In recent years, the requirement for embedded controllers has been steadily on the increase due to the development of computers, communication ,WWW and consumers¡¦ products. Consequently, integration and application of the embedded system and the World-Wide Web become more and more important. The Web-based embedded system developed in this paper tends build a service of micro web server. By this service, users can not only receive the information from the system via the browser, but also design particular processes for themselves. Besides, the system developer can use the most popular tools to edit the page for the Web-based embedded system. This Web service technology offers an operational interface, which is user-friendly, and cost effective with the capability of cross-platform and TCP/IP transmission. The presented achievement is applied to temperature control system for performance evaluation of remote control.

The state assignment is one of the most important problems in hardware implementation of controllers (finite state machines, FSMs). Traditional heuristics include simulated annealing (SA), greedy approach, and recursive Min-Cut partitioning. Since these methods can¡¦t reduce both area and power, thus we propose a new approach which using integer linear programming (ILP) to solve the state assignment. The proposed of ILP approach can set the weight and reach best solution between less area and low power. The approach can find out the best state assignment for both low-area and low power consumption. In addition, we also use ILP to solve the output encoding of controller in order to reduce the power consumption of datapath. Finally, to verify the effectiveness of our proposed approach, we do some experiments on several MCNC FSM benchmarks and controller-datapath systems. The experimental results show that a significant power and area savings can be achieved.

This thesis presents the design and implementation of a single-stage with high power factor asymmetrical half-bridge converter. The main structure combines a boost converter with an asymmetrical half-bridge. An Asymmetrical half-bridge converter has many advantages such as soft-switching properties and fewer components. Therefore it is suitable for DC/DC cell. The boost converter is used in a PFC cell that operating in discontinuous condition mode have innate ability of power factor correction without additional controller. In this thesis, the complete analysis of operation principle and design of controller for the equivalent circuits of a single-stage AC/DC converter in every operating stage have been described in detail. Finally, we construct the single-stage circuit and experimental result show that it can reach the expected goal for power-factor correction.

The thesis aims to the research of active power factor correction (PFC) circuit and develop a DSP-based digital controller. In the thesis, PI controller is the control core for the voltage loop¡Band current loop, and then achieve the function of the power factor correction of boost converter. Finally, we develop a boost converter and connect it to a DSP-based controller to measure the waveforms and verify the power factor correction. Furthermore, the research can be extended to a simulating platform which we can verify the power factor correction by just changing the control law on DSP .

ABSTRACT In this dissertation, several adaptive control design schemes for a class of nonlinear systems are proposed. The first topic of the research is concerned with self-tuning PID controller design. The main problem of designing PID controller is how to determine the values of three control gains, i.e., proportional gain , integral gain , and derivative gain . We attempt to use the technique of adaptive control based on the Lyapunov approach to design the PID controller for some class of partially known nonlinear systems. Three PID control gains are adjusted on-line such that better output performance can be achieved. The stability of the closed-loop PID control systems is analyzed and guaranteed by introducing a supervisory control and a modified adaptation law with projection. Second, two kinds of adaptive neural control systems including the direct and indirect neural controls are considered by using simple single auto-tuning neuron. We will first propose a novel neuron called auto-tuning neuron and use it to take place of the roles of the traditional neural networks used in the direct and indirect adaptive neural control systems. This can greatly reduce the computational time and network complexities due to the simple configuration of the auto-tuning neuron. It is also easy for hardware implementation. Third, based on the idea borrowed from natural evolution, genetic algorithm can search for optimal or near-optimal solutions for an optimization problem over the search domain. An optimization technique of real-coded genetic algorithm is used to design the PID controller by minimizing the performance index of integrated absolute error. The improvements of our results over that using other methods are also illustrated. In the last part of each section, some computer simulation results will also be provided to illustrate our proposed methods.

Abstract We use the non-binary coding ,elitist strategy, increasing mutation rate, extinction, and immigration strategy to improve the simple genetic algorithms in this study. We expect that the search technique can avoid falling into the local optimum due to the premature convergence, and purse the chance that finding the near-optimal parameters in the larger searching space could be obviously increased. The accelerometer is then taken as the feedback sensor for output measurement, and the designed actuator and the PID fuzzy logic controller (PIDFLC) is implemented to actively suppress the vibration of the supporting mechanism that is due to the excitation effect of the high-speed and precision positioning action of the linear motor. From the computer simulations and the experimental results, it is obvious that the near-optimal PIDFLC controller designed by modified genetic algorithms can improve the effect of the vibration suppression; the settling time is also decrease. For the vibration suppressions of high-speed precision positioning problems, the vibrating supporting mechanism can quickly be stabilized.

Based on the Lyapunov stability theorem, an adaptive output feedback controller is proposed in this thesis for a class of multi-input multi-output (MIMO) dynamic systems with time-varying delay and disturbances. With an adaptive mechanism embeded in the proposed control scheme, the controller will automatically adapt the unknown upper bound of perturbation, so that the information of upper bounded of perturbations is not required. Once the controlled system reaches the switching hyperplane, not only the dynamics of system can be stabilized, but also the state trajectories can be driven into a small bounded region whose size can be adjusted through the design parameter. Two numerical examples are given for demonstrating the feasibility of the proposed control scheme.

Abstract Magnetic suspension systems are highly nonlinear and essentially unstable systems. In this thesis, we facilitate the position control problem for the DC electromagnetic suspension system. We utilize a phase-lead controller operating in the inner loop to stabilize the system first, and try to design a PID fuzzy logic controller (PIDFLC) operating in the outer loop to overcome the nonlinearity of the system and to improve the system¡¦s performance. Since the work of setting fuzzy control parameters is a long-winded trial and error, we adopt non-binary modified GAs to help us setting and optimizing parameters. As experimental results show that the designed PIDFLC not only increases the system¡¦s operating range, but also positions accurately and rapidly; meanwhile, it has the ability to eliminate extra disturbance. In addition, comparing with other control theories, the control method which we utilize is easier to be implemented.

In this study, the non-binary coding, elitist strategy, increasing mutation rate, extinction, and immigration strategy are used to improve the simple genetic algorithms. The improved search technique can reduce the possibility of falling into the local optimum due to the premature convergence in a large searching space, and increase the chance of finding out the near-optimal parameters. The hydraulic forming machine used in this thesis, includes a power source of a hydraulic motor and a actuator of two hydraulic cylinders. Both the internal pressure and axial force are controlled to hydroform the tubes into the shapes we want. The PID fuzzy logic controller is implemented to control the proportional direction valve and pressure reducing valve of this dual-cylinder electro-hydraulic system so that the loading path can follow the optimal forming curve of axial-feeding and pressure prescribed. From the experimental results, it is clear that the near-optimal PIDFLC controller designed via modified genetic algorithms can make the loading path follow the prescribed curve, and effective for reducing system uncertainty caused by the varying loads and system unstability resulting from the nonlinear characteristics of the hydraulic system.

Traffic congestion has become a menace to civilized society. It degrades air quality, jeopardizes safety and causes delay. Traffic congestion can be alleviated by providing an effective traffic control signal system. Closed-loop traffic control systems are an example of such a system. Closed-loop traffic control systems can be operated primarily in either of two modes: Time of Day Mode (TOD) or Traffic Responsive Plan Selection Mode (TRPS). TRPS mode, if properly configured, can easily handle time independent variation in traffic volumes. It can also reduce the effect of timing plan aging. Despite these advantages, TRPS mode is not used as frequently as TOD mode. The reason being a lack of methodologies and formal guidelines for predicting the factors and thresholds associated with TRPS mode. In this research, a new methodology is developed for determining the thresholds and factors associated with the TRPS mode. This methodology, when tested on a closed-loop system in Odem, Texas, produced a classification accuracy of 94%. The classification accuracy can be increased to 98% with a proposed TRPS architecture.