Agustín Jiménez

An exact bit-parallel algorithm for the maximum clique problem

This paper presents a new exact maximum clique algorithm which improves the bounds obtained in state of the art approximate coloring by reordering the vertices at each step. Moreover, the algorithm can make full use of bit strings to sort vertices in constant time as well as to compute graph transitions and bounds efficiently, exploiting the ability of CPUs to process bitwise operations in blocks of size the ALU register word. As a result it significantly outperforms a current leading algorithm.

Fuzzy controllers: lifting the linear-nonlinear frontier

Abstract This paper brings back some ideas related with the linear analysis of fuzzy controllers. A fuzzy control algorithm does not go further than a non-linear function described by its inference map. Firstly, it is possible to obtain the inference map corresponding to a classical PID controller by choosing adequately the linguistic terms, the membership functions and the table of rules. Then the inverse problem is presented: to obtain the closer PID to a given fuzzy controller. From these ideas, the paper focuses its attention on the obtainment of a useful tool to design fuzzy controllers at least as good as the PID that allows the system to follow a specified behaviour. The next step is to improve the fuzzy controller parameters. Finally, an industrial application of these ideas is shown. The design of a fuzzy controller over a clinker cooler with grill, improving P and PI controllers already functioning, is discussed.

An optimal fuzzy control system in a network environment based on simulated annealing. An application to a drilling process

This paper shows a strategy for the optimal tuning of a fuzzy controller in a networked control system using an offline simulated annealing approach. The optimal tuning of the fuzzy controller using a maximum known delay is based on the integral time absolute error (ITAE) performance index. The goal is to obtain the optimal tuning parameters for the input scaling factors where the ITAE performance index is minimized. In this study, a step change in the force reference signal is considered a disturbance, and the goal is to assess how well the system follows set-point changes using the ITAE criterion. In order to improve the efficiency of high-performance drilling processes while preserving tool life, the current study focuses on the design and implementation of an optimal fuzzy-control system for drilling force. Simulation results demonstrate good convergence properties of the proposed strategy. Experimental tests of the drilling of two materials (GGG40 and 17-4 PH) corroborate the excellent transient response and the minimum overshoot predicted by the simulation results. Thus, the optimal fuzzy control system reduces the influence of the increase in cutting force that occurs at larger drill depths, eliminating the risk of rapid drill wear and catastrophic drill breakage.

The fuzzy Kalman filter: State estimation using possibilistic techniques

A new method to implement fuzzy Kalman filters is introduced. The combination of possibilistic techniques and the extended Kalman filter has special application in fields where inaccurate information is involved. The novelty of this article comes from the fact that by using possibility distributions, instead of Gaussian distributions, a fuzzy description of the expected state and observation is sufficient to obtain a good estimation. Some characteristics of this approach are that uncertainty does not need to be symmetric, and that a wide region of possible values for the expectations is allowed. To implement the algorithm, this approach also contributes a method to propagate uncertainty through the process model and the observation model, based on trapezoidal possibility distributions. Finally, several examples of a real mobile robot moving through a localization process, while using qualitative landmarks, are shown.

Multisensor Fusion: An Autonomous Mobile Robot

A conventional autonomous mobile robot is introduced. The main idea is the integration of many conventional and sophisticated sensor fusion techniques, introduced by several authors in recent years. We show the actual possibility of integrating all these techniques together, rather than analyzing implementation details. The topics of multisensor fusion, observation integration and sensor coordination are widely used throuhout the article. The final goal is to demonstrate the validity of both mathematical and artificial intelligence techniques in guaranteeing vehicle survival in a dynamic environment, while the robot carries out a specific task. We review conventional techniques for the management of uncertainty while we describe an implementation of a mobile robot which combines on-line heterogeneous sensors in its navigation and localisation tasks.

Consistency improvement for SLAM - EKF for indoor environments

The solution to the simultaneous localization and mapping (SLAM) problem using an extended Kalman filter (EKF) is the most extended despite the inconsistency of its estimation, a problem that has been largely avoided in the literature. We review current existing approaches and present novel solutions to this problem that let us to build large monolithic feature based maps of indoor environments

Local maps fusion for real time multirobot indoor simultaneous localization and mapping

This paper presents an implementation of the local maps fusion concept for the simultaneous localization and mapping (SLAM) problem within the extended Kalman filter (EKF) framework. Several problems never addressed before, arise while implementing the solution for indoor environments, and are successfully solved to obtain maps of quite large real indoor environments with more than one robot in real time.

An Emotional Model for a Guide Robot

This paper presents the structure and operation principles of an emotional model. It is a dynamic state-space model where state variables represent the emotional state. Model matrices are time variant. A method based on fuzzy inference systems is developed to calculate the matrix coefficients at each time step. The simulation results of the guide robot case study are presented.

A general methodology for online TS fuzzy modeling by the extended Kalman filter

HighlightsWe present an online fuzzy modeling methodology based on the extended Kalman filter.This methodology can work with noise, is very efficient and completely general.The model can be obtained in a recursive way only based on input-output data.There are no restrictions in the type of membership functions used.Membership functions can even be mixed in the antecedents of the rules. This paper presents an online TS fuzzy modeling general methodology based on the extended Kalman filter. The model can be obtained in a recursive way only based on input-output data. The methodology can work online with the system, properly in the presence of noise, is very efficient computationally and completely general. It is general in the sense theorically there are no restrictions neither in the number of inputs nor outputs, neither in the type nor distribution of membership functions used (which can even be mixed in the antecedents of the rules). Some examples and comparisons with other online fuzzy identification models from signals are provided to illustrate the skill of the online identification of the proposed methodology.

Efficient Search Using Bitboard Models

This paper shows a way to speed up search by using an encoding at bit level to model a particular domain. A bitboard is an unsigned integer whose bits have been given an interpretation in the world of discourse. In models encoded in such a way, states will be described internally as a set of bitboard tuples, whilst operators which allow for transitions between states are essentially bitwise operations over elements belonging to that set. Given a 64-bit processor word, for each transition it would be theoretically possible to reach another state 64 times faster than with a normal encoding, fast transitions being one of the main issues for efficient search algorithms. We have analysed some other key issues related to efficient bitboard model design and formalised the concepts of well formed heuristics and bitboard guides. We have used this approach to solve instances of the maximum clique problem thus increasing the performance of one of the fastest algorithms known in the domain for optimal search