This thesis reports the identification of linear and nonlinear handling models for road vehicles starting from structural identifiability analysis, continuing with the experiments to acquire data on a vehicle equipped with a sensor set and data acquisition system and ending with the estimation of parameters using the collected data. The 2 degrees of freedom (dof) linear model structure originates from the well known linear bicycle model that is frequently used in handling analysis of road vehicles. Physical parameters of the bicycle model structure are selected as the unknown parameter set that is to be identified. Global identifiability of the model structure is analysed, in detail, and concluded according to various available sensor sets. Physical parameters of the bicycle model structure are estimated using prediction error estimation method. Genetic algorithms are used in the optimization phase of the identification algorithm to overcome the difficulty in the selection of initial values for parameter estimates. Validation analysis of the identified model is also presented. Identified model is shown to track the system response successfully. Following the linear model identification, identification of 3 dof nonlinear models are studied. Local identifiability analysis is done and optimal input is designed using the same procedure for linear model structure identification. Practical identifiability analysis is performed using Fisher Information Matrix. Physical parameters are estimated using the data from simulated experiments. High accuracy estimates are obtained. Methodology for nonlinear handling model identification is presented.

Active safety systems for road vehicles make a crucial preventive contribution to road safety. In recent years, technological developments and the increasing demand for road safety have resulted in the integration and cooperation of these individual active safety systems. Traction control system (TCS) is one of these individual systems, which is capable of inhibiting wheel-spin during acceleration of the vehicle on slippery surfaces. In this thesis, design methodology and simulation results of a traction control system for four wheeled road vehicles are presented. The objective of the TCS controller is basically to improve directional stability, steer-ability and acceleration performance of vehicle by controlling the wheel slip during acceleration. In this study, the designed traction control system based on fuzzy logic is composed of an engine torque controller and a slip controller. Reference wheel slip values were estimated from the longitudinal acceleration data of the vehicle. Engine torque controller determines the throttle opening angle corresponding to the desired wheel torque, which is determined by a slip controller to track the reference slip signals. The wheel torques delivered by the engine are compensated by brake torques according to the desired wheel torque determined by the slip controller. Performance of the TCS controller was analyzed through several simulations held in MATLAB/Simulink for different road conditions during straight line acceleration and combined acceleration and steering. For simulations, an 8 DOF nonlinear vehicle model with nonlinear tires and a 2 DOF nonlinear engine model were built.

In this study a universal command generator has been designed for robotics and CNC machinery. Encoding techniques has been utilized in order to represent the commands and their efficiencies have been discussed. The developed algorithm generates the trajectory of the end-effector with linear and circular interpolation in an offline fashion, the corresponding joint states and their error envelopes are computed with the utilization of a numerical inverse kinematic solver with a predefined precision. Finally, the command encoder employs the resulting data and produces the representation of positions in joint space with using proposed encoding techniques depending on the error tolerance for each joint. The encoding methods considered in this thesis are: Lossless data compression via higher order finite difference, Huffman Coding and Arithmetic Coding techniques, Polynomial Fitting methods with Chebyshev, Legendre and Bernstein Polynomials and finally Fourier and Wavelet Transformations. The algorithm is simulated for Puma 560 and Stanford Manipulators for a trajectory in order to evaluate the performances of the above mentioned techniques (i.e. approximation error, memory requirement, number of commands generated). According to the case studies, Chebyshev Polynomials has been determined to be the most suitable technique for command generation. Proposed methods have been implemented in MATLAB environment due to its versatile toolboxes. With this research the way to develop an encoding/decoding standard for an advanced command generator scheme for computer numerically controlled (CNC) machines in the near future has been paved.

This study covers the sliding mode control design for a class of nonlinear systems, where the control input affects the state of the system linearly as described by (d/dt)x=A(x)x+B(x)u+d(x). The main streamline of the study is the sliding surface design for the system. Since there is no systematic way of designing sliding surfaces for nonlinear systems, a moving sliding surface is designed such that its parameters are determined in an adaptive manner to cope with the nonlinearities of the system. This adaptive manner includes only the automatic adaptation of the sliding surface by determining its parameters by means of solving the State Dependent Riccati Equations (SDRE) online during the control process. The two methods developed in this study: SDRE combined sliding control and the pure SDRE with bias terms are applied to a longitudinal model of a generic hypersonic air vehicle to compare the results.

Precision control under the effect of friction requires an effective compensation of friction. Since friction has a complex and highly nonlinear behaviour, it is generally insufficient to represent the friction in a dynamic control system only with a linear viscous model, which is mostly valid in high-velocity motions. Especially when the control system moves near zero velocity regions or changes the direction of motion, an accurate modelling of friction including the lowvelocity dynamic behaviour is a prerequisite to obtain a more complete and realistic dynamic model of the system. Furthermore, the parameters of the friction model should be identified as accurate as possible in order to attain a satisfactory performance. Therefore, the parameters of the friction should be estimated regarding the working conditions. The estimated friction force can then be used to improve the controlled performance of the dynamic system under consideration. In this thesis, the modelling, identification and compensation of friction in a rotary mechanical system are studied. The effectiveness of the existing friction models in the literature are investigated / namely the classical Coulomb with viscous friction model, the Stribeck friction model, the LuGre friction model, and the Generalized Maxwell-Slip (GMS) friction model. All friction models are applied to the system together with the same linear, proportional with derivative (PD)-type and proportional with integral and derivative (PID)-type feedback control actions for the sake of being faithful in comparison. The accuracy of the friction compensation methods is examined separately for both the low-velocity and high-velocity motions of the system. The precision of friction estimation is also shown in the case of using both the desired velocity and measured velocity as an input to the friction models. These control studies are verified in simulation environment and the corresponding results are given. Furthermore, an experimental set-up is designed and manufactured as a case study. The parameters of the aforementioned friction models are identified and the control laws with different friction models are applied to the system in order to demonstrate the compensation capabilities of the models. The results of the experiments are evaluated by comparing them among each other and with the simulation results.

This work focuses on modeling, parameter estimation, and real-time position control of a two axis Gimbaled Mirror System (GMS) which is designed and manufactured to move an IR spot generated by an Infra Red Scene Generator System (IRSGS) in two orthogonal axes (elevation and azimuth) within the IR scene which is also generated by the IRSGS. Mathematical models of the GMS, the control system, and the disturbance torque originated from the movements of Flight Motion Simulator (FMS), on which the IRSGS will be mounted, are constructed using MATLAB&reg / /Simulink&reg / and MATLAB/Simulink/SimMechanics&reg / . Parameter estimations of the GMS and control system elements are achieved using MATLAB/Simulink Parameter Estimation Tool&reg / . The controller tuning is performed using the developed mathematical models in MATLAB/Simulink environment. Optimized digital PID controllers are implemented in the real-time control system. Performances of the controllers for both GMS axes are evaluated by both real system tests and simulation runs / and the results of these runs are compared. Controller performances under the effect of disturbances are analyzed by using the mathematical models developed in the MATLAB/ Simulink environment.

This thesis aims to propose multiple methods for performing a hardware-in-the-loop simulation, providing the hardware and software tools necessary for design and execution. For this purpose, methods of modeling commonly encountered dynamical system components are explored and techniques suitable for calculating the states of the modeled system are presented. Modules and subsystems that enable the realization of a hardware-in-the-loop simulation application and its interfacing with external controller hardware are explained. The thesis also presents three different simulation scenarios. Solutions suitable for these scenarios are provided along with their implementations. The details and specifications of the developed software packages and hardware platforms are given. The provided results illustrate the advantages and disadvantages of the approaches used in these solutions.

In this study, universal motion command generator systems utilizing a Field Programmable Gate Array (FPGA) and an interface board for Robotics and Computer Numerical Control (CNC) applications have been developed. These command generation systems can be classified into two main groups as polynomial approximation and data compression based methods. In the former type of command generation methods, the command trajectory is firstly divided into segments according to the inflection points. Then, the segments are approximated using various polynomial techniques. The sequence originating from modeling error can be further included to the generated series. In the second type, higher-order differences of a given trajectory (i.e. position) are computed and the resulting data are compressed via lossless data compression techniques. Besides conventional approaches, a novel compression algorithm is also introduced in the study. This group of methods is capable of generating trajectory data at variable rates in forward and reverse directions. The generation of the commands is carried out according to the feed-rate (i.e. the speed along the trajectory) set by the external logic dynamically. These command generation techniques are implemented in MATLAB and then the best ones from each group are realized using FPGAs and their performances are assessed according to the resources used in the FPGA chip, the speed of command generation, and the memory size in Static Random Access Memory (SRAM) chip located on the development board.

In recent years, there has been a significant increase in the interest for snake like modular robots due to their superior locomotion capabilities in terms of versatility, adaptability and scalability. Passive wheeled planar snake like robots are a major category and they are being actively researched. Due to the nonholonomic constraints imposed on them, certain configurations lead to the singularity which must be avoided at all costs. Furthermore, it is vital to generate a locomotion pattern such that they can track a wide range of trajectories. All of these objectives must be accomplished smoothly and in an energy efficient manner. Studies indicate that meeting all of these requirements is a challenging problem. In this study, a novel form of the serpenoid curve is proposed in order to make the robot track arbitrary paths. A controller has been designed using the feedback linearization method. Afterwards, a new performance measure, considering both the efficiency and sustainability of the locomotion, has been proposed to evaluate the locomotion. Optimal parameters for the proposed serpenoid curve and the linear controller have been determined for efficient locomotion by running series of simulations. Relations between the locomotion performance, locomotion speed and eigenvalues of the linear controller have been demonstrated. Simulation results show striking differences between the locomotion by using the proposed serpenoid curve with optimal parameters and the locomotion by purely tracking a given path. Obtained results also indicate that the aforementioned requirements are met successfully and confirm the validity and consistency of the proposed performance measure.

In this thesis, a sliding mode controller employing a new sliding surface for antilock brake system (ABS) is proposed, its stability is proven formally and its performance is compared with existing sliding mode controllers. The new sliding mode controller uses the integral-derivative surface, which includes error, its derivative and its integral, all at the same time. This and the already existing derivative surface, which includes error and its derivative only, are named zerothorder sliding surfaces. Their stability analysis is done using first-order auxiliary surfaces. Auxiliary surfaces equal the sliding surfaces when derivative of the error becomes zero. The first-order error surface, which includes only the error, and the integral surface, which includes error and its integral, were also designed for comparison. During design, tire brake force response is modelled as an uncertainty. Controllers are simulated on a road with an abrupt change in road coefficient of adhesion. Controller parameters used are optimized, which results in comparable stopping distances while braking on a constant coefficient of adhesion road. Effect of first order actuator dynamics with varying time constants and actuator absolute time delay were considered. Reaching and sliding properties of controllers were also investigated, using results on a constant coefficient of adhesion road. It is observed that zeroth-order sliding surfaces give smoother response for both derivative and integral-derivative cases. As the controllers employing error and derivative surfaces get unstable in the presence of actuator time delay, the integral-derivative surface, proposed in this study, stands as the best controller.