105,897 research outputs found
Control and optimization methods for problems in intelligent transportation systems
This thesis aims to address three research topics in intelligent transportation systems
which include multi-intersection traffic light control based on stochastic flow models with
delays and blocking, optimization of mobility-on-demand systems using event-driven receding
horizon control and the optimal control of lane change maneuvers in highways for
connected and automated vehicles.
First, for the traffic light control work, we extend Stochastic Flow Models (SFMs),
used for a large class of discrete event and hybrid systems, by including the delays which
typically arise in flow movements, as well as blocking effects due to space constraints. We
apply this framework to the multi-intersection traffic light control problem by including
transit delays for vehicles moving from one intersection to the next and possible blocking
between two intersections. Using Infinitesimal Perturbation Analysis (IPA) for this SFM
with delays and possible blocking, we derive new on-line gradient estimates of several
congestion cost metrics with respect to the controllable green and red cycle lengths. The
IPA estimators are used to iteratively adjust light cycle lengths to improve performance
and, in conjunction with a standard gradient-based algorithm, to obtain optimal values
which adapt to changing traffic conditions.
The second problem relates to developing an event-driven Receding Horizon Control
(RHC) scheme for a Mobility-on-Demand System (MoDS) in a transportation network
where vehicles may be shared to pick up and drop off passengers so as to minimize a
weighted sum of passenger waiting and traveling times. Viewed as a discrete event system,
the event-driven nature of the controller significantly reduces the complexity of the vehicle
assignment problem, thus enabling its real-time implementation.
Finally, optimal control policies are derived for a Connected Automated Vehicle (CAV)
cooperating with neighboring CAVs in order to implement a lane change maneuver consisting
of a longitudinal phase where the CAV properly positions itself relative to the cooperating
neighbors and a lateral phase where it safely changes lanes. For the first phase, the maneuver time subject to safety constraints and subsequently the associated energy consumption of all cooperating vehicles in this maneuver are optimized. For the second phase, time and energy are jointly optimized based on three different solution methods including a real-time approach based on Control Barrier Functions (CBFs). Structural properties of the optimal policies which simplify the solution derivations are provided in the case of the longitudinal maneuver, leading to analytical optimal control expressions. The solutions, when they exist, are guaranteed to satisfy safety constraints for all vehicles involved in the maneuver
Model predictive control techniques for hybrid systems
This paper describes the main issues encountered when applying model predictive control to hybrid processes. Hybrid model predictive control (HMPC) is a research field non-fully developed with many open challenges. The paper describes some of the techniques proposed by the research community to overcome the main problems encountered. Issues related to the stability and the solution of the optimization problem are also discussed. The paper ends by describing the results of a benchmark exercise in which several HMPC schemes were applied to a solar air conditioning plant.Ministerio de Eduación y Ciencia DPI2007-66718-C04-01Ministerio de Eduación y Ciencia DPI2008-0581
A Developmental Organization for Robot Behavior
This paper focuses on exploring how learning and development can be structured in synthetic (robot) systems. We present a developmental assembler for constructing reusable and temporally extended actions in a sequence. The discussion adopts the traditions
of dynamic pattern theory in which behavior
is an artifact of coupled dynamical systems
with a number of controllable degrees of freedom. In our model, the events that delineate
control decisions are derived from the pattern
of (dis)equilibria on a working subset of sensorimotor policies. We show how this architecture can be used to accomplish sequential
knowledge gathering and representation tasks
and provide examples of the kind of developmental milestones that this approach has
already produced in our lab
From Packet to Power Switching: Digital Direct Load Scheduling
At present, the power grid has tight control over its dispatchable generation
capacity but a very coarse control on the demand. Energy consumers are shielded
from making price-aware decisions, which degrades the efficiency of the market.
This state of affairs tends to favor fossil fuel generation over renewable
sources. Because of the technological difficulties of storing electric energy,
the quest for mechanisms that would make the demand for electricity
controllable on a day-to-day basis is gaining prominence. The goal of this
paper is to provide one such mechanisms, which we call Digital Direct Load
Scheduling (DDLS). DDLS is a direct load control mechanism in which we unbundle
individual requests for energy and digitize them so that they can be
automatically scheduled in a cellular architecture. Specifically, rather than
storing energy or interrupting the job of appliances, we choose to hold
requests for energy in queues and optimize the service time of individual
appliances belonging to a broad class which we refer to as "deferrable loads".
The function of each neighborhood scheduler is to optimize the time at which
these appliances start to function. This process is intended to shape the
aggregate load profile of the neighborhood so as to optimize an objective
function which incorporates the spot price of energy, and also allows
distributed energy resources to supply part of the generation dynamically.Comment: Accepted by the IEEE journal of Selected Areas in Communications
(JSAC): Smart Grid Communications series, to appea
Discrete events: Perspectives from system theory
Systems Theory;differentiaal/ integraal-vergelijkingen
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