The robust loop-shaping control methodology is applied in the flight control system design of the Cranfield A3 Observer unmanned, unstable, catapult launched air vehicle. Detailed linear models for the full operational flight envelope of the air vehicle are developed. The nominal and worst-case models are determined using the v-gap metric. The effect of neglecting subsystems such as actuators and/or computation delays on modelling uncertainty is determined using the v-gap metric and shown to be significant. Detailed designs for the longitudinal, lateral, and the combined full dynamics TDF controllers were carried out. The Hanus command signal conditioning technique is also implemented to overcome actuator saturation and windup. The robust control system is then successfully evaluated in the high fidelity 6DOF non-linear simulation to assess its capability of launch stabilization in extreme cross-wind conditions, control effectiveness in climb, and navigation precision through the prescribed 3D flight path in level cruise. Robust performance and stability of the single-point non-scheduled control law is also demonstrated throughout the full operational flight envelope the air vehicle is capable of and for all flight phases and beyond, to severe launch conditions, such as 33knots crosswind and exaggerated CG shifts. The robust TDF control law is finally compared with the classical PMC law where the actual number of variables to be manipulated manually in the design process are shown to be much less, due to the scheduling process elimination, although the size of the final controller was much higher. The robust control law performance superiority is demonstrated in the non-linear simulation for the full flight envelope and in extreme flight conditions.

The robust loop-shaping control methodology is applied in the flight control system design of the Cranfield A3 Observer unmanned, unstable, catapult launched air vehicle. Detailed linear models for the full operational flight envelope of the air vehicle are developed. The nominal and worst-case models are determined using the v-gap metric. The effect of neglecting subsystems such as actuators and/or computation delays on modelling uncertainty is determined using the v-gap metric and shown to be significant. Detailed designs for the longitudinal, lateral, and the combined full dynamics TDF controllers were carried out. The Hanus command signal conditioning technique is also implemented to overcome actuator saturation and windup. The robust control system is then successfully evaluated in the high fidelity 6DOF non-linear simulation to assess its capability of launch stabilization in extreme cross-wind conditions, control effectiveness in climb, and navigation precision through the prescribed 3D flight path in level cruise. Robust performance and stability of the single-point non-scheduled control law is also demonstrated throughout the full operational flight envelope the air vehicle is capable of and for all flight phases and beyond, to severe launch conditions, such as 33knots crosswind and exaggerated CG shifts. The robust TDF control law is finally compared with the classical PMC law where the actual number of variables to be manipulated manually in the design process are shown to be much less, due to the scheduling process elimination, although the size of the final controller was much higher. The robust control law performance superiority is demonstrated in the non-linear simulation for the full flight envelope and in extreme flight conditions.

Unmanned ground vehicles (UGVs) will increasingly be used for tasks such as retrieving injured soldiers from a battlefield, transporting supplies, and towing other small vehicles and payloads. To date, the unmanned test community has not standardized on an apparatus or test operating procedure (TOP) specifically for evaluating the towing capacity of small unmanned ground vehicles. Draw-bar testing has been adapted by several groups to quantify small unmanned ground vehicle (SUGV) tow capacity; however, these devices are inherently limited to measuring peak static towing force. This paper describes an alternative method using a variable-resistance tow sled for quantifying the dynamic towing capacity of SUGVs. The tow sled contains a frontal skid plate and a rear axle and wheel arrangement. A weighted carriage is transferred from the rear of the sled to the front of the sled by a cable geared to the rear axle. As the sled is pulled along the ground, towing resistance increases in a controlled linear fashion. An encoder on the rear axle and a load cell in the tow chain provide motion and force data. Testing of the tow sled has been conducted on a TALON SUGV at the Southwest Research Institute (SwRI) Small Robot Test Facility and a MATILDA SUGV at the Joint Unmanned Systems Test, Experimentation, and Research (JOUSTER) site. / Master of Science

This thesis presents a prototype of Unmanned Cooperative Fire-Seeking and -Fighting Robots (UCSFRs) which have a new way to climb up the stairs or traverse over obstacles with a ball screw. There are three unmanned vehicles (one Mother Vehicle (MV) and two Daughter Vehicles (DVs)) presented in this research. The MV can carry two DVs to climb stairs. They can communicate with each other using Bluetooth communication modules. The core system of the UCSFRs is a PIC 16F877 microcontroller on a 2840 development board. The software is written in C language and the interface is established through Hyper Terminal built in Windows XP. UCSFRs are low cost unmanned vehicles compared with other commercial ones. The double-deck structure is applied on the DVs. The body of the MV can be extended for special purposes. In this research, there are three tests used to verify the functionality of the UCSFRs: (1) MV?s finding and stopping fire, (2) Communication between the MV and the DVs, and (3) the MV?s climbing stairs. In the second test, the DVs run in the opposite direction to assist MV detect fire. By cooperative work, they can save time finding the fire. The MV will go to the hightemperature area according to the data sent by the DVs. Because of the features mentioned above, UCSFRs can be used to perform dangerous tasks instead of fire-fighters.

The primary objective of this thesis is to leverage on the framework of H∞ loop-shaping control to formulate efficient and powerful optimization algorithms in LMI framework for the synthesis of performance loop-shaping weights. The H∞ loop-shaping design procedure is an efficient controller synthesis technique that combines classical loop-shaping concepts with H∞ synthesis. This procedure establishes a good tradeoff between robust stability and robust performance of a closed-loop system in a systematic manner. However, the selection of pre- and/or post-compensators, a crucial step in the design procedure, is nontrivial as factors such as the right half plane poles/zeros of the nominal plant, roll-off rate around the crossover frequency, strength of cross-coupling in multi-input multi-output systems, expected bandwidth, etc. must be adequately considered.Firstly, a frequency-dependent weight optimization framework is formulated in state-space form in order to remove the dependency on frequency while retaining the objective of maximizing the robust stability margin of a closed-loop system. This formulation facilitates the synthesis of low-order controllers, which is desirable from an implementation perspective.A weight optimization framework that incorporates smoothness constraints in order to prevent the cancellation of important modes of the system, for example, lightly damped poles/zeros of flexible structures, is subsequently formulated. The proposed formulation is intuitive from a design perspective as the smoothness constraints are expressed as gradient constraints on a log-log scale in dB/decade, consistent with the notation used in Bode plot for single-input single-output systems and singular value plots for multi-input multi-output systems.Thereafter, an optimization framework that maximizes the robust performance of a closed-loop system is presented. The philosophy in this framework is in line with practical design objectives that give the best achievable robust performance on a particular problem once a level of robust stability margin is demanded.Lastly, a novel unmanned vehicle is proposed. The vehicle uses a full six-degree-of-freedom tri-rotor actuation, capable of fully decoupled thrust and torque vectoring in all the 3D space. This vehicle can act as an unmanned ground vehicle or unmanned aerial vehicle, but the objective herein is restricted to the upright stability of the vehicle while operating on the ground as this is a precursor to rolling motion. The full nonlinear model of the vehicle is derived and linearized for subsequent controller synthesis, and this is thereafter validated by means of numerical simulations.

Unmanned vehicles (UVs) are seeing more widespread use in military, scientific, and civil sectors in recent years. These UVs range from unmanned air and ground vehicles to surface and underwater vehicles. Each of these different UVs has its own inherent strengths and weaknesses, from payload to freedom of movement. Research in this field is growing primarily because of the National Defense Act of 2001 mandating that one-third of all military vehicles be unmanned by 2015. Research using small UVs, in particular, is a growing because small UVs can go places that may be too dangerous for humans. Because of the limitations inherent in small UVs, including power consumption and payload, the selection of light weight and low power sensors and processors becomes critical. Low power CMOS cameras and real-time vision processing algorithms can provide fast and reliable information to the UVs. These vision algorithms often require computational power that limits their use in traditional general purpose processors using conventional software. The latest developments in field programmable gate arrays (FPGAs) provide an alternative for hardware and software co-design of complicated real-time vision algorithms. By tracking features from one frame to another, it becomes possible to perform many different high-level vision tasks, including object tracking and following. This thesis describes a vision guidance system for unmanned vehicles in general and the FPGA hardware implementation that operates vision tasks in real-time. This guidance system uses an object following algorithm to provide information that allows the UV to follow a target. The heart of the object following algorithm is real-time rank transform, which transforms the image into a more robust image that maintains the edges found in the original image. A minimum sum of absolute differences algorithm is used to determine the best correlation between frames, and the output of this correlation is used to update the tracking of the moving target. Control code can use this information to move the UV in pursuit of a moving target such as another vehicle.

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Radio frequency interference is an ever growing problem in the wireless community. This dissertation presents methods to reduce interference for vehicular multi-antenna devices. This document is organized into two parts: the main chapters and the appendices. The main chapters present research conducted primarily by the author. These deserve the reader's primary attention. The appendices showcase contributions made by the author serving in a supporting role to projects led by others and/or do not fit the vehicular theme. These should receive secondary attention. The main chapter contributions are summarized as follows. A device was created that provides over 105 dB of transmit to receive isolation in a full duplex printed circuit board radio. This technology can improve the effective range of vehicular radar systems and increase the bandwidth of full duplex communication schemes for vehicles. The technologies involved are compatible with existing circuit board topologies and are mindful of the size and weight requirements for vehicular use. This isolation performance pushes the state of the art for printed circuit board designs and provides greater capability for these kinds of devices. Recent system on chip computing architectures are opening new pathways for integrating phased array technologies into a single chip. The computer engineering required to configure these devices is beyond the capabilities of many vehicle systems engineers, inviting the author to use one to implement a 16 antenna adaptive beamformer for GPS. The adaptive beamformer can combat multipath bounces and malicious spoofing from ground sources. The high rate analog conversion architecture eliminates the local oscillator distribution to simplify the analog front end to an active antenna. This allows vehicular phased arrays to use smaller footprints and suggests that multi-antenna beamforming devices may be easier to deploy on small to midsized vehicles. Bench tests of the beamformer indicate it can adapt to the environment and increase the received signal strength suggesting it can improve GPS quality for active deployments. The bank of subspace projection beamformers is a popular choice for mitigating interference in digital phased array receivers. A method was discovered that maps that matrix operator into a circuit topology that is simple to implement in an analog circuit and cancels across the entire bandwidth simultaneously. This can offload computational interference mitigation from the signal processor while still allowing secondary multi-pixel digital beamforming downstream. This beamformer was analytically connected to the body of phased array literature and studied to estimate practical error bounds and design methods of calibration.

The aim of this thesis is to write a multisensor navigation algorithm and to design a test setup. After doing these, test the algorithm by using the test setup. In navigation, dead reckoning is a procedure to calculate the position from initial position with some measured inputs. These measurements do not include absolute position data. Using only an inertial measurement unit is an example for dead reckoning navigation. Calculating position and velocity with the inertial measurement unit is highly erroneous because, this calculation requires integration of acceleration data. Integration means accumulation of errors as time goes. For example, a constant acceleration error of 0.1 m/s^2 on 1 m/s^2 of acceleration will lead to 10% of position error in only 5 seconds. In addition to this, wrong calculation of attitude is going to blow the accumulated position errors. However, solving the navigation equations while knowing the initial position and the IMU readings is possible, the IMU is not used solely in practice. In literature, there are studies about this topic and in these studies / some other sensors aid the navigation calculations. The aiding or fusion of sensors is accomplished via Kalman filter. In this thesis, a navigation algorithm and a sensor fusion algorithm were written. The sensor fusion algorithm is based on estimation of IMU errors by use of a Kalman filter. The design of Kalman filter is possible after deriving the mathematical model of error propagation of mechanization equations. For the sensor fusion, an IMU, two incremental encoders and a digital compass were utilized. The digital compass outputs the orientation data directly (without integration). In order to find the position, encoder data is calculated in dead reckoning sense. The sensor triplet aids the IMU which calculates position data by integrations. In order to mount these four sensors, an unmanned tracked vehicle prototype was manufactured. For data acquisition, an xPC&ndash / Target system was set. After planning the test procedure, the tests were performed. In the tests, different paths for different sensor fusion algorithms were experimented. The results were recorded in a computer and a number of figures were plotted in order to analyze the results. The results illustrate the benefit of sensor fusion and how much feedback sensor fusion is better than feed forward sensor fusion.

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