrix (also called the Cramer-Rao Bound matrix) for the problem at hand is used to determine the sensor configuration that yields the minimum possible covariance of any unbiased target estimator. It is shown that the optimal configuration lends itself to an interesting geometrical interpretation and that the spreading of the sensor configuration depends explicitly on the intensity of the measurement noise and the target depth. Simulation examples illustrate the key results derived.
In this paper, we present a new idea to analyze facial expression by exploring some common and specific information among different expressions. Inspired by the observation that only a few facial parts are active in e...
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In this paper, we present a new idea to analyze facial expression by exploring some common and specific information among different expressions. Inspired by the observation that only a few facial parts are active in expression disclosure (e.g., around mouth, eye), we try to discover the common and specific patches which are important to discriminate all the expressions and only a particular expression, respectively. A two-stage multi-task sparse learning (MTSL) framework is proposed to efficiently locate those discriminative patches. In the first stage MTSL, expression recognition tasks, each of which aims to find dominant patches for each expression, are combined to located common patches. Second, two related tasks, facial expression recognition and face verification tasks, are coupled to learn specific facial patches for individual expression. Extensive experiments validate the existence and significance of common and specific patches. Utilizing these learned patches, we achieve superior performances on expression recognition compared to the state-of-the-arts.
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