The aim of this study is to employ the state convergence scheme to control a nonlinear teleoperation system represented by TS fuzzy models and then to extend this scheme for the case of teleoperation systems having more than one master and/or slave devices. To achieve the first objective, a parallel distributed compensation (PDC) type control law is introduced to close the feedback loop around the master and slave devices and method of state convergence is applied to solve for the control gains. The second objective is achieved by proposing an alpha modified version of the standard state convergence scheme which provides a framework to combine the commands from all the master units to affect the slave units. The proposed works are validated afterwards in MATLAB/Simulink environment using single and multi-degree-of-freedom (DoF) manipulators.

Computationally fast neuro-fuzzy networks are proposed with hybridization of adaptive decayed brain emotional learning (ADBEL) and neo-fuzzy networks. Few chaotic time series namely the Mackey glass, Lorenz, Rossler, the Disturbance storm time, Narendra dynamic plant identification as well as pattern recognition problems such as breast cancer classification are used to evaluate the performance of the proposed networks in terms of the root mean squared error and correlation coefficient criterions using MATLAB ^® programming environment.

We present the design of an intelligent autonomous vehicle which can navigate in noisy and unknown environments without hitting the obstacles in its way. The vehicle is made intelligent with the help of two multilayer feed forward neural network controllers namely ‘Hurdle Avoidance Controller’ and ‘Goal Reaching Controller’ with back error propagation as training algorithm. Hurdle avoidance controller ensures collision free motion of mobile robot while goal reaching controller helps the mobile robot in reaching the destination. Both these controllers are trained offline with the data obtained during experimental run of the robot and implemented with low cost AT89C52 microcontrollers. The computational burden on microcontrollers is reduced by using piecewise linearly approximated version of tangent-sigmoid activation function of neurons. The vehicle with the proposed controllers is tested in outdoor complex environments and is found to reach the set targets successfully.

Design and implementation of fuzzy logic controller for mobile robot navigation in unknown environments is presented. The task of navigation is divided into three behaviors namely hurdle avoidance, wall following and goal seeking. The outputs from these behaviors are combined to generate collision free motion of robot amongst obstacles in reaching the target. The controllers for these behaviors are designed using Fuzzy Logic toolbox of MATLAB® and their implementation is realized with readily available and inexpensive AT89C52 microcontrollers. Finally, the robot with these controllers is tested in indoor environments containing obstacles with changing destination places and is found to reach the set targets successfully which shows the validity of the designed controllers in achieving the required task.

This study proposes and implements a solution for enhancing public transportation management services based on GPS and GSM in Punjab province of Pakistan. The system consists of four modules: BUS Station Module, In-BUS Module, BASE Station Module and BUS Stop Module. Equipped with PC and GSM modem, BUS Station Module sends the initialization information containing the bus number and license plate number to In-BUS Module and BASE Station Module using SMS. The microcontroller based In-BUS Module consisting mainly of a GPS receiver and GSM modem then starts transmitting its location and number of passengers to BASE Station Module. BASE Station Module equipped with a microcontroller unit and GSM modems interfaced to PCs is designed to keep track record of every bus, processes user request about a particular bus location out of BUS Station and updates buses location on bus stops. BUS Stop Module is installed at every bus stop and consists of a GSM modem, memory unit and dot matrix display all interfaced to a microcontroller. This module receives buses location information coming towards that stop from BASE Station module and displays the information on a dot matrix display. A per stop statistical analysis is carried out based on the number of passengers and a recommendation report along with this analysis is sent to Punjab Government Transportation Department to have a check on the performance and services offered by transporters to common people. The results have shown that the developed system is useful for facilitating people using public transportation services.

In this research, a nonlinear least squares optimization method is employed to optimize the performance of pole-zero-cancellation (PZC)-based digital controllers applied to a switching converter. An extensively used step-down converter operating at 1000 kHz is considered as a plant. In the PZC technique, the adverse effect of the (unwanted) poles of the buck converter power stage is diminished by the complex or real zeros of the compensator. Various combinations of the placement of the compensator zeros and poles can be considered. The compensator zeros and poles are nominally/roughly placed while attempting to cancel the converter poles. Although PZC techniques exhibit satisfactory performance to some extent, there is still room for improvement of the controller performance by readjusting its poles and zeros. The (nominal) digital controller coefficients thus obtained through PZC techniques are retuned intelligently through a nonlinear least squares (NLS) method using the Levenberg-Marquardt (LM) algorithm to ameliorate the static and dynamic performance while minimizing the sum of squares of the error in a quicker way. Effects of nonlinear components such as delay, ADC/DAC quantization error, and so forth contained in the digital control loop on performance and loop stability are also investigated. In order to validate the effectiveness of the optimized PZC techniques and show their supremacy over the traditional PZC techniques and the ones optimized by genetic algorithms (GAs), simulation results based on a MATLAB/Simulink environment are provided. For experimental validation, rapid hardware-in-the-loop (HiL) implementation of the compensated buck converter system is also performed