Robust H-infinity state estimation for discrete-time state-delayed and measurement-delayed systems with uncertainties

published_or_final_versio

Stability analysis for dynamical neural network systems

In this paper, the small gain theorem will be used to establish a criterion for the stability of a feedback system containing a feedforward neural network. A method for the determination of the gain of a piecewise-linear feedforward neural network is introduced and applied to the stability analysis for a control system consisting of a LTI SISO system with a dynamic ANN controller.published_or_final_versio

Matching patterns of line segments by eigenvector decomposition

This paper presents an algorithm for matching line segments in two images which are related by an affine transformation. Images are represented as patterns Of line segments. Areas defined between line segments are used to describe a line pattern in the form of a proximity matrix. Matches are determined by comparing the feature vectors obtained from eigenvalue decomposition of the proximity matrices. Reliable matches of line segments are obtained in both synthetic and real images.published_or_final_versio

Detecting outlier samples in microarray data

In this paper, we address the problem of detecting outlier samples with highly different expression patterns in microarray data. Although outliers are not common, they appear even in widely used benchmark data sets and can negatively affect microarray data analysis. It is important to identify outliers in order to explore underlying experimental or biological problems and remove erroneous data. We propose an outlier detection method based on principal component analysis (PCA) and robust estimation of Mahalanobis distances that is fully automatic. We demonstrate that our outlier detection method identifies biologically significant outliers with high accuracy and that outlier removal improves the prediction accuracy of classifiers. Our outlier detection method is closely related to existing robust PCA methods, so we compare our outlier detection method to a prominent robust PCA method. Copyright ©2009 The Berkeley Electronic Press. All rights reserved.published_or_final_versio

Image noise induced errors in camera positioning

The problem of evaluating worst-case camera positioning error induced by unknown-but-bounded (UBB) image noise for a given object-camera configuration is considered. Specifically, it is shown that upper bounds to the rotation and translation worst-case error for a certain image noise intensity can be obtained through convex optimizations. These upper bounds, contrary to lower bounds provided by standard optimization tools, allow one to design robust visual servo systems. © 2007 IEEE.published_or_final_versio

Modelling and control of a 2-DOF planar parallel manipulator for semiconductor packaging systems

A novel direct-drive planar parallel manipulator for high-speed and high-precision semiconductor packaging systems is presented. High precision kinematics design, significant redaction on moving mass and driving power of the actuators over traditional XY motion stages are the benefits of the proposed manipulator. The mathematical model of the manipulator is obtained using the Newton-Enter method and a practical model-based control design approach is employed to design the PID computed-torque controller. Experimental results demonstrate that the proposed planar parallel manipulator has significant improvements on motion performance in terms of positioning accuracy, settling time and stability when compared with traditional XY stages. This shows that the proposed planar parallel manipulator can provide a superior alternative for replacing traditional XY motion stages in high precision low-payload applications. © 2005 IEEE.published_or_final_versio

An integrated approach to feature selection and classification for microarray data with outlier detection

postprintThe 8th Annual International Conference on Computational Systems Bioinformatics (CSB 2009), Stanford University, 10-13 August 2009

Global path-planning for constrained and optimal visual servoing

Visual servoing consists of steering a robot from an initial to a desired location by exploiting the information provided by visual sensors. This paper deals with the problem of realizing visual servoing for robot manipulators taking into account constraints such as visibility, workspace (that is obstacle avoidance), and joint constraints, while minimizing a cost function such as spanned image area, trajectory length, and curvature. To solve this problem, a new path-planning scheme is proposed. First, a robust object reconstruction is computed from visual measurements which allows one to obtain feasible image trajectories. Second, the rotation path is parameterized through an extension of the Euler parameters that yields an equivalent expression of the rotation matrix as a quadratic function of unconstrained variables, hence, largely simplifying standard parameterizations which involve transcendental functions. Then, polynomials of arbitrary degree are used to complete the parametrization and formulate the desired constraints and costs as a general optimization problem. The optimal trajectory is followed by tracking the image trajectory with an IBVS controller combined with repulsive potential fields in order to fulfill the constraints in real conditions. © 2007 IEEE.published_or_final_versio

Investigating the load flow equations in power systems via LMI-based techniques

Solving the load flow equations is an important problem in power systems. This paper proposes an approach for addressing this problem via a convex optimization with LMI constraints. This approach ensures to find all solutions provided that the dimension of a linear space provided by the optimization is smaller than a known threshold. Then, this paper considers the characterization of the set of admissible power, in particular the computation of the largest admissible power, which amounts to solving a nonconvex optimization problem. It is shown that an upper bound of the sought power can be obtained via convex LMI optimization. Moreover, a necessary and sufficient condition for establishing whether the upper bound is tight or not is provided. Some numerical examples illustrate the proposed approach. ©2009 ACA.published_or_final_versionThe 7th Asian Control Conference (ASCC 2009), Hong Kong, China, 27-29 August 2009. In Proceedings of the Asian Control Conference, 2009, p. 418-42

Robust mixed H2/H∞ filtering with regional pole assignment for uncertain discrete-time systems

This paper deals with the robust mixed H2/H∞ filtering problem with regional pole assignment for linear uncertain discrete-time systems in the presence of two sets of exogenous disturbance inputs. A general framework for solving this problem is established using a linear matrix inequality (LMI) approach in conjunction with regional pole constraints, and H2 and H∞ optimization characterization. Necessary and sufficient conditions for the solvability of the problem are given in terms of a set of feasible LMIs. A numerical example is provided to illustrate the effectiveness of the proposed design algorithm.published_or_final_versio