Moderating effects of management control systems and innovation on performance. Simple methods for correcting the effects of measurement error for interaction effects in small samples

In the accounting literature, interaction or moderating effects are usually assessed by means of OLS regression and summated rating scales are constructed to reduce measurement error bias. Structural equation models and two-stage least squares regression could be used to completely eliminate this bias, but large samples are needed. Partial Least Squares are appropriate for small samples but do not correct measurement error bias. In this article, disattenuated regression is discussed as a small sample alternative and is illustrated on data of Bisbe and Otley (in press) that examine the interaction effect of innovation and style of use of budgets on performance. Sizeable differences emerge between OLS and disattenuated regression

Studies about the atomic capabilities concept for linear control systems in physical multi-agent environments

This paper shows the impact of the atomic capabilities concept to include control-oriented knowledge of linear control systems in the decisions making structure of physical agents. These agents operate in a real environment managing physical objects (e.g. their physical bodies) in coordinated tasks. This approach is presented using an introspective reasoning approach and control theory based on the specific tasks of passing a ball and executing the offside manoeuvre between physical agents in the robotic soccer testbed. Experimental results and conclusions are presented, emphasising the advantages of our approach that improve the multi-agent performance in cooperative systems

Development of an air-scour control system for membrane bioreactors

The thesis involves the development and implementation of a new and robust control system based on permeability trends but at the same time capable of reducing aeration proportionally to permeate flux. Permeability was made a key parameter for directly comparing temporary changes in membrane performance. Transmembrane pressure and flux were gathered every 10 seconds and permeability values were automatically calculated; different mathematical algorithms were applied for the signal filtering of on-line data. Short term and long term permeability trends were compared once a day, and a control action was applied proportionally to the short term/long term permeability ratio without exceeding the aeration flow recommended by the membrane suppliers.

Algunos desarrollos basados en el JUMP para el apoyo logístico y control de calidad en las operaciones de recogida de información estadística

Exhaustive statistical information-gathering operations pose major logistical challenges. By using GISs, managing the associated information becomes simpler, and monitoring the quality control of the information gathered can be stricter

A survey on voltage sag events in power systems

This paper aims to survey the techniques and methods described in literature to analyse and characterise voltage sags and the corresponding objectives of these works. The study has been performed from a data mining point of view

Application for fault location in electrical power distribution systems

Fault location has been studied deeply for transmission lines due to its importance in power systems. Nowadays the problem of fault location on distribution systems is receiving special attention mainly because of the power quality regulations. In this context, this paper presents an application software developed in Matlabtrade that automatically calculates the location of a fault in a distribution power system, starting from voltages and currents measured at the line terminal and the model of the distribution power system data. The application is based on a N-ary tree structure, which is suitable to be used in this application due to the highly branched and the non- homogeneity nature of the distribution systems, and has been developed for single-phase, two-phase, two-phase-to-ground, and three-phase faults. The implemented application is tested by using fault data in a real electrical distribution power system

Control de posició del robot wifibot

Aquest projecte pretén presentar de forma clara i detallada l’estructura i el funcionament del robot així com dels components que el conformen. Aquesta informació és de vital importància a l’hora de desenvolupar aplicacions per al robot. Un cop descrites les característiques del robot s’analitzaran les eines necessàries i/o disponibles per poder desenvolupar programari per cada nivell de la forma més senzilla i eficient possible. Posteriorment s’analitzaran els diferents nivells de programació i se’n contrastaran els avantatges i els inconvenients de cada un. Aquest anàlisi es començarà fent pel nivell més alt i anirà baixant amb la intenció de no entrar en nivells més baixos del necessari. Baixar un nivell en la programació suposa haver de crear aplicacions sempre compatibles amb els nivells superiors de forma que com més es baixa més augmenta la complexitat. A partir d’aquest anàlisi s’ha arribat a la conclusió que per tal d’aprofitar totes les prestacions del robot és precís arribar a programar en el nivell més baix del robot. Finalment l’objectiu és obtenir una sèrie de programes per cada nivell que permetin controlar el robot i fer-lo seguir senzilles trajectòries

Millora experimental de les lleis de control predictiu aplicades sobre la plataforma PRIM I, per el seguiment de trajectòries

Aquest projecte s’aplica sobre el robot PRIM (Plataforma Robotitzada d’Informació Multimèdia), un robot autònom no humanoide creat el 2004 per Ateneu Informàtic (AI) que permet realitzar trajectòries 2D gràcies a un sistema de tracció format per dues rodes motrius propulsades independentment. La plataforma PRIM és controlada a partir del control predictiu, aquest control es va implementar en un projecte anterior, creat per l’Alexandre Blasco Gutierrez i titulat “Implementació de tècniques MPC (Model Predictiu Control) sobre la plataforma PRIM I”. El que es pretén en aquest projecte és millorar els resultats obtinguts en el passat projecte reformulant la llei de control i analitzar les discrepàncies obtingudes en les metodologies que s’utilitzen per minimitzar la funció de costos a partir de simulacions de trajectòries

Predicting overall service quality: a structural equation modelling approach

In this article, the results of a modified SERVQUAL questionnaire (Parasuraman et al., 1991) are reported. The modifications consisted in substituting questionnaire items particularly suited to a specific service (banking) and context (county of Girona, Spain) for the original rather general and abstract items. These modifications led to more interpretable factors which accounted for a higher percentage of item variance. The data were submitted to various structural equation models which made it possible to conclude that the questionnaire contains items with a high measurement quality with respect to five identified dimensions of service quality which differ from those specified by Parasuraman et al. And are specific to the banking service. The two dimensions relating to the behaviour of employees have the greatest predictive power on overall quality and satisfaction ratings, which enables managers to use a low-cost reduced version of the questionnaire to monitor quality on a regular basis. It was also found that satisfaction and overall quality were perfectly correlated thus showing that customers do not perceive these concepts as being distinct

Autonomous underwater vehicle control using reinforcement learning policy search methods

Autonomous underwater vehicles (AUV) represent a challenging control problem with complex, noisy, dynamics. Nowadays, not only the continuous scientific advances in underwater robotics but the increasing number of subsea missions and its complexity ask for an automatization of submarine processes. This paper proposes a high-level control system for solving the action selection problem of an autonomous robot. The system is characterized by the use of reinforcement learning direct policy search methods (RLDPS) for learning the internal state/action mapping of some behaviors. We demonstrate its feasibility with simulated experiments using the model of our underwater robot URIS in a target following task

Towards Direct Policy Search Reinforcement Learning for Robot Control

This paper proposes a high-level reinforcement learning (RL) control system for solving the action selection problem of an autonomous robot. Although the dominant approach, when using RL, has been to apply value function based algorithms, the system here detailed is characterized by the use of direct policy search methods. Rather than approximating a value function, these methodologies approximate a policy using an independent function approximator with its own parameters, trying to maximize the future expected reward. The policy based algorithm presented in this paper is used for learning the internal state/action mapping of a behavior. In this preliminary work, we demonstrate its feasibility with simulated experiments using the underwater robot GARBI in a target reaching task

Model-based objects recognition in industrial environments for autonomous vehicles control

Behavior-based navigation of autonomous vehicles requires the recognition of the navigable areas and the potential obstacles. In this paper we describe a model-based objects recognition system which is part of an image interpretation system intended to assist the navigation of autonomous vehicles that operate in industrial environments. The recognition system integrates color, shape and texture information together with the location of the vanishing point. The recognition process starts from some prior scene knowledge, that is, a generic model of the expected scene and the potential objects. The recognition system constitutes an approach where different low-level vision techniques extract a multitude of image descriptors which are then analyzed using a rule-based reasoning system to interpret the image content. This system has been implemented using a rule-based cooperative expert system

WMR navigation using local potential field corridors and narrow local occupancy grid perception

Path planning and control strategies applied to autonomous mobile robots should fulfil safety rules as well as achieve final goals. Trajectory planning applications should be fast and flexible to allow real time implementations as well as environment interactions. The methodology presented uses the on robot information as the meaningful data necessary to plan a narrow passage by using a corridor based on attraction potential fields that approaches the mobile robot to the final desired configuration. It employs local and dense occupancy grid perception to avoid collisions. The key goals of this research project are computational simplicity as well as the possibility of integrating this method with other methods reported by the research community. Another important aspect of this work consist in testing the proposed method by using a mobile robot with a perception system composed of a monocular camera and odometers placed on the two wheels of the differential driven motion system. Hence, visual data are used as a local horizon of perception in which trajectories without collisions are computed by satisfying final goal approaches and safety criteria

Knowledge integration within an applied mobile robot summer course

This paper presents the use of a mobile robot platform as an innovative educational tool in order to promote and integrate different curriculum knowledge. Hence, it is presented the acquired experience within a summer course named ldquoapplied mobile roboticsrdquo. The main aim of the course is to integrate different subjects as electronics, programming, architecture, perception systems, communications, control and trajectory planning by using the educational open mobile robot platform PRIM. The summer course is addressed to a wide range of student profiles. However, it is of special interests to the students of electrical and computer engineering around their final academic year. The summer course consists of the theoretical and laboratory sessions, related to the following topics: design & programming of electronic devices, modelling and control systems, trajectory planning and control, and computer vision systems. Therefore, the clues for achieving a renewed path of progress in robotics are the integration of several knowledgeable fields, such as computing, communications, and control sciences, in order to perform a higher level reasoning and use decision tools with strong theoretical base

Local model predictive control experiences with differential driven wheeled mobile robots

This work extends a previously developed research concerning about the use of local model predictive control in differential driven mobile robots. Hence, experimental results are presented as a way to improve the methodology by considering aspects as trajectory accuracy and time performance. In this sense, the cost function and the prediction horizon are important aspects to be considered. The aim of the present work is to test the control method by measuring trajectory tracking accuracy and time performance. Moreover, strategies for the integration with perception system and path planning are briefly introduced. In this sense, monocular image data can be used to plan safety trajectories by using goal attraction potential fields