5,164 research outputs found
Distributed Bio-inspired Humanoid Posture Control
This paper presents an innovative distributed bio-inspired posture control
strategy for a humanoid, employing a balance control system DEC (Disturbance
Estimation and Compensation). Its inherently modular structure could
potentially lead to conflicts among modules, as already shown in literature. A
distributed control strategy is presented here, whose underlying idea is to let
only one module at a time perform balancing, whilst the other joints are
controlled to be at a fixed position. Modules agree, in a distributed fashion,
on which module to enable, by iterating a max-consensus protocol. Simulations
performed with a triple inverted pendulum model show that this approach limits
the conflicts among modules while achieving the desired posture and allows for
saving energy while performing the task. This comes at the cost of a higher
rise time.Comment: 2019 41st Annual International Conference of the IEEE Engineering in
Medicine & Biology Society (EMBC
Distributed Decision Through Self-Synchronizing Sensor Networks in the Presence of Propagation Delays and Asymmetric Channels
In this paper we propose and analyze a distributed algorithm for achieving
globally optimal decisions, either estimation or detection, through a
self-synchronization mechanism among linearly coupled integrators initialized
with local measurements. We model the interaction among the nodes as a directed
graph with weights (possibly) dependent on the radio channels and we pose
special attention to the effect of the propagation delay occurring in the
exchange of data among sensors, as a function of the network geometry. We
derive necessary and sufficient conditions for the proposed system to reach a
consensus on globally optimal decision statistics. One of the major results
proved in this work is that a consensus is reached with exponential convergence
speed for any bounded delay condition if and only if the directed graph is
quasi-strongly connected. We provide a closed form expression for the global
consensus, showing that the effect of delays is, in general, the introduction
of a bias in the final decision. Finally, we exploit our closed form expression
to devise a double-step consensus mechanism able to provide an unbiased
estimate with minimum extra complexity, without the need to know or estimate
the channel parameters.Comment: To be published on IEEE Transactions on Signal Processin
Secondary Frequency and Voltage Control of Islanded Microgrids via Distributed Averaging
In this work we present new distributed controllers for secondary frequency
and voltage control in islanded microgrids. Inspired by techniques from
cooperative control, the proposed controllers use localized information and
nearest-neighbor communication to collectively perform secondary control
actions. The frequency controller rapidly regulates the microgrid frequency to
its nominal value while maintaining active power sharing among the distributed
generators. Tuning of the voltage controller provides a simple and intuitive
trade-off between the conflicting goals of voltage regulation and reactive
power sharing. Our designs require no knowledge of the microgrid topology,
impedances or loads. The distributed architecture allows for flexibility and
redundancy, and eliminates the need for a central microgrid controller. We
provide a voltage stability analysis and present extensive experimental results
validating our designs, verifying robust performance under communication
failure and during plug-and-play operation.Comment: Accepted for publication in IEEE Transactions on Industrial
Electronic
V2I-Based Platooning Design with Delay Awareness
This paper studies the vehicle platooning system based on
vehicle-to-infrastructure (V2I) communication, where all the vehicles in the
platoon upload their driving state information to the roadside unit (RSU), and
RSU makes the platoon control decisions with the assistance of edge computing.
By addressing the delay concern, a platoon control approach is proposed to
achieve plant stability and string stability. The effects of the time headway,
communication and edge computing delays on the stability are quantified. The
velocity and size of the stable platoon are calculated, which show the impacts
of the radio parameters such as massive MIMO antennas and frequency band on the
platoon configuration. The handover performance between RSUs in the V2I-based
platooning system is quantified by considering the effects of the RSU's
coverage and platoon size, which demonstrates that the velocity of a stable
platoon should be appropriately chosen, in order to meet the V2I's
Quality-of-Service and handover constraints
Decentralized optimal control of a vehicle platoon with guaranteed string stability
International audienceThis paper presents new decentralized optimal strategies for Cooperative Adaptive Cruise Control (CACC) of a car platoon under string-stability constraints. Two related scenarios are explored in the article: in the first one, a linear-quadratic regulator in the presence of measurable disturbances is synthesized, and the string-stability of the platoon is enforced over the controller's feedback and feedforward gains. In the second scenario, H2- and Hinf-performance criteria, respectively accounting for the desired group behavior and the string-stability of the platoon, are simultaneously achieved using the recently-proposed compensator blending method. An analytical study of the impact of actuation/communication delays and uncertain model parameters on the stability of the multi-vehicle system, is also conducted. The theory is illustrated via numerical simulations
Automated driving and autonomous functions on road vehicles
In recent years, road vehicle automation has become an important and popular topic for research
and development in both academic and industrial spheres. New developments received
extensive coverage in the popular press, and it may be said that the topic has captured the
public imagination. Indeed, the topic has generated interest across a wide range of academic,
industry and governmental communities, well beyond vehicle engineering; these include computer
science, transportation, urban planning, legal, social science and psychology. While this
follows a similar surge of interest – and subsequent hiatus – of Automated Highway Systems
in the 1990’s, the current level of interest is substantially greater, and current expectations
are high. It is common to frame the new technologies under the banner of “self-driving cars”
– robotic systems potentially taking over the entire role of the human driver, a capability that
does not fully exist at present. However, this single vision leads one to ignore the existing
range of automated systems that are both feasible and useful. Recent developments are underpinned
by substantial and long-term trends in “computerisation” of the automobile, with
developments in sensors, actuators and control technologies to spur the new developments in
both industry and academia. In this paper we review the evolution of the intelligent vehicle
and the supporting technologies with a focus on the progress and key challenges for vehicle
system dynamics. A number of relevant themes around driving automation are explored in
this article, with special focus on those most relevant to the underlying vehicle system dynamics.
One conclusion is that increased precision is needed in sensing and controlling vehicle
motions, a trend that can mimic that of the aerospace industry, and similarly benefit from
increased use of redundant by-wire actuators
Energy-efficient Connected Cruise Control with Lean Penetration of Connected Vehicles
This paper focuses on energy-efficient longitudinal controller design for a
connected automated truck that travels in mixed traffic consisting of connected
and non-connected vehicles. The truck has access to information about connected
vehicles beyond line of sight using vehicle-to-vehicle (V2V) communication. A
novel connected cruise control design is proposed which incorporates additional
delays into the control law when responding to distant connected vehicles to
account for the finite propagation of traffic waves. The speeds of
non-connected vehicles are modeled as stochastic processes. A fundamental
theorem is proven which links the spectral properties of the motion signals to
the average energy consumption. This enables us to tune controller parameters
and maximize energy efficiency. Simulations with synthetic data and real
traffic data are used to demonstrate the energy efficiency of the control
design. It is demonstrated that even with lean penetration of connected
vehicles, our controller can bring significant energy savings.Comment: This is submitted to IEEE Transactions on Intelligent Transportation
System
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