911 resultados para Autonomous robots -- Control systems


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Networked control systems (NCS) are distributed control system where the sensors, actuators and controllers are physically separated and connected through communication networks. NCS represent the evolution of networked control architectures providing greater modularity and control decentralization, ease maintenance and diagnosis and lower cost of implementation. A recent trend in this research topic is the development of NCS using wireless networks (WNCS) enabling interoperability between existing wired and wireless systems. This paper evaluates a serial RS-232 ZigBee device as a wireless sensor link in NCS. In order to support this investigation, relevant performance metrics for wireless control applications such as jitter, time delay and messages lost are highlighted and calculated to evaluate the device capabilities. In addition the control performance of an implemented motor control system using the device is analyzed. Experimental results led to the conclusion that serial RS-232 ZigBee devices can be used to implement WNCS and the use of this device delay information in the PID controller discretization can improve the control performance of the system. © 2012 IEEE.

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A recent trend in networked control systems (NCSs) is the use of wireless networks enabling interoperability between existing wired and wireless systems. One of the major challenges in these wireless NCSs (WNCSs) is to overcome the impact of the message loss that degrades the performance and stability of these systems. Moreover, this impact is greater when dealing with burst or successive message losses. This paper discusses and presents the experimental results of a compensation strategy to deal with this burst message loss problem in which a NCS mathematical model runs in parallel with the physical process, providing sensor virtual data in case of packet losses. Running in real-time inside the controller, the mathematical model is updated online with real control signals sent to the actuator, which provides better reliability for the estimated sensor feedback (virtual data) transmitted to the controller each time a message loss occurs. In order to verify the advantages of applying this model-based compensation strategy for burst message losses in WNCSs, the control performance of a motor control system using CAN and ZigBee networks is analyzed. Experimental results led to the conclusion that the developed compensation strategy provided robustness and could maintain the control performance of the WNCS against different message loss scenarios.

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This paper is concerned with the controllability and stabilizability problem for control systems described by a time-varyinglinear abstract differential equation with distributed delay in the state variables. An approximate controllability propertyis established, and for periodic systems, the stabilization problem is studied. Assuming that the semigroup of operatorsassociated with the uncontrolled and non delayed equation is compact, and using the characterization of the asymptoticstability in terms of the spectrum of the monodromy operator of the uncontrolled system, it is shown that the approximatecontrollability property is a sufficient condition for the existence of a periodic feedback control law that stabilizes thesystem. The result is extended to include some systems which are asymptotically periodic. Copyright © 2014 John Wiley &Sons, Ltd.

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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Networked control systems (NCSs) are distributed control system in which sensors, actuators and controllers are physically separated and connected through communication networks. NCS represent the evolution of networked control architectures providing greater modularity and control decentralization, ease maintenance and diagnosis and lower cost of implementation. A recent trend in this research topic is the development of NCS using wireless networks(WNCS)which enable interoperability between existing wiredand wireless systems. This paper presents the feasibility analysis of using serial to wireless converter as a wireless sensor link in NCS. In order to support this investigation, relevant performance metrics for wireless control applications such as jitter, time delay and messages lost are highlighted and calculated to evaluate the wireless converter capabilities. In addition the control performance of an implemented motor control system using the converter is analyzed. Experimental results led to the conclusion that serial ZigBee device isrecommended against the Bluetooth as it provided better metrics for control applications. However, bothdevices can be used to implement WNCS providing transmission rates and closed control loop times which are acceptable for NCS applications.Moreoverthe use of thewireless device delay in the PID controller discretization can improve the control performance of the system.

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Networked control systems (NCSs) are distributed control systems in which the sensors, actuators, and controllers are physically separated and connected through an industrial network. The main challenge related to the development of NCSs is the degenerative effects caused by the inclusion of this communication network in the closed loop control. In order to mitigate these effects, co-simulation tools for NCS have been developed to study the network influence in the NCS. This paper presents a revision about co-simulation tools for NCS and the application of two of these tools for the design and evaluation of NCSs. The TrueTime and Jitterbug tools were used together to evaluate the main configuration parameter that affects the performance of CAN-based NCS and to verify the NCS quality of control under various timing conditions including different transmission period of messages and network delays. Therefore, the simulation results led to the conclusion that despite the transmission period of messages is the most significant factor among the analyzed in the design of NCS, its influence is related to the kind of system with greater effects in NCSs with fast dynamics.

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Building facilities have become important infrastructures for modern productive plants dedicated to services. In this context, the control systems of intelligent buildings have evolved while their reliability has evidently improved. However, the occurrence of faults is inevitable in systems conceived, constructed and operated by humans. Thus, a practical alternative approach is found to be very useful to reduce the consequences of faults. Yet, only few publications address intelligent building modeling processes that take into consideration the occurrence of faults and how to manage their consequences. In the light of the foregoing, a procedure is proposed for the modeling of intelligent building control systems, considersing their functional specifications in normal operation and in the of the event of faults. The proposed procedure adopts the concepts of discrete event systems and holons, and explores Petri nets and their extensions so as to represent the structure and operation of control systems for intelligent buildings under normal and abnormal situations. (C) 2012 Elsevier B.V. All rights reserved.

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Constraints are widely present in the flight control problems: actuators saturations or flight envelope limitations are only some examples of that. The ability of Model Predictive Control (MPC) of dealing with the constraints joined with the increased computational power of modern calculators makes this approach attractive also for fast dynamics systems such as agile air vehicles. This PhD thesis presents the results, achieved at the Aerospace Engineering Department of the University of Bologna in collaboration with the Dutch National Aerospace Laboratories (NLR), concerning the development of a model predictive control system for small scale rotorcraft UAS. Several different predictive architectures have been evaluated and tested by means of simulation, as a result of this analysis the most promising one has been used to implement three different control systems: a Stability and Control Augmentation System, a trajectory tracking and a path following system. The systems have been compared with a corresponding baseline controller and showed several advantages in terms of performance, stability and robustness.

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Management Control System (MCS) research is undergoing turbulent times. For a long time related to cybernetic instruments of management accounting only, MCS are increasingly seen as complex systems comprising not only formal accounting-driven instruments, but also informal mechanisms of control based on organizational culture. But not only have the means of MCS changed; researchers increasingly ap-ply MCS to organizational goals other than strategy implementation.rnrnTaking the question of "How do I design a well-performing MCS?" as a starting point, this dissertation aims at providing a comprehensive and integrated overview of the "current-state" of MCS research. Opting for a definition of MCS, broad in terms of means (all formal as well as informal MCS instruments), but focused in terms of objectives (behavioral control only), the dissertation contributes to MCS theory by, a) developing an integrated (contingency) model of MCS, describing its contingencies, as well as its subcomponents, b) refining the equifinality model of Gresov/Drazin (1997), c) synthesizing research findings from contingency and configuration research concerning MCS, taking into account case studies on research topics such as ambi-dexterity, equifinality and time as a contingency.

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This thesis proposes a novel technology in the field of swarm robotics that allows a swarm of robots to sense a virtual environment through virtual sensors. Virtual sensing is a desirable and helpful technology in swarm robotics research activity, because it allows the researchers to efficiently and quickly perform experiments otherwise more expensive and time consuming, or even impossible. In particular, we envision two useful applications for virtual sensing technology. On the one hand, it is possible to prototype and foresee the effects of a new sensor on a robot swarm, before producing it. On the other hand, thanks to this technology it is possible to study the behaviour of robots operating in environments that are not easily reproducible inside a lab for safety reasons or just because physically infeasible. The use of virtual sensing technology for sensor prototyping aims to foresee the behaviour of the swarm enhanced with new or more powerful sensors, without producing the hardware. Sensor prototyping can be used to tune a new sensor or perform performance comparison tests between alternative types of sensors. This kind of prototyping experiments can be performed through the presented tool, that allows to rapidly develop and test software virtual sensors of different typologies and quality, emulating the behaviour of several hardware real sensors. By investigating on which sensors is better to invest, a researcher can minimize the sensors’ production cost while achieving a given swarm performance. Through augmented reality, it is possible to test the performance of the swarm in a desired virtual environment that cannot be set into the lab for physical, logistic or economical reasons. The virtual environment is sensed by the robots through properly designed virtual sensors. Virtual sensing technology allows a researcher to quickly carry out real robots experiment in challenging scenarios without all the required hardware and environment.

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The main objective of ventilation systems in case of fire is the reduction of the possible consequences by achieving the best possible conditions for the evacuation of the users and the intervention of the emergency services. In the last years, the required quick response of the ventilation system, from normal to emergency mode, has been improved by the use of automatic and semi-automatic control systems, what reduces the response times through the support to the operators decision taking, and the use of pre-defined strategies. A further step consists on the use of closedloop algorithms, which takes into account not only the initial conditions but their development (air velocity, traffic situation, etc), optimizing the quality of the smoke control process

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This paper presents an analysis of the fault tolerance achieved by an autonomous, fully embedded evolvable hardware system, which uses a combination of partial dynamic reconfiguration and an evolutionary algorithm (EA). It demonstrates that the system may self-recover from both transient and cumulative permanent faults. This self-adaptive system, based on a 2D array of 16 (4×4) Processing Elements (PEs), is tested with an image filtering application. Results show that it may properly recover from faults in up to 3 PEs, that is, more than 18% cumulative permanent faults. Two fault models are used for testing purposes, at PE and CLB levels. Two self-healing strategies are also introduced, depending on whether fault diagnosis is available or not. They are based on scrubbing, fitness evaluation, dynamic partial reconfiguration and in-system evolutionary adaptation. Since most of these adaptability features are already available on the system for its normal operation, resource cost for self-healing is very low (only some code additions in the internal microprocessor core)

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Evaluation of three solar and daylighting control systems based on Calumen II, Ecotect and Radiance simulation programs to obtain an energy efficient and healthy interior in the experimental building prototype SDE10