10,168 research outputs found
Consensus-based control for a network of diffusion PDEs with boundary local interaction
In this paper the problem of driving the state of a network of identical
agents, modeled by boundary-controlled heat equations, towards a common
steady-state profile is addressed. Decentralized consensus protocols are
proposed to address two distinct problems. The first problem is that of
steering the states of all agents towards the same constant steady-state
profile which corresponds to the spatial average of the agents initial
condition. A linear local interaction rule addressing this requirement is
given. The second problem deals with the case where the controlled boundaries
of the agents dynamics are corrupted by additive persistent disturbances. To
achieve synchronization between agents, while completely rejecting the effect
of the boundary disturbances, a nonlinear sliding-mode based consensus protocol
is proposed. Performance of the proposed local interaction rules are analyzed
by applying a Lyapunov-based approach. Simulation results are presented to
support the effectiveness of the proposed algorithms
Predictor-feedback synthesis in coordinate-free formation control under time-varying delays
This paper investigates new coordinate-free formation control strategies of multi-agent systems to overcome the negative effects of time delays. To this end, we present a single predictor-feedback scheme to compensate the multiple communication delays, assumed to be unknown but bounded and arbitrarily-fast time-varying. Although delays cannot exactly be compensated due to time-varying delay mismatches, the trade-off between robustness and convergence speed can be notably improved if the control gain is suitably designed. Hence, with the objective of enlarging the time-varying delay interval for a given convergence speed, an LMI-based iterative algorithm is presented to solve the control gain synthesis
Mean-Field-Type Games in Engineering
A mean-field-type game is a game in which the instantaneous payoffs and/or
the state dynamics functions involve not only the state and the action profile
but also the joint distributions of state-action pairs. This article presents
some engineering applications of mean-field-type games including road traffic
networks, multi-level building evacuation, millimeter wave wireless
communications, distributed power networks, virus spread over networks, virtual
machine resource management in cloud networks, synchronization of oscillators,
energy-efficient buildings, online meeting and mobile crowdsensing.Comment: 84 pages, 24 figures, 183 references. to appear in AIMS 201
Persistence based analysis of consensus protocols for dynamic graph networks
This article deals with the consensus problem involving agents with
time-varying singularities in the dynamics or communication in undirected graph
networks. Existing results provide control laws which guarantee asymptotic
consensus. These results are based on the analysis of a system switching
between piecewise constant and time-invariant dynamics. This work introduces a
new analysis technique relying upon classical notions of persistence of
excitation to study the convergence properties of the time-varying multi-agent
dynamics. Since the individual edge weights pass through singularities and vary
with time, the closed-loop dynamics consists of a non-autonomous linear system.
Instead of simplifying to a piecewise continuous switched system as in
literature, smooth variations in edge weights are allowed, albeit assuming an
underlying persistence condition which characterizes sufficient inter-agent
communication to reach consensus. The consensus task is converted to
edge-agreement in order to study a stabilization problem to which classical
persistence based results apply. The new technique allows precise computation
of the rate of convergence to the consensus value.Comment: This article contains 7 pages and includes 4 figures. it is accepted
in 13th European Control Conferenc
On the Robust Control and Optimization Strategies for Islanded Inverter-Based Microgrids
In recent years, the concept of Microgrids (MGs) has become more popular due to a significant integration of renewable energy sources (RESs) into electric power systems. Microgrids are small-scale power grids consisting of localized grouping of heterogeneous Distributed Generators (DGs), storage systems, and loads. MGs may operate either in autonomous islanded mode or connected to the main power system. Despite the significant benefits of increasing RESs, many new challenges raise
in controlling MGs. Hence, a three layered hierarchical architecture consisting of
three control loops closed on the DGs dynamics has been introduced for MGs. The
inner loop is called Primary Control (PC), and it provides the references for the DG’s
DC-AC power converters. In general, the PC is implemented in a decentralized way
with the aim to establish, by means of a droop control term, the desired sharing of
power among DGs while preserving the MG stability. Then, because of inverterbased DGs have no inertia, a Secondary Control (SC) layer is needed to compensate
the frequency and voltage deviations introduced by the PC’s droop control terms.
Finally, an operation control is designed to optimize the operation of the MGs by
providing power setpoints to the lower control layers.
This thesis is mainly devoted to the design of robust distributed secondary frequency and voltage restoration control strategies for AC MGs to avoid central controllers and complexity of communication networks. Different distributed strategies
are proposed in this work: (i) Robust Adaptive Distributed SC with Communication delays (ii) Robust Optimal Distributed Voltage SC with Communication Delays and (iii) Distributed Finite-Time SC by Coupled Sliding-Mode Technique. In all
three proposed approaches, the problem is addressed in a multi-agent fashion where
the generator plays the role of cooperative agents communicating over a network
and physically coupled through the power system. The first approach provides an
exponentially converging voltage and frequency restoration rate in the presence of
both, model uncertainties, and multiple time-varying delays in the DGs’s communications. This approach consist of two terms: 1) a decentralized Integral Sliding
Mode Control (ISMC) aimed to enforce each agent (DG) to behaves as reference
unperturbed dynamic; 2) an ad-hoc designed distributed protocol aimed to globally, exponentially, achieves the frequency and voltage restoration while fulfilling
the power-sharing constraints in spite of the communication delays. The second
approach extends the first one by including an optimization algorithm to find the
optimal control gains and estimate the corresponding maximum delay tolerated by
the controlled system. In the third approach, the problem of voltage and frequency
restoration as well as active power sharing are solved in finite-time by exploiting
delay-free communications among DGs and considering model uncertainties. In this approach, for DGs with no direct access to their reference values, a finite-time
distributed sliding mode estimator is implemented for both secondary frequency
and voltage schemes. The estimator determines local estimates of the global reference values of the voltage and frequency for DGs in a finite time and provides this
information for the distributed SC schemes.
This dissertation also proposes a novel certainty Model Predictive Control (MPC)
approach for the operation of islanded MG with very high share of renewable energy sources. To this aim, the conversion losses of storage units are formulated by
quadratic functions to reduce the error in storage units state of charge prediction
The Hierarchical Control Method for Coordinating a Group of Connected Vehicles on Urban Roads
Safety, mobility and environmental impact are the three major challenges in today\u27s transportation system. As the advances in wireless communication and vehicle automation technologies, they have rapidly led to the emergence and development of connected and automated vehicles (CAVs). We can expect fully CAVs by 2030. The CAV technologies offer another solution for the issues we are dealing with in the current transportation system. In the meanwhile, urban roads are one of the most important part in the transportation network. Urban roads are characterized by multiple interconnected intersections. They are more complicated than highway traffic, because the vehicles on the urban roads are moving in multiple directions with higher relative velocity. Most of the traffic accidents happened at intersections and the intersections are the major contribution to the traffic congestions. Our urban road infrastructures are also becoming more intelligent. Sensor-embedded roadways are continuously gathering traffic data from passing vehicles. Our smart vehicles are meeting intelligent roads. However, we have not taken the fully advantages of the data rich traffic environment provided by the connected vehicle technologies and intelligent road infrastructures. The objective of this research is to develop a coordination control strategy for a group of connected vehicles under intelligent traffic environment, which can guide the vehicles passing through the intersections and make smart lane change decisions with the objective of improving overall fuel economy and traffic mobility. The coordination control strategy should also be robust to imperfect connectivity conditions with various connected vehicle penetration rate. This dissertation proposes a hierarchical control method to coordinate a group of connected vehicles travelling on urban roads with intersections. The dissertation includes four parts of the application of our proposed method: First, we focus on the coordination of the connected vehicles on the multiple interconnected unsignalized intersection roads, where the traffic signals are removed and the collision avoidance at the intersection area relays on the communication and cooperation of the connected vehicles and intersection controllers. Second, a fuel efficient hierarchical control method is proposed to control the connected vehicles travel on the signalized intersection roads. With the signal phase and timing (SPAT) information, our proposed approach is able to help the connected vehicles minimize red light idling and improve the fuel economy at the same time. Third, the research is extended form single lane to multiple lane, where the connected vehicle discretionary and cooperative mandatory lane change have been explored. Finally, we have analysis the real-world implementation potential of our proposed algorithm including the communication delay and real-time implementation analysis
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