4,405 research outputs found
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
A Near-Optimal Decentralized Servomechanism Controller for Hierarchical Interconnected Systems
This paper is concerned with decentralized output regulation of hierarchical systems subject to input and output disturbances. It is assumed that the disturbance can be represented as the output of an autonomous LTI system with unknown initial state. The primary objective is to design a decentralized controller with the property that not only does it reject the degrading effect of the disturbance on the output (for a satisfactory steady-state performance), it also results in a small LQ cost function (implying a good transient behavior). To this end, the underlying problem is treated in two phases. In the first step, a number of modified systems are defined in terms of the original system. The problem of designing a LQ centralized controller which stabilizes all the modified systems and rejects the disturbance in the original system is considered, and it is shown that this centralized controller can be efficiently found by solving a LMI problem. In the second step, a method recently presented in the literature is exploited to decentralize the designed centralized controller. It is proved that the obtained controller satisfies the pre-determined design specifications including disturbance rejection. Simulation results elucidate the efficacy of the proposed control law
Distributed Design for Decentralized Control using Chordal Decomposition and ADMM
We propose a distributed design method for decentralized control by
exploiting the underlying sparsity properties of the problem. Our method is
based on chordal decomposition of sparse block matrices and the alternating
direction method of multipliers (ADMM). We first apply a classical
parameterization technique to restrict the optimal decentralized control into a
convex problem that inherits the sparsity pattern of the original problem. The
parameterization relies on a notion of strongly decentralized stabilization,
and sufficient conditions are discussed to guarantee this notion. Then, chordal
decomposition allows us to decompose the convex restriction into a problem with
partially coupled constraints, and the framework of ADMM enables us to solve
the decomposed problem in a distributed fashion. Consequently, the subsystems
only need to share their model data with their direct neighbours, not needing a
central computation. Numerical experiments demonstrate the effectiveness of the
proposed method.Comment: 11 pages, 8 figures. Accepted for publication in the IEEE
Transactions on Control of Network System
A decentralized proportional-integral sliding mode tracking controller for a 2 D.O.F robot arm
Trajectory tracking with high accuracy is a very challenging topic in direct drive robot control. This is due to the nonlinearities and input couplings present in the dynamics of the arm. This paper deals with the tracking control of a class of direct-drive robot manipulators. A robust Proportional-Integral (PI) sliding mode control law is derived so that the robot trajectory tracks a desired trajectory as closely as possible despite the highly non-linear and coupled dynamics. The controller is designed using the decentralized approaches. Application to a two degree of freedom direct drive robot arm is considered
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
Unified Approach to Convex Robust Distributed Control given Arbitrary Information Structures
We consider the problem of computing optimal linear control policies for
linear systems in finite-horizon. The states and the inputs are required to
remain inside pre-specified safety sets at all times despite unknown
disturbances. In this technical note, we focus on the requirement that the
control policy is distributed, in the sense that it can only be based on
partial information about the history of the outputs. It is well-known that
when a condition denoted as Quadratic Invariance (QI) holds, the optimal
distributed control policy can be computed in a tractable way. Our goal is to
unify and generalize the class of information structures over which quadratic
invariance is equivalent to a test over finitely many binary matrices. The test
we propose certifies convexity of the output-feedback distributed control
problem in finite-horizon given any arbitrarily defined information structure,
including the case of time varying communication networks and forgetting
mechanisms. Furthermore, the framework we consider allows for including
polytopic constraints on the states and the inputs in a natural way, without
affecting convexity
- …