A method is presented for augmenting an extended Kalman filter with an adaptive element. The resulting estimator provides robustness to parameter uncertainty and unmodeled Dynamics.
標簽： augmenting presented adaptive extended
上傳時間： 2014-01-05
上傳用戶：qq1604324866
Robotics TOOLBOX The Toolbox provides many functions that are useful in robotics including such things as kinematics, Dynamics, and trajectory generation. The Toolbox is useful for simulation as well as analyzing results from experiments with real robots. Have fun with the toolbox. It is self-explanatory and very (robotics) user friendly...see the robot.pdf
標簽： functions including Robotics provides
上傳時間： 2014-12-06
上傳用戶：yyyyyyyyyy
Detecting Network Intrusions via Sampling_A Game Theoretic Approach Internet Quarantine_Requirements for Containing Self-Propagating Code Modeling Malware Spreading Dynamics Modeling the Spread of Active Worms
標簽： Quarantine_Requireme Intrusions Sampling_A Detecting
上傳時間： 2013-11-30
上傳用戶：xc216
The Robotics Toolbox provides many functions that are useful in robotics such as kinematics, Dynamics, and trajectory generation. The Toolbox is useful for simulation as well as analyzing results from experiments with real robots.
標簽： kinematics functions Robotics provides
上傳時間： 2013-12-17
上傳用戶：cx111111
Isisns is an extension of Network Simulator (ns) for the IS-IS routing protocol. It is focused on simulation of network Dynamics and convergence.
標簽： Simulator extension protocol Network
上傳時間： 2016-11-06
上傳用戶：thesk123
The design is transformed into a wiener filtering problem and the parameters are modeled as correlated ARIMA processes with known Dynamics.
標簽： transformed parameters filtering correlat
上傳時間： 2014-12-06
上傳用戶：ardager
Robot tool box - provides many functions that are useful in robotics including such things as kinematics, Dynamics, and trajectory generation
標簽： functions including provides robotics
上傳時間： 2014-11-27
上傳用戶：dongqiangqiang
Abstract—Stable direct and indirect decentralized adaptive radial basis neural network controllers are presented for a class of interconnected nonlinear systems. The feedback and adaptation mechanisms for each subsystem depend only upon local measurements to provide asymptotic tracking of a reference trajectory. Due to the functional approximation capabilities of radial basis neural networks, the Dynamics for each subsystem are not required to be linear in a set of unknown coeffi cients as is typically required in decentralized adaptive schemes. In addition, each subsystem is able to adaptively compensate for disturbances and interconnections with unknown bounds.
標簽： decentralized controllers Abstract adaptive
上傳時間： 2017-08-17
上傳用戶：gdgzhym
Computational models are commonly used in engineering design and scientific discovery activities for simulating complex physical systems in disciplines such as fluid mechanics, structural Dynamics, heat transfer, nonlinear structural mechanics, shock physics, and many others. These simulators can be an enormous aid to engineers who want to develop an understanding and/or predictive capability for complex behaviors typically observed in the corresponding physical systems. Simulators often serve as virtual prototypes, where a set of predefined system parameters, such as size or location dimensions and material properties, are adjusted to improve the performance of a system, as defined by one or more system performance objectives. Such optimization or tuning of the virtual prototype requires executing the simulator, evaluating performance objective(s), and adjusting the system parameters in an iterative, automated, and directed way. System performance objectives can be formulated, for example, to minimize weight, cost, or defects; to limit a critical temperature, stress, or vibration response; or to maximize performance, reliability, throughput, agility, or design robustness. In addition, one would often like to design computer experiments, run parameter studies, or perform uncertainty quantification (UQ). These approaches reveal how system performance changes as a design or uncertain input variable changes. Sampling methods are often used in uncertainty quantification to calculate a distribution on system performance measures, and to understand which uncertain inputs contribute most to the variance of the outputs. A primary goal for Dakota development is to provide engineers and other disciplinary scientists with a systematic and rapid means to obtain improved or optimal designs or understand sensitivity or uncertainty using simulationbased models. These capabilities generally lead to improved designs and system performance in earlier design stages, alleviating dependence on physical prototypes and testing, shortening design cycles, and reducing product development costs. In addition to providing this practical environment for answering system performance questions, the Dakota toolkit provides an extensible platform for the research and rapid prototyping of customized methods and meta-algorithms
標簽： Optimization and Uncertainty Quantification
上傳時間： 2016-04-08
上傳用戶：huhu123456
Characterizing the Dynamics underlying global spread of epidemics
標簽： Characterizing underlying epidemics Dynamics global spread the of
上傳時間： 2019-04-18
上傳用戶：glstone
