Ahmed A. Bahnasawi

Solving Riccati differential equation using Adomian's decomposition method

In this paper, we suggest a method to solve the matrix Riccati differential equation. The suggested method, which we called multistage Adomians decomposition method (MADM), can be considered as an extension of the Adomians decomposition method (ADM) which is very efficient in solving a variety of differential and algebraic equations. The solution is introduced in a recursive form which can be used to obtain the solution for the whole time horizon. Comparisons are made between MADM and the exact solution and further between MADM and different numerical methods.

Asymptotic stability for a class of linear discrete systems with bounded uncertainties

The problem of stabilizing linear discrete systems with additive-type bounded uncertainties is considered. It is established that when matching conditions hold, a two-part feedback control can be designed: a linear part to assign the eigenvalues within the unit cycle and a nonlinear part to ensure the uniform asymptotic stability for arbitrary initial conditions and bounded admissible uncertainties. >

Adaptive model-following control based on variable structure systems

This paper considers a class of multivariable linear time-varying systems which have a fast and wide range of unknown parameter variations, but whose boundaries are known. For such systems, an adaptive model-following control based on variable structure theory, is presented. An optimal observer, based on the sliding mode in variable structure systems, is then introduced. It has been shown that the proposed control structure guarantees both the system asymptotic stability and the error transient shaping capability. The application of the developed control scheme is demonstrated using a typical example.

Variable structure control of non-linear adaptive model-following systems

The purpose of this paper is to design a variable structure controller (VSC) for a class of non-linear model-following systems, when subjected to fast and wide ranges of unknown-but-bounded parameter variations and disturbances. It has been shown that the use of discontinuous VSC may produce what is called chattering phenomena. By adopting a boundary layer controller, such chattering can be removed. The controller gains are then adjusted in such a way that the global asymptotic stability of the overall system is assured. An illustrative example for controlling a non-linear adaptive model-following system is carried out to demonstrate the design procedure.

Logical radial basis function networks a hybrid intelligent model for function approximation

Abstract The aim of this article is to introduce a new approach for fuzzy neural network models which can be used effectively in function approximation problems. The proposed model is introduced as an adaptive two-level fuzzy inference system. The architecture of the model is basically a two-layer network of new types of fuzzy-neurons which act as fuzzy IF–THEN rules. The model can be considered as a logical version of the Radial Basis Function networks (RBF). Genetic Algorithms have been adopted as the learning mechanism of the proposed model. Simulations show both highly nonlinear mapping and reasoning capabilities together with simpler structure and better performance when compared with classical neural networks.

Comments on "Asymptotic stability for a class of linear discrete systems with bounded uncertainties" [with reply]

In the above-named work, M.S. Mahmoud and A.A. Bahnasawi (see ibid., vol.33, p.572-5, June 1988) present a class of feedback controllers and claims that these controllers yield a closed-loop system which is asymptotically stable for all allowable uncertainties. The commenter claims that the results they present are incorrect and indicates why he thinks so. The authors reply point by point to the commenters remarks. >

Sensitivity analysis of machine interference in manufacturing systems

Abstract A class of manufacturing systems is presented in which the machine interference problem plays an important role in production. We consider a single server (robot) in addition to two types of random machine stoppages with priorities. A detailed analysis has been focused on two measures: robot utilization and machine efficiency. It has been shown that one has to make a compromise between the above two sensitive measures. We have further computed the optimum number of machines that can be served by a robot. A novel optimization technique is used to fulfill this requirement. The simulation results reveal that the number of machines as well as the service rate can be utilized as decision variables in the problem at hand.

A novel framework for hybrid intelligent systems

The aim of this paper is to generalize the approaches used for developing hybrid intelligent systems based on integration of neural networks, fuzzy logic and genetic algorithms. The paper introduces the concepts of intelligent artificial life system (IALS) space as a generalized conceptual space which represents a framework for all possible integration schemes of such intelligence technologies. Concepts like order of intelligence, degree of intelligence and types of hybrid coupling are also illustrated. Based on such concepts, a proposed philosophy for hybrid integration schemes in the IALS space is presented and discussed.

Adaptive model-following controller for robotic manipulators

A nonlinear state-space model representing the robot dynamics and containing a disturbance term due to gravitational loading is presented. An adaptive model-following control problem satisfying the matching conditions is formulated using a suitable linear time-invariant reference model. The control input is designed to have two components: a non-adaptive linear component to do the task of model-following and a nonlinear unit-vector component based on hyperstability theory to do the adaptive task. An additional integral feedback term is further added and then the overall asymptotic hyperstability is established. Simulation experiments on the first three joints of a PUMA 560 robot manipulator have indicated the potential of our design approach.

Indirect discrete-time adaptive algorithm for manipulator control

Abstract An adaptive controller design is proposed for discrete-time robotic control. The position of the robot arm is shown to converge to a desired point through two control loops. The first loop is an indirect adaptive perturbation controller based on the decoupled dynamics approach and using a perturbation model for the torque generation. The second loop generates the nominal torque component through a nonlinear controller representing the inverse manipulator dynamics. Simulation results on a typical three-link manipulator have indicated the potential and applicability of the developed design.