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This work proposes a control algorithm to stabilize a circular formation of AUVs tracking a time-varying center. We also consider the problem of uniform distribution of all the agents along the circle from two approaches: all-to-all and limited communication. We tackle with this communication constraint using a cooperative control strategy which includes the Laplacian matrix of the communication graph...
In this article, we investigate a new class of control problems called Ensemble Control, a notion coming from the study of complex spin dynamics in Nuclear Magnetic Resonance (NMR) spectroscopy and imaging (MRI). This subject involves controlling a continuum of parameterized dynamical systems with the same open-loop control signal. From a viewpoint of mathematical control theory, this class of problems...
This paper is a first attempt for a new second order sliding mode output feedback controller. This last one is developed in the case of finite sampling frequency and is using only output information in order to ensure desired trajectory tracking with high accuracy in a finite time in spite of uncertainties and perturbations. This controller ensures the establishment of a ??real?? second order sliding...
Estimates from an extended Kalman filter (EKF) is used in an iterative learning control (ILC) algorithm applied to a realistic two-link robot model with flexible joints. The angles seen from the arm side of the joints (arm angles) are estimated by an EKF in two ways: 1) using measurements of angles seen from the motor side of the joints (motor angles), which normally are the only measurements available...
Consider a network of sensors able to move in 2-dimensional space. We may aim to impose distance constraints between certain sensors to ensure every pair of sensors maintain their distance from one another under any continuous movement. This property is known as rigidity. Rigidity may be required to ensure that no sensor will move out of range of any other sensor during movement. However, there arise...
We propose a dynamical model-based approach for tracking the shape and deformation of highly deforming objects from time-varying imagery. Previous works have assumed that the object deformation is smooth, which is realistic for the tracking problem, but most have restricted the deformation to belong to a finite-dimensional group, such as affine motions, or to finitely-parameterized models. This, however,...
Multi-model based fault detection is often a viable alternative to various multi-model based state estimation techniques using banks of Kalman filters. A main advantage of the fault detection techniques based approach is the possibility to use detectors having low order dynamics with disturbance decoupling capabilities. The proposed synthesis algorithm of detectors relies on numerically reliable rational...
In this paper we present a novel algorithm to identify MIMO Hammerstein-Wiener systems under open and closed-loop conditions.We reformulate a linear regression problem, commonly used as the first step in closed loop subspace identification, as an intersection problem which can be solved by using canonical correlation analysis (CCA). This makes it possible to utilize ideas from machine learning to...
Dataflow representations of Digital Signal Processing (DSP) software have been developing since the 1980's. They have proven to be useful in identifying bottlenecks in DSP algorithms, improving the efficiency of the computations, and in designing appropriate hardware for implementing the algorithms. This paper demonstrates the use of dataflow to improve a Model Predictive Control (MPC) algorithm....
For a large class of switched systems with zeno phenomenon, classical observer cannot be applied directly since the terms leading to zeno phenomenon are not derivable. However in this paper, by assuming that these terms are integrable in the less restrictive way, we can define a new output, with which algebraic observer can then be adopted to estimate the states of the studied switched systems with...
This paper presents a novel Model Predictive Control strategy for input-saturated nonlinear systems having a polynomial structure. The method is based on algebraic geometry and viability theory arguments for computing the sets of states that can be steered in a finite number of steps, via a general control law, to a given robust positive invariant set. A first key aim is to present Sum-of-Squares...
In this paper an Iterative Learning Control (ILC) algorithm is proposed for a certain class of Linear Parameter Varying (LPV) systems whose dynamics change between iterations. Consistency of the algorithm in the presence of stochastic disturbances is shown. The proposed algorithm is tested in simulation and the obtained tracking performance is compared with that obtained using a standard Linear Time...
In this paper, an optimization-based adaptive Kalman filtering method is proposed. The method produces an estimate of the process noise covariance matrix Q by solving an optimization problem over a short window of data. The algorithm recovers the observations h(x) from a system x = f (x); y = h(x)+v without a priori knowledge of system dynamics. Potential applications include target tracking using...
This paper is concerned with the stability and convergence of a general stochastic self-tuning control (STC) system, which consists of arbitrary control strategy and arbitrary estimation algorithm. The necessary conditions required for global stability and convergence are relaxed, i.e., the convergence of parameter estimates is removed. The key point is that with the help of virtual equivalent system...
Practical stabilizability of discrete-time (DT) switched systems is studied in this paper. We first prove a sufficient condition for ??-practical asymptotic stabilizability of DT switched systems, then we focus on switched affine systems and present an approach to estimating the minimum bound for practical stabilizability. Based on the approach, we present several new sufficient conditions for global...
Low gain feedback has found several applications in constrained control, robust control and nonlinear control. Low gain feedback refers to a family of stabilizing state feedback gains that are parameterized in a scalar and go to zero as the scalar decreases to zero. Slow peaking, the peak value of the state of the closed-loop system increasing towards infinity as the time goes to infinity and the...
Control systems utilizing wireless sensor and actuator networks can be severely affected by the properties of the wireless links. Radio fading and interference may cause communication outage of several samples in situations when the radio environment is noisy and low transmission power is desirable. We propose a method to compensate for outages by introducing a predictive outage compensator (POC),...
The problem of model reduction by moment matching for switched power converters described in so-called port controlled Hamiltonian form is addressed and solved using the recently introduced notion of moment for nonlinear systems. The theory is illustrated by means of simulations on a three-phase rectifier with LCL filter.
The paper concerns the identification of the multiple-input multiple-output (MIMO) Wiener system consisting of a linear subsystem followed by a static nonlinearity. Based on Fourier transform, the coefficient matrices of the linear subsystem is recursively estimated by stochastic approximation based principal component analysis (SABPCA) method with random inputs with possibly non-Gaussian distribution...
This paper discusses the development of a recursive estimator which systematically arrives at sparse parameter estimates. Prior work achieved this by utilizing a Gaussian sum filter. This paper shows the relationship between the implementation using a Gaussian sum filter, where the mean and covariance of each component is propagated, and the equivalent representation using an information filter. We...
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