Event-triggered state observers for sparse sensor noise/attacks

This paper describes two algorithms for state reconstruction from sensor measurements that are corrupted with sparse, but otherwise arbitrary, 'noise.' These results are motivated by the need to secure cyber-physical systems against a malicious adversary that can arbitrarily corrupt sensor measurements. The first algorithm reconstructs the state from a batch of sensor measurements while the second algorithm is able to incorporate new measurements as they become available, in the spirit of a Luenberger observer. A distinguishing point of these algorithms is the use of event-triggered techniques to improve the computational performance of the proposed algorithms

The Effect of Decomposing Organic Matter on Zinc Level in Soil and Plants

That proportion of the total zinc (Zn) in the soil that is available to plants is variable, and little is known about the various forms of Zn or even the extent to which it occurs. Because of the complexity of the problem, most workers have approached the problem of availability of Zn to plants from the opposite point of view, that is, the forms in which the added or available Zn becomes unavailable

Two-Level Lattice Neural Network Architectures for Control of Nonlinear Systems

In this paper, we consider the problem of automatically designing a Rectified Linear Unit (ReLU) Neural Network (NN) architecture (number of layers and number of neurons per layer) with the guarantee that it is sufficiently parametrized to control a nonlinear system. Whereas current state-of-the-art techniques are based on hand-picked architectures or heuristic-based search to find such NN architectures, our approach exploits a given model of the system to design an architecture; as a result, we provide a guarantee that the resulting NN architecture is sufficient to implement a controller that satisfies an achievable specification. Our approach exploits two basic ideas. First, we assume that the system can be controlled by a Lipschitz-continuous state-feedback controller that is unknown but whose Lipschitz constant is upper-bounded by a known constant; then using this assumption, we bound the number of affine functions needed to construct a Continuous Piecewise Affine (CPWA) function that can approximate the unknown Lipschitz-continuous controller. Second, we utilize the authors' recent results on the Two-Level Lattice (TLL) NN architecture, a novel NN architecture that was shown to be parameterized directly by the number of affine functions that comprise the CPWA function it realizes. We also evaluate our method by designing a NN architecture to control an inverted pendulum

Spectral Clustering for Optical Confirmation and Redshift Estimation of X-ray Selected Galaxy Cluster Candidates in the SDSS Stripe 82

We develop a galaxy cluster finding algorithm based on spectral clustering technique to identify optical counterparts and estimate optical redshifts for X-ray selected cluster candidates. As an application, we run our algorithm on a sample of X-ray cluster candidates selected from the third XMM-Newton serendipitous source catalog (3XMM-DR5) that are located in the Stripe 82 of the Sloan Digital Sky Survey (SDSS). Our method works on galaxies described in the color-magnitude feature space. We begin by examining 45 galaxy clusters with published spectroscopic redshifts in the range of 0.1 to 0.8 with a median of 0.36. As a result, we are able to identify their optical counterparts and estimate their photometric redshifts, which have a typical accuracy of 0.025 and agree with the published ones. Then, we investigate another 40 X-ray cluster candidates (from the same cluster survey) with no redshift information in the literature and found that 12 candidates are considered as galaxy clusters in the redshift range from 0.29 to 0.76 with a median of 0.57. These systems are newly discovered clusters in X-rays and optical data. Among them 7 clusters have spectroscopic redshifts for at least one member galaxy.Comment: 15 pages, 7 figures, 3 tables, 1 appendix, Accepted by Journal of "Astronomy and Computing

Sensorless action-reaction-based residual vibration suppression for multi-degree-of-freedom flexible systems

This paper demonstrates the feasibility of controlling motion and vibration of a class of flexible systems with inaccessible or unknown outputs through measurements taken from their actuators which are used as single platforms for measurements, whereas flexible dynamical systems are kept free from any attached sensors. Based on the action reaction law of dynamics, the well-known disturbance observer is used to determine the incident reaction forces from these dynamical systems on the interface planes with their actuators. Reaction forces are considered as feedback-like signals that can be used as alternatives to the inaccessible system outputs. The sensorless action reaction based motion and vibration control technique is implemented on a flexible system with finite modes and all results are verified experimentally

A multistage hierarchical algorithm for hand shape recognition

This paper represents a multistage hierarchical algorithm for hand shape recognition using principal component analysis (PCA) as a dimensionality reduction and a feature extraction method. The paper discusses the effect of image blurring to build data manifolds using PCA and the different ways to construct these manifolds. In_order to classify the hand shape of an incoming sign object and to be invariant to linear transformations like translation and rotation, a multistage hierarchical classifier structure is used. Computer generated images for different Irish Sign Language shapes are used in testing. Experimental results are given to show the accuracy and performance of the proposed algorithm

Sensorless torque/force control

Motion control systems represent a main subsystem for majority of processing systems that can be found in the industrial sector. These systems are concerned with the actuation of all devices in the manufacturing process such as machines, robots, conveyor systems and pick and place mechanisms such that they satisfy certain motion requirements, e.g., the pre specified reference trajectories are followed along with delivering the proper force or torque to the point of interest at which the process occurs. In general, the aim of force/torque control is to impose the desired force on the environment even if the environment has dynamical motion

Securing state reconstruction under sensor and actuator attacks: Theory and design

This paper discusses the problem of reconstructing the state of a linear time invariant system when some of its actuators and sensors are compromised by an adversarial agent. In the model considered in this paper, the adversarial agent attacks an input (output) by manipulating its value arbitrarily, i.e., we impose no constraints (statistical or otherwise) on how control commands (sensor measurements) are changed by the adversary other than a bound on the number of attacked actuators and sensors In the first part of this paper, we introduce the notion of sparse strong observability and we show that is a necessary and sufficient condition for correctly reconstructing the state despite the considered attacks. In the second half of this work, we propose an observer to harness the complexity of this intrinsically combinatorial problem, by leveraging satisfiability modulo theory solving. Numerical simulations illustrate the effectiveness and scalability of our observer