Khier Benmahammed

A fuzzy-based reactive controller for a non-holonomic mobile robot

Abstract This paper presents the theoretical development of a complete navigation problem of an autonomous mobile robot. The situation for which the vehicle tries to reach the endpoint is treated using a fuzzy logic controller. The problem of extracting the optimized IF–THEN rule base is solved using an evolutionary algorithm. A new approach based on fuzzy concepts is presented in this paper to avoid any collision with the surrounding environment when this latter becomes relatively complex. Simulation results show that the designed fuzzy controller achieves effectively any movement control of the vehicle from its current position to its end motion and without any collision.

State observer based robust adaptive fuzzy controller for nonlinear uncertain and perturbed systems

A robust adaptive fuzzy controller, based on a state observer, for a nonlinear uncertain and perturbed system is presented. The state observer is introduced to resolve the problem of the unavailability of the state variables. Two control signals are added to a basic state feedback control law, deduced from a nominal model, to guarantee the tracking performance in the presence of structural uncertainties and external disturbances. The first control signal is computed from an adaptive fuzzy system and eliminates the effect of structural uncertainties and estimation errors. Updating the adjustable parameters is ensured by a PID law to obtain a fast convergence. Robustness of the closed-loop system is guaranteed by an H/spl infin/ supervisor computed from a Riccati type equation. Simulation example is presented to show the efficiency of the proposed method.

A Two-Layer Robot Controller Design Using Evolutionary Algorithms

The results obtained by a rule-based proportional, integral, derivative (PID) precompensator controller applied to a two-joint manipulator are discussed. The end effector is made to follow a specified trajectory obtained from the inverse kinematics by an appropriate design of a fuzzy control law. The desired trajectory is determined by the values of the joint variables and the structural kinematics parameters of the manipulator. The performance of the PID controller is exploited here to build a fuzzy precompensator that will enhance the conventional PID and to obtain better performances and results. The fuzzy rule base of the precompensator designed is found by associating two evolutionary algorithms that search for the optimal solution.

Activation and Defuzzification Methods for Fuzzy Rule-Based Systems

In this paper, a Selective Inference Engine (SIE) is first proposed. SIE predicts the rules that will be fired, based on an anticipated location procedure, and then performs the inference calculations only on the latter. This anticipated location is based on the projection of the input data on the conditional space of the fuzzy system and the delimitation of the excited region. Then, the fired rules can be aggregated using the appropriate scheme. In the second part of this work, we propose new defuzzification methods which take into account the consequent membership function shapes.

Partial Fraction Decomposition and Correlation Sequence in 2D Systems

In this paper, results of the one-dimensional (1D) digital filtering are extended to the two-dimensional (2D) case. It introduces a technique and an algorithm for the computation of the product H(z1,z2)H(z1−1,z2−1). The technique is used to find a minimum phase transfer function of a 2D system such that the previous product matches a given correlation sequence. The algorithm requires less arithmetic operations than the traditional methods. The former is based on a matrix formulation of the product, which is used to investigate the 2D partial fraction decomposition (PFD) and stability.

A WAVELET-BASED APPROACH FOR DISTURBANCE LINE IDENTIFICATION IN PRINTED CIRCUIT BOARDS

The problem of identifying disturbance lines in printed circuit boards is addressed. Identification is achieved by estimating the disturbance frequency and the separation distance between the coupled lines. Frequency estimation uses a wavelet coefficients thresholding method to reconstruct the interference caused by the disturbance line. The separation distance is computed using two empirical laws based on physical ground and verified by simulation. The performance of the proposed method is illustrated by simulation results.

A wavelet-based approach for crosstalk frequency estimation in printed circuit boards

This paper proposes a wavelet-based approach for frequency estimation of the source of interference in a PCB. The frequency constitutes a relevant information that characterizes the disturbance signal and may lead to the identification of the source of disturbance, we consider two parallel lines on a PCB. A high frequency digital signal is propagating down the first track which induces an electromagnetic interference that affects the signal propagating down the second line. The estimation procedure is based only on the disturbed signal, already available, from which the interference signal is reconstructed by performing a wavelet decomposition at level one. The estimated interference is then appropriately processed to determine its frequency.

Tracking instantaneous frequency using two-sided linear prediction

We consider the problem of estimating of the instantaneous frequency of nonstationary signals. Instead of the usual one-sided linear prediction (OSP), we propose to use the so-called two-sided linear prediction (TSP) approach. In the TSP, the signal is modeled as a linear combination of its past and future values. The vector of prediction coefficients is estimated adaptively using an algorithm based on the least mean square noisy gradient technique. Numerical examples show that TSP requires a smaller order than OSP to achieve better resolution, and consequently is computationally efficient.

Application of the SD to LCTI systems. 1

For pt. 1 see ibid., p. 500-502 (May 2002). This paper presents some of the algorithms used in control theory, but using different frame of work, namely the spectral decomposition (SD) of the state matrix of a linear continuous time invariant (LCTI) system.