19,514 research outputs found
Analysis of input delay systems using integral quadratic constraint
The L2-gain computation of a linear time-invariant system with state and input delay is discussed. The input and the state delay are handled separately by using dissipation inequality involving a Lyapunov-Krasovskii functional and integral quadratic constraints. A conic combination of IQCs is proposed for characterizing the input delay, where the coefficients are linear time-invariant systems. The numerical example (a vehicle platoon) confirm that using this dissipativity approach a more effective method for L2-gain computation is obtained
An Overview of Integral Quadratic Constraints for Delayed Nonlinear and Parameter-Varying Systems
A general framework is presented for analyzing the stability and performance
of nonlinear and linear parameter varying (LPV) time delayed systems. First,
the input/output behavior of the time delay operator is bounded in the
frequency domain by integral quadratic constraints (IQCs). A constant delay is
a linear, time-invariant system and this leads to a simple, intuitive
interpretation for these frequency domain constraints. This simple
interpretation is used to derive new IQCs for both constant and varying delays.
Second, the performance of nonlinear and LPV delayed systems is bounded using
dissipation inequalities that incorporate IQCs. This step makes use of recent
results that show, under mild technical conditions, that an IQC has an
equivalent representation as a finite-horizon time-domain constraint. Numerical
examples are provided to demonstrate the effectiveness of the method for both
class of systems
Stochastic model predictive control for constrained networked control systems with random time delay
In this paper the continuous time stochastic constrained optimal control problem is formulated for the class of networked control systems assuming that time delays follow a discrete-time, finite Markov chain . Polytopic overapproximations of the system's trajectories are employed to produce a polyhedral inner approximation of the non-convex constraint set resulting from imposing the constraints in continuous time. The problem is cast in a Markov jump linear systems (MJLS) framework and a stochastic MPC controller is calculated explicitly, oine, coupling dynamic programming with parametric piecewise quadratic (PWQ) optimization. The calculated control law leads to stochastic stability of the closed loop system, in the mean square sense and respects the state and input constraints in continuous time
Localization of Control Synthesis Problem for Large-Scale Interconnected System Using IQC and Dissipativity Theories
The synthesis problem for the compositional performance certification of
interconnected systems is considered. A fairly unified description of control
synthesis problem is given using integral quadratic constraints (IQC) and
dissipativity. Starting with a given large-scale interconnected system and a
global performance objective, an optimization problem is formulated to search
for admissible dissipativity properties of each subsystems. Local control laws
are then synthesized to certify the relevant dissipativity properties.
Moreover, the term localization is introduced to describe a finite collection
of syntheses problems, for the local subsystems, which are a feasibility
certificate for the global synthesis problem. Consequently, the problem of
localizing the global problem to a smaller collection of disjointed sets of
subsystems, called groups, is considered. This works looks promising as another
way of looking at decentralized control and also as a way of doing performance
specifications for components in a large-scale system
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