43 research outputs found
Plug-and-Play Decentralized Model Predictive Control
In this paper we consider a linear system structured into physically coupled
subsystems and propose a decentralized control scheme capable to guarantee
asymptotic stability and satisfaction of constraints on system inputs and
states. The design procedure is totally decentralized, since the synthesis of a
local controller uses only information on a subsystem and its neighbors, i.e.
subsystems coupled to it. We first derive tests for checking if a subsystem can
be plugged into (or unplugged from) an existing plant without spoiling overall
stability and constraint satisfaction. When this is possible, we show how to
automatize the design of local controllers so that it can be carried out in
parallel by smart actuators equipped with computational resources and capable
to exchange information with neighboring subsystems. In particular, local
controllers exploit tube-based Model Predictive Control (MPC) in order to
guarantee robustness with respect to physical coupling among subsystems.
Finally, an application of the proposed control design procedure to frequency
control in power networks is presented.Comment: arXiv admin note: text overlap with arXiv:1210.692
Plug-and-Play Model Predictive Control based on robust control invariant sets
In this paper we consider a linear system represented by a coupling graph
between subsystems and propose a distributed control scheme capable to
guarantee asymptotic stability and satisfaction of constraints on system inputs
and states. Most importantly, as in Riverso et al., 2012 our design procedure
enables plug-and-play (PnP) operations, meaning that (i) the addition or
removal of subsystems triggers the design of local controllers associated to
successors to the subsystem only and (ii) the synthesis of a local controller
for a subsystem requires information only from predecessors of the subsystem
and it can be performed using only local computational resources. Our method
hinges on local tube MPC controllers based on robust control invariant sets and
it advances the PnP design procedure proposed in Riverso et al., 2012 in
several directions. Quite notably, using recent results in the computation of
robust control invariant sets, we show how critical steps in the design of a
local controller can be solved through linear programming. Finally, an
application of the proposed control design procedure to frequency control in
power networks is presented
Voltage stabilization in DC microgrids: an approach based on line-independent plug-and-play controllers
We consider the problem of stabilizing voltages in DC microGrids (mGs) given
by the interconnection of Distributed Generation Units (DGUs), power lines and
loads. We propose a decentralized control architecture where the primary
controller of each DGU can be designed in a Plug-and-Play (PnP) fashion,
allowing the seamless addition of new DGUs. Differently from several other
approaches to primary control, local design is independent of the parameters of
power lines. Moreover, differently from the PnP control scheme in [1], the
plug-in of a DGU does not require to update controllers of neighboring DGUs.
Local control design is cast into a Linear Matrix Inequality (LMI) problem
that, if unfeasible, allows one to deny plug-in requests that might be
dangerous for mG stability. The proof of closed-loop stability of voltages
exploits structured Lyapunov functions, the LaSalle invariance theorem and
properties of graph Laplacians. Theoretical results are backed up by
simulations in PSCAD
Plug-and-play distributed state estimation for linear systems
This paper proposes a state estimator for large-scale linear systems
described by the interaction of state-coupled subsystems affected by bounded
disturbances. We equip each subsystem with a Local State Estimator (LSE) for
the reconstruction of the subsystem states using pieces of information from
parent subsystems only. Moreover we provide conditions guaranteeing that the
estimation errors are confined into prescribed polyhedral sets and converge to
zero in absence of disturbances. Quite remarkably, the design of an LSE is
recast into an optimization problem that requires data from the corresponding
subsystem and its parents only. This allows one to synthesize LSEs in a
Plug-and-Play (PnP) fashion, i.e. when a subsystem gets added, the update of
the whole estimator requires at most the design of an LSE for the subsystem and
its parents. Theoretical results are backed up by numerical experiments on a
mechanical system
Model predictive controllers for reduction of mechanical fatigue in wind farms
We consider the problem of dispatching WindFarm (WF) power demand to
individual Wind Turbines (WT) with the goal of minimizing mechanical stresses.
We assume wind is strong enough to let each WTs to produce the required power
and propose different closed-loop Model Predictive Control (MPC) dispatching
algorithms. Similarly to existing approaches based on MPC, our methods do not
require changes in WT hardware but only software changes in the SCADA system of
the WF. However, differently from previous MPC schemes, we augment the model of
a WT with an ARMA predictor of the wind turbulence, which reduces uncertainty
in wind predictions over the MPC control horizon. This allows us to develop
both stochastic and deterministic MPC algorithms. In order to compare different
MPC schemes and demonstrate improvements with respect to classic open-loop
schedulers, we performed simulations using the SimWindFarm toolbox for MatLab.
We demonstrate that MPC controllers allow to achieve reduction of stresses even
in the case of large installations such as the 100-WTs Thanet offshore WF
A decentralized scalable approach to voltage control of DC islanded microgrids
We propose a new decentralized control scheme for DC Islanded microGrids
(ImGs) composed by several Distributed Generation Units (DGUs) with a general
interconnection topology. Each local controller regulates to a reference value
the voltage of the Point of Common Coupling (PCC) of the corresponding DGU.
Notably, off-line control design is conducted in a Plug-and-Play (PnP) fashion
meaning that (i) the possibility of adding/removing a DGU without spoiling
stability of the overall ImG is checked through an optimization problem; (ii)
when a DGU is plugged in or out at most neighbouring DGUs have to update their
controllers and (iii) the synthesis of a local controller uses only information
on the corresponding DGU and lines connected to it. This guarantee total
scalability of control synthesis as the ImG size grows or DGU gets replaced.
Yes, under mild approximations of line dynamics, we formally guarantee
stability of the overall closed-loop ImG. The performance of the proposed
controllers is analyzed simulating different scenarios in PSCAD.Comment: arXiv admin note: text overlap with arXiv:1405.242
Plug-and-play and coordinated control for bus-connected AC islanded microgrids
This paper presents a distributed control architecture for voltage and
frequency stabilization in AC islanded microgrids. In the primary control
layer, each generation unit is equipped with a local controller acting on the
corresponding voltage-source converter. Following the plug-and-play design
approach previously proposed by some of the authors, whenever the
addition/removal of a distributed generation unit is required, feasibility of
the operation is automatically checked by designing local controllers through
convex optimization. The update of the voltage-control layer, when units plug
-in/-out, is therefore automatized and stability of the microgrid is always
preserved. Moreover, local control design is based only on the knowledge of
parameters of power lines and it does not require to store a global microgrid
model. In this work, we focus on bus-connected microgrid topologies and enhance
the primary plug-and-play layer with local virtual impedance loops and
secondary coordinated controllers ensuring bus voltage tracking and reactive
power sharing. In particular, the secondary control architecture is
distributed, hence mirroring the modularity of the primary control layer. We
validate primary and secondary controllers by performing experiments with
balanced, unbalanced and nonlinear loads, on a setup composed of three
bus-connected distributed generation units. Most importantly, the stability of
the microgrid after the addition/removal of distributed generation units is
assessed. Overall, the experimental results show the feasibility of the
proposed modular control design framework, where generation units can be
added/removed on the fly, thus enabling the deployment of virtual power plants
that can be resized over time