This research addressed the design and implementation of a polynomial-complexity deadlock avoidance controller for a flexible manufacturing cell modeled using Colored Petri Nets. The cell model is robust to changes in the part types to be manufactured in the system and is automatically generated using the interaction of the resources in the cell and the technological capabilities of the machines. The model also captures dynamic routing flexibility options. The framework introduced separates the cell model from the control logic allowing the system designer to implement and test various control algorithms using the same cell model. The controller adopts the neighborhood deadlock avoidance policy to resolve deadlocks and control the resource allocation decisions within the system. The evaluation of the performance of systems controlled by not maximally permissive algorithms is important in determining the applicability of the control algorithms. There are many polynomial time deadlock avoidance algorithms proposed for the control of general resource allocation systems. However, the permissiveness of these algorithms is not quantified and the applicability of these algorithms in terms of effective resource utilization remains unanswered. The performance of automated manufacturing cells controlled using the neighborhood deadlock avoidance policy is benchmarked by comparing its performance with other control policies.

Thesis (M.S.)--Ohio University, June, 2007. / Title from PDF t.p. Includes bibliographical references.

Multimedia applications such as video streaming and Voice over IP are becoming common today with the tremendous growth of the Internet. General purpose operating systems thus are required to support these applications. These multimedia applications have some timing constraints that need to be satisfied for good quality. For example, video streaming applications require that each video frame be decoded in time to be displayed every 33.3 milliseconds. In order to satisfy these timing requirements, general purpose operating systems need to have fine-grained scheduling. Current general purpose operating systems unfortunately are designed to maximize throughput to serve traditional data-oriented applications and have coarse-grained scheduling and timers. Time Sensitive Linux (TSL), designed by Goel, et al., solves this problem with fine-grained timers and schedulers. The scheduler for TSL is implemented at a very low level. The controller that implements the algorithm for resource allocation is implemented at a higher level. This controller can easily be modified to implement new control algorithms. Successful implementation of resource allocation to satisfy timing constraints of multimedia applications requires two problems to be addressed. First, the resources required by the application to satisfy the timing constraints should not exceed the total available resources in the system. Second, the controller must adapt to changing needs of the applications and allocate enough resources to satisfy the timing constraints of each application over time. The first problem has been addressed elsewhere using intelligent data dropping with TSL. We focus on the second problem in this thesis. We design a proportion-period controller in this thesis for allocating CPU to multimedia video applications with timing constraints. The challenges for the controller design include the coarse granularity of the time-stamp markings of the video frames, the unpredictable decoding completion times of the frames, the large variations in the decoding times of the frames, and the limit of the control actuation to positive values. We set up the problem in a state space. We design a predictive estimating controller to allocate the proportion of the CPU to a thread when its long term error is small. When the decoding process is running behind by more than a certain threshold, we switch to a different controller to drive the error back to a small value. This controller is the solution to a dynamic optimization LQR tracking problem. / Graduation date: 2003

As control systems are becoming more and more complex, system complexity is rapidly becoming a limiting factor in the efficacy of established techniques for control systems design. To cope with the growing complexity, control architectures often have a hierarchical structure. At the base of the system pyramid lie feedback loops with simple closed-loop control laws. These are followed, at a higher level, by discrete control logics. Such hierarchical systems typically have a hybrid nature. A common approach to addressing these types of complexity consists of decomposing, in the time domain, the control task into a number of modes, i.e. control laws dedicated to carrying out a limited task. This type of control generally involves switching laws among the various modes, and its design poses a major challenge in many application domains. The primary goal of this thesis is to develop a unified framework for addressing this challenge. To this end, the contribution of this thesis is threefold: 1. An algorithmic framework for how to optimize the performance of switched autonomous systems is derived. The optimization concerns both the sequence in which different modes appear in and the duration of each mode. The optimization algorithms are presented together with detailed convergence analyses. 2. Control strategies for how to optimize switched autonomous systems operating in real time, and when the initial state of the system is unknown, are presented. 3. A control strategy for how to optimally navigate an autonomous mobile robot in real-time is presented and evaluated on a mobile robotics platform. The control strategy uses optimal switching surfaces for when to switch between different modes of operations (behaviors).

This thesis provides a real-time algorithmic optimal control framework for autonomous switched systems. Traditional optimal control approaches for autonomous switched systems are open-loop in nature. Therefore, the switching times of the system can not be adjusted or adapted when the system parameters or the operational environments change. This thesis aims to close this loop, and apply adaptations to the optimal switching strategy based on new information that can only be captured on-line. One important contribution of this work is to provide the means to allow feedback (in a general sense) to the control laws (i.e. the switching times) of the switched system so that the control laws can be updated to maintain optimality of the switching-time control inputs. Furthermore, convergence analyses for the proposed algorithms are presented. The effectiveness of the real-time algorithms is demonstrated by an application in optimal formation and coverage control of a networked system. This application is implemented on a realistic simulation framework consisting of a number of Unmanned Aerial Vehicles (UAVs) that interact in a virtual 3D world.

Hyperthermia based cancer treatments delivered under various modalities have the potential to become an effective option to eradicate the disease, maintain functionality of infected organs, and minimize complications and relapse. Moreover, hyperthermia therapies are a form of minimally invasive cancer treatment which are key to improving the quality of life post-treatment. Many modalities are available for delivering the heat source. However, the ability to control the energy deposition to prevent damage to adjacent healthy tissue is a limiting factor in all forms of thermal therapies, including cryotherapy, microwave, radio-frequency, ultrasound, and laser. The application of a laser heat source under the guidance of real-time treatment data has the potential to provide unprecedented control over the temperature field induced within the biological domain. The computational infrastructure developed in this work combines a computational model of bioheat transfer based on a nonlinear version of the Pennes equation for heterogeneous media with the precise timing and orchestration of the real-time solutions to the problems of calibration, optimal control, data transfer, registration, finite element mesh refinement, cellular damage prediction, and laser control; it is an example of Dynamic-Data-Driven Applications System (DDDAS) in which simulation models interact with measurement devices and assimilates data over a computational grid for the purpose of producing high-fidelity predictions of physical events. The tool controls the thermal source, provides a prediction of the entire outcome of the treatment and, using intra-operative data, updates itself to increase the accuracy of the prediction. A precise mathematical framework for the real-time finite element solution of the problems of calibration, optimal heat source control, and goal-oriented error estimation applied to the equations of bioheat transfer is presented. It is demonstrated that current finite element technology, parallel computer architecture, data transfer infrastructure, and thermal imaging modalities are capable of inducing a precise computer controlled temperature field within a biological domain. The project thus addresses a set of problems falling in the intersection of applied mathematics, imaging physics, computational science, computer science and visualizations, biomedical engineering, and medical science. The work involves contributions in the three component areas of the CAM program; A, Applicable Mathematics; B, Numerical Analysis and Scientific Computing; and C, Mathematical modeling and Applications. The ultimate goal of this research is to provide the medical community a minimally invasive clinical tool that uses predictive computational techniques to provide the optimal hyperthermia laser treatment procedure given real-time, patient specific data. / text

Extremely large telescopes (ELTs) are the next generation of ground-based reflecting telescopes of optical wavelengths. ELTs possess an aperture of more than 20 meters and share a number of common features, particularly the use of a segmented primary mirror and the use of adaptive optics systems. In 2005, the European Southern Observatory introduced a new giant telescope concept, named the European Extremely Large Telescope (E-ELT), which is scheduled for operation in 2018. The E-ELT will address key scientific challenges and will aim for a number of notable firsts, including discovering Earth-like planets around other stars in the ``habitable zones'' where life could exist, attempting to uncover the relationship between black holes and galaxies, measuring the properties of the first stars and galaxies, and probing the nature of dark matter and dark energy. In 2009, a feasibility study, conducted by National Instruments, proved the feasibility of the real-time (RT) control system architecture for the E-ELT's nearly 1,000 mirror segments with 3,000 actuators and 6,000 sensors. The goal of the RT control system was to maintain a perfectly aligned field of mirrors at all times with a loop-time of 1 ms. The study assumed a prescribed controller algorithm. This research report prescribes the optimal controller algorithms for large segmented telescopes. In this respect, optimal controller designs for the primary mirror of the E-ELT, where optimality is formulated in the [H-2] and [H-infinity] frameworks are derived. Moreover, the designed controllers are simulated to show that the desired performance metrics are met. / text

Engineering educators the world over are being faced with the dilemma of combining traditional mathematically intensive courses, like Control Systems and Robotics with advances in computational hardware and software. This is because it is impractical to include both software engineering issues as well as conventional course content. A solution to the problem lies in Rapid Prototyping technology to develop and design software, for application on PC's and embedded systems. Rapid Prototyping, based on automatic code generation, allows users to develop advanced software on high level graphical platforms like Simulink® and LabView®, while " hiding" the underlying layers of complex code. This approach allows the advanced hardware, traditionally reserved for software engineers, to be accessed by a much wider audience and is an ideal educational tool. This thesis presents the complete development of the Rapid Application Development Environment (RADE). The RADE system customises the Mathworks Real Time Workshop (RTW) revision 11 for application on both standalone and networked DS? cards. The functionality of the RTW is incorporated into the RADE system. This affords the user seamless code generation, downloading, on-line parameter tuning and on-line data visualisation with storage capability. An added advantage of the RADE system is its easy portability to multiple target platforms, which is demonstrated by its implementation on two different DSP cards. Finally the functionality of the RADE system is demonstrated as an educational tool, with the demonstration of a DC motor speed and position controller. / Thesis (M.Sc.Eng.-University of Natal, Durban, 2001.

No description available.

The switched reluctance motor (SRM) is receiving attention because of its merits: high operating temperature capability, fault tolerance, inherent shoot-through preventing inverter topology, high power density, high speed operation, and small rotor inertia. Rotor position information plays a critical role in the control of the SRM. Conventionally, separate position sensors, are used to obtain this information. Position sensors add complexity and cost to the control system and reduce its reliability and flexibility. In order to overcome the drawbacks of position sensors, this dissertation proposed and investigated a position sensorless control system that meets the needs of an electric actuator application. It is capable of working from zero to high speeds. In the control system, two different control strategies are proposed, one for low speeds and one for high speeds. Each strategy utilizes a state observer to estimate rotor position and speed and is capable of 4 quadrant operation. In the low speed strategy a Luenberger observer, which has been named the inductance profile demodulator based observer, is used where a pulse voltage is applied to the SRMs idle phases generating triangle shaped phase currents. The amplitude of the phase current is modulated by the SRMs inductance. The current is demodulated and combined with the output of a state observer to produce an error input to the observer so that the observer will track the actual SRM rotor position. The strategy can determine the SRMs rotor position at standstill and low speeds with torques up to rated torque. Another observer, named the simplified flux model based observer, is used for medium and high speeds. In this case, the flux is computed using the measured current and a simplified flux model. The difference between the computed flux and the measured flux generates an error that is input to the observer so that it will track the actual SRM rotor position. Since the speed ranges of the two control stragegies overlap, the final control system is capable of working from zero to high speed by switching between the two observers according to the estimated speed. The stability and performance of the observers are verified with simulation and experiments.