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The corrected Field of View (FoV) in Adaptive Optics (AO) is limited by the anisoplanatism effect. Multi-Conjugate AO (MCAO) aims at providing a wide FoV correction through the use of several Deformable Mirrors (DMs) and of multi-guide-star WaveFront Sensor (WFS). However the performance optimization of such complex systems raises new questions in terms of calibration and control. We present our current...
In this paper we will discuss the application of optimal filtering techniques for the adaptive optics system of the LBT telescope. We have studied the application of both Kalman and H∞ filters to estimate the temporal evolution of the phase perturbations due to the atmospheric turbulence and the telescope vibrations on tip/tilt modes. We will focus on the H∞ filter and on its advantages and disadvantages...
This paper presents an application of a novel constrained control methodology known as Command Governor (CG) to the shape control of plasmas in thermonuclear fusion reactors. The CG strategy is based on predictive control ideas and consists in modifying, whenever necessary, the reference signal supplied to a primal internal loop controlling the plasma distance from the internal walls of the tokamak,...
This paper forms a part of a series of recent studies we have undertaken, where the problem of nonlinear signal modelling is examined. We assume that an observed "output" signal is derived from a Volterra filter that is driven by a Gaussian input. Both the filter parameters and the input signal are unknown and therefore the problem can be classified as blind or unsupervised in nature. In...
In this paper a nonlinear robust control strategy designed for underactuated mechanical systems is proposed in order to solve the path tracking problem for a quadrotor unmanned aerial vehicle. An underactuated nonlinear ℋ∞ controller based on the six degrees of freedom dynamic model is designed to control the helicopter attitude and altitude in the inner-loop. The outer-loop control is performed using...
This paper deals with the attitude estimation of a quadrotor in the presence of measurement losses. This situation may appear when the quadrotor is controlled through a network. The attitude estimation is a prerequisite to the implementation of any kind of control law. Moreover, the attitude cannot be directly measured and different sensor modalities must be used. The observer implemented is an Extended...
When a Kalman filter is applied to an image for restoration purposes, the model of the original image affects the accuracy of the restoration. The model for effective restoration depends on the correlation of the original image and the variance of the noise. If these parameters are unknown, they have to be estimated from the observed image. In this paper, a method to estimate the unknown parameters...
This paper describes a method by which a set of piece-wise constant autoregressive parameters could be obtained when the source signal is subject to a multistage analysis. It also illustrates an FIR prediction scheme with application to a speech process. It describes a method where the prediction is carried out on a sample by sample basis. This prediction scheme demonstrates the possibility of having...
This paper presents a way of accelerating the evaluation and simulation of nonlinear POD models by using feedforward neural networks. Traditionally, Proper Orthogonal Decomposition (POD) and Galerkin projection have been employed to reduce the high-dimensionality of the discretized systems used to approximate Partial Differential Equations (PDEs). Although a large model-order reduction can be obtained...
The rotary calcination kiln for a production of Titanium dioxide (TiO2) is a very interesting dynamical system. The titanuim dioxide is mostly available in a crystaline form known as anatase. The aim of the calcination process is to produce the titanium dioxide with the rutile content around 98% that has the right pigmentary properties in contrast to the anatase. The system of the rotary calcination...
Iterative controller design for planar Poiseuille flow by model unfalsification and controller redesign is the topic of the paper. The main contribution is to show that model-unfalsification-based iterative design can be useful in flow control problems. The a priori knowledge on the dynamics of the sampled system is obtained from the analytic approximation of the Navier-Stokes equations by a Galerkin...
A bias-correction method for closed-loop identification, introduced in the literature as the bias-eliminated least squares (BELS) method [9], is shown to be equivalent to a basic instrumental variable estimator applied to a predictor for the closed-loop system. This predictor is a function of the plant parameters and the known controller. Corresponding to the related method using a least squares criterion,...
The aim of this paper is to find a fixed structure transfer matrix, whose dynamics (i.e. whose poles) are not a priori fixed, and whose frequency response is the closest as possible to a target one. This non convex optimization problem is recast into a generalized μ problem. A generalized n lower bound is proposed, which provides an a priori suboptimal solution (i.e. a local minimum), namely a transfer...
The theoretic ground of a locally topological method for defining a minimal attractor embedding dimension on the basis of linear and nonlinear decompositions in state-space of a dynamic system is proposed. The computer confirmation of the theoretical results is presented.
This paper is concerned with dynamical population models obtained from short and long-term changes in size and age composition due to demographic processes such as births, deaths, migration, etc. Both deterministic and stochastic models are presented. The parameters which are embedded in the models may be either unavailable or noisy, therefore system identification methods are invoked to estimate...
This paper is concerned with the stability and control of linear systems with uncertain physical parameters. The case where the characteristic equations of the systems are polynomially dependent on uncertain parameters is studied. A new algorithm is presented for the calculation of stability margins in the parameter space in general / p-norms. The stability is defined with respect to a desired region...
The paper proposed to apply a fuzzy-neural recurrent multi-model for systems identification and states estimation of complex nonlinear plants. The parameters of the local recurrent neural network models are used for a local indirect adaptive trajectory tracking control systems design. The designed local control laws are coordinated by a fuzzy rule based control system. The applicability of the proposed...
This paper considers the problem of applying eigenstracture assignment to parameter dependant systems. The concept of modal sensitivity is introduced, and a recently presented method for the assignment of reduced sensitivity eigenstracture is presented in this context. A new proof for this method is presented, allowing greater insight into the sensitivity problem, and leading to a more flexible design...
A piecewise-linear hybrid system is a dynamic system which is the product of a finite-state automaton and a family of affine systems on polytopes. In full generality, determination of the controllability of such systems is undecidable. For control synthesis it is therefore of interest to determine subclasses of such systems for which the problem is decidable. In this paper an approach to controllability...
This work focuses on the nonlinear control of helicopters. Our global interest is a general model (7-DOF) to be used on the autonomous forward-flight of helicopters. However, in this paper we present a reduced-order model (3-DOF) representing a scale model helicopter mounted on an experimental platform. In this system the vertical flight of the helicopter can be studied. Although simplified, this...
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