In this thesis work construction of the angular acceleration signal of a 2-DOF gimbal platform and use of this signal for improving the stabilization performance is aimed. This topic can be divided into two subtopics, first being the construction of angular acceleration and the second being the use of this information in a way to improve system performance. Both problems should be tackled in order to get satisfactory results. The most important output of this work is defined as the demonstration of the improvements obtained both theoretically and on experimental setup. Although the system to be studied is a two axis gimbal platform, the results obtained can be applied to other servo control problems. It is possible to define different performance criteria for a servo control problem and different techniques will be addressed with different control objectives. For this thesis work, the performance criterion is defined as the stabilization performance of the platform. As a result, disturbance rejection characteristics of the controller emerges as the main topic and methods for rejecting these disturbances such as the friction torques and externally applied moments are focused on throughout the studies. As expected, remarkable improvement is achieved as a result of the use of acceleration feedback.

Elevation axis model of a barrel stabilization system is constructed. The nonlinearities which are considered in the model are orifice flow characteristics, coulomb friction, hard-stop limits, kinematics of the system and unbalance on the barrel. A Simulink&reg / model for the servo valve, actuation system and barrel is constructed. Servo valve identification is made via the actual test data. Compressibility of the hydraulic fluid is taken into consideration while modeling the actuation system. Friction model is simulated for different cases. Controller of the system is constructed by two PIDs, one for each of the velocity and the position loops. Velocity feed forward can reduce the time to make a quick move by the system. The disturbance is evaluated from a given road profile and disturbance feed forward is applied to the system.

This thesis attempts to tune any controller without the mathematical model knowledge of the system it is controlling. For that purpose, the optimization algorithm of MATLAB&reg / 6.5 / Nonlinear Control Design Blockset (NCD) is adapted for real-time executions and combined with a hardware-in-the-loop simulation provided by MATLAB&reg / 6.5 / Real-Time Windows Target (RTWT). A noise-included model of a DC motor position control system is obtained in MATLAB&reg / / SIMULINK first and simulated to test the modified algorithm in some aspects. Then the presented methodology is verified using the physical plant (DC motor position control system) where tuning algorithm is driven mainly by the real system data and the required performance parameters specified by a user defined constraint window are successfully satisfied. Resultant improvements on the step response behavior of DC motor position control system are shown for two case studies.

The aim of this thesis is to develop a stereo vision system to locate and classify objects moving on a conveyor belt. The vision system determines the locations of the objects with respect to a world coordinate system and class of the objects. In order to estimate the locations of the objects, two cameras placed at different locations are used. Image processing algorithms are employed to extract some features of the objects. These features are fed to stereo matching and classifier algorithms. The results of stereo matching algorithm are combined with the calibration parameters of the cameras to determine the object locations. Pattern classification techniques (Bayes and Nearest Neighbor classifiers) are used to classify the objects. The linear velocity of the objects is determined by using an encoder mounted to the shaft of the motor driving the conveyor belt. A robot can plan a sequence of motion to pick the object from the conveyor belt by using the output of the proposed system.

In this thesis, the walking of a humanoid system is simulated applying an optimal predictive control algorithm. The simulation is built using Matlab and Simulink softwares. Four separate physical models are developed to represent the single support and the double support phases of a full gait cycle. The models are three dimensional and their properties are analogous to the human&rsquo / s. In this connection, the foot models in the double support phases include an additional joint which connects the toe to the foot. The kinematic relationships concerning the physical models are formulated recursively and the dynamic models are obtained using the Newton &ndash / Euler formulation. The computed torque method is utilized at the level of joints. In the double support phase, the redundancy problem is solved by the optimization of the actuating torques. The command accelerations required to control the gait are obtained by applying an optimal predictive control law. The introduced humanoid walker achieves a sustainable gait by tuning the optimization and prediction parameters. The control algorithm manages the tracking of the predefined walking pattern with easily realizable joint accelerations. The simulation is capable of producing all the reaction forces, reaction moments and the values of the other variables. During these computations, a three dimensional view of the humanoid walker is animated simultaneously. As a result of this study, a suitable simulation structure is obtained to test and improve the mechanical systems which perform bipedal locomotion. The modular nature of the simulation structure developed in this study allows testing the performance of alternative control laws as well.

This work focuses on modeling and real-time control of a motion simulator for dynamic testing of a two-axis gyro-stabilized head mirror used in modern tanks. For this purpose, a six-degree-of freedom Stewart Platform which can simulate disturbances on the stabilized head mirror during operation of the tank is employed. Mathematical models of the Stewart Platform are constructed using MATLAB and ADAMS. Control system infrastructure is constructed and real-time control system elements are employed. Controller tuning is achieved by using the developed mathematical models in MATLAB. These parameters are applied in the real-time control system and fine tuning is achieved. Accuracy of the motion simulator is tested by mounting an Inertial Measurement Unit on the Stewart Platform. Further control system strategies are discussed by means of simulation.

In this thesis, an aeroservoelastic test appratus is designed to investigate the flutter phenomena in a low speed wind tunnel environment. Flutter is an aeroelastic instability that may occur at control surfaces of aircrafts and missiles. Aerodynamic, elastic, and inertial forces are involved in flutter. A mathematical model using aeroelastic equations of motion is derived to investigate flutter and is used as a basis to design the test setup. Simulations using this mathematical model are performed and critical flutter velocities and frequencies are found. Stiffness characteristics of the test setup are determined using the results of these simulations. The test setup is a two degrees of freedom system, with motions in pitch and plunge, and is controlled by a servomotor in the pitch degree of freedom. A NACA 0012 airfoil is used as a control surface in the test setup. Using this setup, the flutter phenomena is generated in Ankara Wind Tunnel (AWT) and experiments are conducted to validate the results of the theoretical aeroelastic mathematical model calculations.

Flutter is one of the most important phenomena in which aerodynamic surfaces become unstable in certain flight conditions. Since the 1930&amp / #8217 / s many studies were conducted in the areas of flutter prediction in design stage, research of design methods for flutter prevention, derivation and confirmation of flutter flight envelopes via tests, and in similar subjects for aircraft wings. With the use of controllers in 1960&amp / #8217 / s, studies on the active flutter suppression began. First the classical controllers were used. Then, with the improvement of the controller synthesis methods, optimal controllers and later robust controllers started to be used. However, there are not many studies in the literature about fully movable control surfaces, commonly referred to as fins. Fins are used as missile control surfaces, and they can also be used as a horizontal stabilizer or as a canard in aircraft. In the scope of this thesis, controllers satisfying the performance and flutter suppression requirements of a fin are synthesized and compared. For this purpose, H2, Hinf, and mu controllers are used. A new flutter suppression method is proposed and used. In order to assess the performance of this method, results obtained are compared with the results of another flutter suppression method given in the literature. or the purpose of implementation of the controllers developed, aeroelastic model equations are derived by using the typical section wing model with thin airfoil assumption. The controller synthesis method is tested for aeroelastic models that are veloped for various flow regimes / namely, steady incompressible subsonic, unsteady incompressible subsonic, nsteady compressible subsonic, and unsteady compressible supersonic.

In this thesis, control and guidance algorithms for unmanned sea surface vehicles are studied. To design control algorithms of different complexity, first a mathematical model for an unmanned sea surface vehicle is derived. The dynamical and kinematical equations for a sea surface vehicle are obtained, and they are adapted to real life conditions with necessary additions and simplifications. The forces and torques effecting on the vehicle are investigated in detail. Control algorithms for under-actuated six degrees-of-freedom model are designed. PID and LQR controllers are implemented to attain desired surge speed and yaw position. The autopilots are designed and their performances are compared. Based on the autopilots, a guidance algorithm is implemented to achieve desired motions of the vehicle. An obstacle avoidance algorithm is proposed for safe motion among the obstacles. A next-point generation algorithm is designed to direct the vehicle to the most appropriate next way-point if the one ahead is missed. The effects of disturbances on the motion of the vehicle are studied thoroughly on simulation results. PID controller for an unmanned sea surface vehicle is implemented on ArduPilot Mega v1.4 cart controlling a Traxxas Spartan model boat. The performance of the controller is validated. Simulations and experimental results are provided.

Most engineering systems are highly nonlinear in nature and thus one could not develop efficient mathematical models for these systems. Artificial neural networks, which are used in estimation, filtering, identification and control in technical literature, are considered as universal modeling and functional approximation tools. Unfortunately, developing a well trained monolithic type neural network (with many free parameters/weights) is known to be a daunting task since the process of loading a specific pattern (functional relationship) onto a generic neural network is proven to be a NP-complete problem. It implies that if training is conducted on a deterministic computer, the time required for training process grows exponentially with increasing size of the free parameter space (and the training data in correlation). As an alternative modeling technique for nonlinear dynamic systems / this thesis proposed a general methodology for structured neural network topologies and their corresponding applications are realized. The main idea behind this (rather classic) divide-and-conquer approach is to employ a priori information on the process to divide the problem into its fundamental components. Hence, a number of smaller neural networks could be designed to tackle with these elementary mapping problems. Then, all these networks are combined to yield a tailored structured neural network for the purpose of modeling the dynamic system under study accurately. Finally, implementations of the devised networks are taken into consideration and the efficiency of the proposed methodology is tested on four different types of mechanical systems.