scholarly journals Behavior-Based High Level Control of a VTOL UAV

2009 ◽  
Author(s):  
Florian Adolf ◽  
Maurício Moraes Carneiro
Keyword(s):  
Level Control ◽  
Vtol Uav ◽  
Behavior Based ◽  
High Level

scholarly journals Robust Tracking Controller for a DC/DC Buck-Boost Converter–Inverter–DC Motor System

Energies ◽  
2018 ◽  
Vol 11 (10) ◽  
pp. 2500 ◽  
Author(s):  
Eduardo Hernández-Márquez ◽  
Carlos Avila-Rea ◽  
José García-Sánchez ◽  
Ramón Silva-Ortigoza ◽  
Gilberto Silva-Ortigoza ◽  
...  
Keyword(s):  
Motor System ◽  
Dc Motor ◽  
Boost Converter ◽  
Differential Flatness ◽  
Robust Tracking ◽  
Level Control ◽  
Tracking Controller ◽  
The One ◽  
High Level ◽  
Better Than

This paper has two aims. The first is to develop a robust hierarchical tracking controller for the DC/DC Buck-Boost–inverter–DC motor system. This controller considers a high level control for the inverter–DC motor subsystems and a low level control for the DC/DC Buck-Boost converter subsystem. Such controls solve the tracking task associated with the angular velocity of the motor shaft and the output voltage of the converter, respectively, via the differential flatness approach. The second aim is to present a comparison of the robust hierarchical controller to a passive controller. This, with the purpose of showing that performance achieved with the hierarchical controller proposed in this paper, is better than the one achieved with the passive controller. Both controllers are experimentally implemented on a prototype of the DC/DC Buck-Boost–inverter–DC motor system by using Matlab-Simulink along with the DS1104 board from dSPACE. According to experimental results, the proposal in the present paper achieves a better performance than the passive controller.

scholarly journals A flexible user-interface for audiovisual presentation and interactive control in neurobehavioral experiments

F1000Research ◽  
2013 ◽  
Vol 2 ◽  
pp. 20
Author(s):  
Christopher T Noto ◽  
Suleman Mazhar ◽  
James Gnadt ◽  
Jagmeet S Kanwal
Keyword(s):  
User Interface ◽  
Data Acquisition ◽  
Digital Signal Processor ◽  
Digital Signal ◽  
Stimulus Presentation ◽  
Cost Effective ◽  
Level Control ◽  
Interactive Control ◽  
High Level ◽  
Behavioral Monitoring

A major problem facing behavioral neuroscientists is a lack of unified, vendor-distributed data acquisition systems that allow stimulus presentation and behavioral monitoring while recording neural activity. Numerous systems perform one of these tasks well independently, but to our knowledge, a useful package with a straightforward user interface does not exist. Here we describe the development of a flexible, script-based user interface that enables customization for real-time stimulus presentation, behavioral monitoring and data acquisition. The experimental design can also incorporate neural microstimulation paradigms. We used this interface to deliver multimodal, auditory and visual (images or video) stimuli to a nonhuman primate and acquire single-unit data. Our design is cost-effective and works well with commercially available hardware and software. Our design incorporates a script, providing high-level control of data acquisition via a sequencer running on a digital signal processor to enable behaviorally triggered control of the presentation of visual and auditory stimuli. Our experiments were conducted in combination with eye-tracking hardware. The script, however, is designed to be broadly useful to neuroscientists who may want to deliver stimuli of different modalities using any animal model.

Policy Technologies for Security Management in Coalition Networks

2011 ◽  
pp. 750-776
Author(s):  
Seraphin B. Calo ◽  
Clare-Marie Karat ◽  
John Karat ◽  
Jorge Lobo ◽  
Robert Craven ◽  
...  
Keyword(s):  
Military Personnel ◽  
Security Management ◽  
Security Requirements ◽  
Security Policies ◽  
Technical Expertise ◽  
Policy Management ◽  
Level Control ◽  
Concrete System ◽  
Human In The Loop ◽  
High Level

The goal of policy-based security management is to enable military personnel to specify security requirements in terms of simple, intuitive goals. These goals are translated into the concrete system settings in a way that the system behaves in a consistent and desirable way. This technology minimizes the technical expertise required by military personnel and automates security management while allowing a high level control by the human in the loop. This chapter describes a framework for managing security policies, and an overview of two prototypes that simplify different aspects of policy management in the context of coalition operations.

scholarly journals Mobile Robotics in Agricultural Operations: A Narrative Review on Planning Aspects

2020 ◽  
Vol 10 (10) ◽  
pp. 3453 ◽  
Author(s):  
Vasileios Moysiadis ◽  
Naoum Tsolakis ◽  
Dimitris Katikaridis ◽  
Claus G. Sørensen ◽  
Simon Pearson ◽  
...  
Keyword(s):  
Mobile Robots ◽  
Mobile Robotics ◽  
Narrative Review ◽  
Level Control ◽  
Relevant Research ◽  
World Model ◽  
Level Ii ◽  
Agricultural Operations ◽  
Definition Of ◽  
High Level

The advent of mobile robots in agriculture has signaled a digital transformation with new automation technologies optimize a range of labor-intensive, resources-demanding, and time-consuming agri-field operations. To that end a generally accepted technical lexicon for mobile robots is lacking as pertinent terms are often used interchangeably. This creates confusion among research and practice stakeholders. In addition, a consistent definition of planning attributes in automated agricultural operations is still missing as relevant research is sparse. In this regard, a “narrative” review was adopted (1) to provide the basic terminology over technical aspects of mobile robots used in autonomous operations and (2) assess fundamental planning aspects of mobile robots in agricultural environments. Based on the synthesized evidence from extant studies, seven planning attributes have been included: (i) high-level control-specific attributes, which include reasoning architecture, the world model, and planning level, (ii) operation-specific attributes, which include locomotion–task connection and capacity constraints, and (iii) physical robot-specific attributes, which include vehicle configuration and vehicle kinematics.

scholarly journals A Stabilization Method Based on an Adaptive Feedforward Controller for the Underactuated Bipedal Walking with Variable Step-Length on Compliant Discontinuous Ground

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-16
Author(s):  
Yang Wang ◽  
Daojin Yao ◽  
Jie He ◽  
Xiaohui Xiao
Keyword(s):  
Control Strategy ◽  
Control Method ◽  
Ground Surface ◽  
Step Length ◽  
Bipedal Walking ◽  
Level Control ◽  
Stabilization Method ◽  
Feedforward Controller ◽  
High Level ◽  
Adaptive Feedforward

Both compliance and discontinuity are the common characteristics of the real ground surface. This paper proposes a stabilization method for the underactuated bipedal locomotion on the discontinuous compliant ground. Unlike a totally new control method, the method is actually a high-level control strategy developed based on an existing low-level controller meant for the continuous compliant ground. As a result, although the ground environment is more complex, the calculation cost for the robot walking control system is not increased. With the high-level control strategy, the robot is able to adjust its step-length and velocity simultaneously to stride over the discontinuous areas on the compliant ground surface. The effectiveness of the developed method is validated with a numerical simulation and a physical experiment.

scholarly journals Strategic Tasks for Explainable Reinforcement Learning

2019 ◽  
Vol 33 ◽  
pp. 10007-10008 ◽  
Author(s):  
Rey Pocius ◽  
Lawrence Neal ◽  
Alan Fern
Keyword(s):  
Decision Making ◽  
Reinforcement Learning ◽  
Learning Environment ◽  
Strategic Decision ◽  
Strategic Decision Making ◽  
Sequential Decision Making ◽  
Sequential Decision ◽  
Level Control ◽  
Mini Games ◽  
High Level

Commonly used sequential decision making tasks such as the games in the Arcade Learning Environment (ALE) provide rich observation spaces suitable for deep reinforcement learning. However, they consist mostly of low-level control tasks which are of limited use for the development of explainable artificial intelligence(XAI) due to the fine temporal resolution of the tasks. Many of these domains also lack built-in high level abstractions and symbols. Existing tasks that provide for both strategic decision-making and rich observation spaces are either difficult to simulate or are intractable. We provide a set of new strategic decision-making tasks specialized for the development and evaluation of explainable AI methods, built as constrained mini-games within the StarCraft II Learning Environment.

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