This thesis documents the development of a novel nonlinear controller for servo pneumatic actuators that give good reference tracking at low speed motion, where friction has strong effect to the system behaviors. The design of the nonlinear controller presented in this thesis is based on the formalism of Lyapunov stability theory. The controller is constructed through a dynamical adaptive backstepping-sliding mode control algorithm. The conventional Lyapunov-based control algorithm is often limited by the order of the dynamical system; however, the backstepping design concept allows the control algorithm to be extended to higher order dynamical systems. In addition, the friction is estimated on-line via the Lyapunov-based adaptive laws embedded in the controller; meanwhile, the sliding mode control provides high robustness to the system parameter uncertainties. The simulation results clearly demonstrating the improved system performance (i.e., fast response and the reduced tracking error) are presented. Finally, the integration of the controller with a Lyapunov-based pressure observer reduces the state feedback of the servo pneumatic actuator model to only the piston displacement.

This thesis focuses on implementing a program, using Python and the symbolic package SymPy, to evaluate balancing of a humanoid robot modelled as inverted pendulums. The balancing algorithm used to evaluate the program is the feedback controller LQR. The program has successfully implemented a working LQR algorithm together with features such as underactuation and a tilting plane as disturbance. We have shown that the energy is conserved for the falling pendulums and that it is possible to predict the behavior for certain parameter values of the pendulums, thus confirming that the program is working correctly. Furthermore we have shown that a fully-actuated system is more controllable than an under-actuated system, and for each actuator that is removed, the system becomes less controllable. Finally we discuss the program performance where some concern is given toward the seemingly poor execution time of the program. The program has been tested for up to five pendulums with successful results. Most of the results however, are revolving around three pendulum systems.

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This thesis introduces locomotion synthesis methods for humanoid characters. Motion synthesis is an under-constrained problem that requires additional constraints beyond user inputs. Two main approaches to introducing additional constraints are physics-based and data-driven. Despite significant progress in the past 20 years, major difficulties still exist for both approaches. In general, building animation systems that are flexible to user requirements while keeping the synthesized motions plausible remain a challenging task. The methods introduced in this thesis, presented in two-parts, aim to allow animation systems to be more flexible to user demands without radically violating constraints that are important for maintaining plausibility. In the first part of the thesis, we address an important subproblem in physics-based animation --- controller synthesis for humanoid characters. We describe a method for optimizing the parameters of a physics-based controller for full-body, 3D walking. The objective function includes terms for power minimization, angular momentum minimization, and minimal head motion, among others. Together these terms produce a number of important features of natural walking, including active toe-off, near-passive knee swing, and leg extension during swing. We then extend the algorithm to optimize for robustness to uncertainty. Many unknown factors, such as external forces, control torques, and user control inputs, cannot be known in advance and must be treated as uncertain. Controller optimization entails optimizing the expected value of the objective function, which is computed by Monte Carlo methods. We demonstrate examples with a variety of sources of uncertainty and task constraints. The second part of this thesis deals with the data-driven approach and the problem of motion modeling. Defining suitable models for human motion data is non-trivial. Simple linear models are not expressive enough, while more complex models require setting many parameters and are difficult to learn with limited data. Using Bayesian methods, we demonstrate how the Gaussian process prior can be used to derive a kernelized version of multilinear models. The result is a locomotion model that takes advantage of training data addressed by multiple indices to improve generalization to unseen motions.

This thesis presents the design, construction and experiments done on a microcontroller board called 'SMARTY BOARD' targeted at small mobile robot applications. The primary motivation for this work was the lack of commercially available and cheap controller boards that would have all their components including interfaces on a single board. Having a single board simplifies the construction of programmable robots that can be used as platforms for teaching and learning robotics. Reducing the cost of the board as much as possible was one of the main design objectives. The target user groups for this device are the secondary and tertiary students, and hobbyists. Previous studies have shown that equipment cost is one of the major obstacles for teaching robotics in Australia. The other design objectives were robustness, reliability and functionality of the board. Most of the early technological learners such as high school students lack experience and expert knowledge for interfacing a controller board with other components. To prevent the learners from making errors, connectors on our board have been made foolproof (the user cannot damage the components of the board by plugging cables in the wrong sockets). Commercially available designs lack these essential features. After reviewing the commercially available micro-controller boards with respect to their suitability as teaching tools, we concluded that none of the existing microcontroller boards met our requirements. We then designed a new controller board based on previous boards. The main advantage of this new controller board is that it is a single board whereas the other controller boards are multi-board. Moreover, it is more foolproof. The new controller board was demonstrated at high-school seminars. In these demonstrations the new controller board was used for controlling two robots that we built. These robots are available as kits. The response from the high school teachers was very positive. The board has been selected as the platform for a robotic competition.

Master of Engineering (Research) / This thesis, by developing a Miniature Aerial Vehicle (MAV) hovering platform, presents a practical solution to allow researchers and students to implement their theoretical methods for guidance and navigation in the real world. The thesis is not concerned with the development of guidance and navigation algorithms, nor is it concerned with the development of external sensors. There have been some recent advances in guidance and navigation towards developing algorithms and simple sensors for MAVs. The task of developing a platform to test such advancements is the subject of this thesis. It is considered a difficult and time consuming process due to the complexities of autonomous flight control and the strict size, weight and computational requirements of this type of system. It would be highly beneficial to be able to buy a platform specifically designed for this task that already possesses autonomous hovering capability and the expansion connectivity for interfacing your own custom developed sensors and algorithms. Many biological and computer scientists would jump at the opportunity to maximize their research by real world implementation. The development of such a system is not a trivial task. It requires a great deal of understanding in a broad range of fields including; Aeronautical, Microelectronic, Mechanical, Computer and Embedded Software Engineering in order to create a successful prototype. The challenge of this thesis was to design a research platform to enable easy implementation of external sensors and guidance algorithms, in a real world environment for research and education. The system is designed so it could be used for a broad range of testing experiments. After extensive research in current MAV and avionics design it became obvious in several areas the best available products were not sufficient to meet the needs of the proposed platform. Therefore it was necessary to custom design and build; sensors, a data acquisition system and a servo controller. The latter two products are available for sale by Jimonics (www.jimonics.com). It was then necessary to develop a complete flight control system with integrated sensors, processor and wireless communications network which is called ‘The MicroBrain’. ‘The MicroBrain’ board measures only 45mm x 35mm x 11mm and weighs ~11 grams. The coaxial contra-rotating MAV platform design provides a high level of mechanical stability to help minimise the control system complexity. The platform was highly modified from a commercially available remotely controlled helicopter. The system incorporates a novel collision protection system that was designed to also double as a mounting place for external sensors around its perimeter. The platform equipped with ‘The MicroBrain’ is capable of fully autonomous hover. This provides a great base for testing guidance and navigational sensors and algorithms by decoupling the difficult task of platform design and low-level stability control. By developing a platform with these capabilities the researcher can now focus on the guidance and navigation task, as the difficulties in developing a custom platform have been taken care of. This therefore promotes a faster evolution of guidance and navigational control algorithms for MAVs.

Thesis (M.E.)--University of Canterbury, 2006. / Typescript (photocopy). Includes bibliographical references (p. 77-78). Also available via the World Wide Web.

Thesis (M.S.)--West Virginia University, 2007. / Title from document title page. Document formatted into pages; contains x, 89 p. : ill. (some col.). Includes abstract. Includes bibliographical references (p. 81-89).

abstract: During the past decade, different kinds of fancy functions are developed in portable electronic devices. This trend triggers the research of how to enhance battery lifetime to meet the requirement of fast growing demand of power in portable devices. DC-DC converter is the connection configuration between the battery and the functional circuitry. A good design of DC-DC converter will maximize the power efficiency and stabilize the power supply of following stages. As the representative of the DC-DC converter, Buck converter, which is a step down DC-DC converter that the output voltage level is smaller than the input voltage level, is the best-fit sample to start with. Digital control for DC-DC converters reduces noise sensitivity and enhances process, voltage and temperature (PVT) tolerance compared with analog control method. Also it will reduce the chip area and cost correspondingly. In battery-friendly perspective, current mode control has its advantage in over-current protection and parallel current sharing, which can form different structures to extend battery lifetime. In the thesis, the method to implement digitally average current mode control is introduced; including the FPGA based digital controller design flow. Based on the behavioral model of the close loop Buck converter with digital current control, the first FPGA based average current mode controller is burned into board and tested. With the analysis, the design metric of average current mode control is provided in the study. This will be the guideline of the parallel structure of future research. / Dissertation/Thesis / M.S. Electrical Engineering 2011

Este trabalho apresenta um método alternativo para sintonia de múltiplos controladores ressonantes aplicados aos sistemas ininterruptos de energia. A proposta do método é fornecer um conjunto de equações algébricas de simples aplicação que possibilite aos projetistas destes sistemas determinar os parâmetros dos controladores ressonantes com múltiplos modos. As equações apresentadas para determinação dos parâmetros do controlador foram obtidas diretamente com base nos parâmetros e nas características funcionais do inversor. Também nestas equações estão presentes constantes as quais garantem que todo o inversor cujo controlador for sintonizado pelo método atenda as especificações estabelecidas pela norma 60240-3. As constantes são determinadas através da formulação do problema por desigualdades matriciais lineares (LMI - Linear Matrix Inequalities) que levam em conta o equacionamento dinâmico do inversor e dos múltiplos controladores ressonantes. A solução do problema satisfaz simultaneamente a minimização do esforço de controle, onde foi empregada a formulação de custo garantido, juntamente com a localização dos polos de malha-fechada para toda a variação admissível de carga, formulada através do procedimento de D-Estabilidade. / This master thesis shows an alternative method for tuning multiple resonant controllers applied to uninterrupted power supply. The method is intended to provide a set of simple algebraic equations that enable designers of those systems to determine the parameters of the resonant controllers through multiple modes. The equations presented for determining the controller’s parameters were obtained directly based on the parameters and functional characteristics of the inverter. Additionally, constants that ensure that every inverter whose controller is attuned by the method meets the 60240-3 specifications norms can be found in these equations. The constants are determined based on the formulation of the problem through linear matrix inequalities (LMI) that take in consideration the dynamic of the inverter and of the multiple resonant controllers. The solution of the problem ensures both the needs for minimization of control efforts at guaranteed cost, along with the location of close-loop poles for every permissible load variation, formulated through the D-Stability procedure.