7,765 research outputs found
Dynamic state reconciliation and model-based fault detection for chemical processes
In this paper, we present a method for the fault detection based on the residual generation. The main idea is to reconstruct the outputs of the system from the measurements using the extended Kalman filter. The estimations are compared to the values of the reference model and so, deviations are interpreted as possible faults. The reference model is simulated by the dynamic hybrid simulator, PrODHyS. The use of this method is illustrated through an application in the field of chemical processe
Quantum Markovian Subsystems: Invariance, Attractivity, and Control
We characterize the dynamical behavior of continuous-time, Markovian quantum
systems with respect to a subsystem of interest. Markovian dynamics describes a
wide class of open quantum systems of relevance to quantum information
processing, subsystem encodings offering a general pathway to faithfully
represent quantum information. We provide explicit linear-algebraic
characterizations of the notion of invariant and noiseless subsystem for
Markovian master equations, under different robustness assumptions for
model-parameter and initial-state variations. The stronger concept of an
attractive quantum subsystem is introduced, and sufficient existence conditions
are identified based on Lyapunov's stability techniques. As a main control
application, we address the potential of output-feedback Markovian control
strategies for quantum pure state-stabilization and noiseless-subspace
generation. In particular, explicit results for the synthesis of stabilizing
semigroups and noiseless subspaces in finite-dimensional Markovian systems are
obtained.Comment: 16 pages, no figures. Revised version with new title, corrected
typos, partial rewriting of Section III.E and some other minor change
The turnpike property in finite-dimensional nonlinear optimal control
Turnpike properties have been established long time ago in finite-dimensional
optimal control problems arising in econometry. They refer to the fact that,
under quite general assumptions, the optimal solutions of a given optimal
control problem settled in large time consist approximately of three pieces,
the first and the last of which being transient short-time arcs, and the middle
piece being a long-time arc staying exponentially close to the optimal
steady-state solution of an associated static optimal control problem. We
provide in this paper a general version of a turnpike theorem, valuable for
nonlinear dynamics without any specific assumption, and for very general
terminal conditions. Not only the optimal trajectory is shown to remain
exponentially close to a steady-state, but also the corresponding adjoint
vector of the Pontryagin maximum principle. The exponential closedness is
quantified with the use of appropriate normal forms of Riccati equations. We
show then how the property on the adjoint vector can be adequately used in
order to initialize successfully a numerical direct method, or a shooting
method. In particular, we provide an appropriate variant of the usual shooting
method in which we initialize the adjoint vector, not at the initial time, but
at the middle of the trajectory
Towards Integrating Hybrid DAEs with a High-Index DAE Solver
J.D. Pryce and N.S. Nedialkov have developed a Taylor series method and a C++ package, DaeTs, for solving numerically an initial-value problem differential-algebraic equation (DAE) that can be of high index, high order, nonlinear, and fully implicit. Numerical results have shown this method to be efficient and very accurate, and particularly suitable for problems that are of too high an index for present DAE solvers. However, DaeTs cannot be applied to systems of DAEs that change at points it time, also called hybrid or multi-mode DAEs. This paper presents methods for extending Daets with the capability to integrate hybrid DAEs. Methods for event location and consistent initializations are given. Daets is applied to simulate a model of a parallel robot: a hybrid system of index-3 DAEs with closed-loop control
Model predictive control architecture for rotorcraft inverse simulation
A novel inverse simulation scheme is proposed for applications to rotorcraft dynamic models. The algorithm adopts an architecture that closely resembles that of a model predictive control scheme, where the controlled plant is represented by a high-order helicopter model. A fast solution of the inverse simulation step is obtained on the basis of a lower-order, simplified model. The resulting control action is then propagated forward in time using the more complex one. The algorithm compensates for discrepancies between the models by updating initial conditions for the inverse simulation step and introducing a simple guidance scheme in the definition of the tracked output variables. The proposed approach allows for the assessment of handling quality potential on the basis of the most sophisticated model, while keeping model complexity to a minimum for the computationally more demanding inverse simulation algorithm. The reported results, for an articulated blade, single main rotor helicopter model, demonstrate the validity of the approach
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