Fault-accommodation with intelligent sensors

Optimal sensor fault-accommodation is considered for faults modelled by an increase in measurement noise. This noise is taken to be bounded and its probabilistic properties unknown. It is assumed that intelligent (e.g. self-validating) instrumentation is in use and estimates of the noise bounds are available. The fault-tolerant controller is designed to optimize a noise rejection and a nominal reference tracking index and leads to a mixed norm minimization problem (l₁/l₂). We exploit known results and a particular feedback configuration to show that it is possible to optimize simultaneously without a trade-off the two performance indices. The results are applied to systems where the presence of auxiliary measurements allows for an optimal fault-accommodation strategy. Using properties of the optimal solution, we define a factorization for the optimal controller alternative to the Youla parametrization, leading to an algorithm which is optimal, transparent and efficient.     

Tracking trajectories of the cart-pendulum system

The problem of tracking a periodic trajectory of the well-known cart-pendulum system is solved. After a change of coordinates and a change of feedback, the equations of this system are nonlinear but feedforward. This property is extensively used to carry out for this system the design of uniformly asymptotically stabilizing time-varying state feedbacks by using the forwarding approach.     

Bizarre imagery, interference, and distinctiveness.

Previous studies have shown that bizarre and common images produce equivalent levels of recall in unmixed-list designs. Using unmixed lists, we tested the view that bizarre images would be less susceptible than common images to common sources of interference. In all experiments, subjects imaged a list of either bizarre or common sentences and then performed some kind of interfering task before recalling the initial list of sentences. Experiment 1 showed that bizarre images were better accessed than common images after imaging an intervening list of common sentences. Also, components of common images tended to be better recalled than those of bizarre images after imaging an intervening list of bizarre sentences. Experiments 2a and 2b showed that interfering tasks consisting of studying lists of common concrete nouns did not differentially affect memory for bizarre and common images. In Experiment 3, labeling and imaging an interfering list of common pictures produced higher recall of bizarre images. Generally, bizarre images appeared to be less susceptible than common images to interference from certain types of common encodings. Importantly, the superior recall of bizarre images was always due to greater image (sentence) access, whereas higher recall of common images was associated with greater recovery of the image (sentence) constituents. Explanation of the precise pattern of results requires consideration of the distinctive properties of bizarre images. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Algorithm for finding all k nearest neighbors

A very simple algorithm for computing all k nearest neighbors in 2-D is presented. The method does not rely on complicated forms of tessellation, it only requires simple data binning for fast range searching. Its applications range from scattered data interpolation to reverse engineering.     

Scaffolded writing and rewriting in the discipline: A web-based reciprocal peer review system

This paper describes how SWoRD (scaffolded writing and rewriting in the discipline), a web-based reciprocal peer review system, supports writing practice, particularly for large content courses in which writing is considered critical but not feasibly included. To help students gain content knowledge as well as writing and reviewing skills, SWoRD supports the whole cycle of writing, reviews, back-reviews, and rewriting by scaffolding the journal publication process as its authentic practice model. In addition, SWoRD includes algorithms that compute individual reviewer’s review accuracy, which is in turn used to support the various drawbacks of reciprocal peer reviews (e.g., variation in motivation or ability of reviewers). Finally, this paper describes an empirical evaluation showing that the SWoRD approach is effective in improving writing quality in content classes.     

A parametric interpolator with confined chord errors, acceleration and deceleration for NC machining

Parametric interpolation has many advantages over linear interpolation in machining curves. Real time parametric interpolation research so far has addressed achieving a uniform feed rate, confined chord errors and jerk limited trajectory planning. However, simultaneous consideration of confined chord errors that respect the acceleration and deceleration capabilities of the machine has not been attempted. In this paper, the offline detection of feed rate sensitive corners is proposed. The velocity profile in these zones is planned so that chord errors are satisfied while simultaneously accommodating the machine's acceleration and deceleration limits. Outside the zone of the feed rate sensitive corners, the feed rate is planned using the Taylor approximation. Simulation results indicate that the offline detection of feed rate sensitive corners improves parametric interpolation. For real time interpolation, the parametric curve information can be augmented with the detected feed rate sensitive corners that are stored in 2×2 matrices.     

Determination of optimal feedback terminal controllers for general boundary conditions using generating functions

Given a nonlinear system and a performance index to be minimized, we present a general approach to expressing the finite time optimal feedback control law applicable to different types of boundary conditions. Starting from the necessary conditions for optimality represented by a Hamiltonian system, we solve the Hamilton-Jacobi equation for a generating function for a specific canonical transformation. This enables us to obtain the optimal feedback control for fundamentally different sets of boundary conditions only using a series of algebraic manipulations and partial differentiations. Furthermore, the proposed approach reveals an insight that the optimal cost functions for a given dynamical system can be decomposed into a single generating function that is only a function of the dynamics plus a term representing the boundary conditions. This result is formalized as a theorem. The whole procedure provides an advantage over methods rooted in dynamic programming, which require one to solve the Hamilton-Jacobi-Bellman equation repetitively for each type of boundary condition. The cost of this favorable versatility is doubling the dimension of the partial differential equation to be solved.