Adaptive control systems

Designing a dependable network for a highly sustainable system gives a challenging network design problem. The network must be highly adaptive to the changes in the network environment. It should also sustain any damages occurring in the network and recover itself quickly and efficiently. This thesis ultimately maps a real network to simulated network by developing a concept of generic nodes and experimentally investigates different parameters that affects the reliability of the system. The work includes designing a simulation for generation of network traffic in a simulated network and studying the behavior of the network with different parameters. The experiment helped us in determining the optimum values of these parameters. For the selected set of experiments and further implies that simulation can determine the nodes different parameter in a control network and will result in a Dependable system.

Implementation of the Optimized Policies for Adaptive Control (OPAC) strategy in conjunction with a vehicle velocity controller offers the potential for significantly improving the control strategies used at isolated intersections with respect to measured vehicle delays. The exhaustive sequential search procedure by OPAC provides the optimal switching policies for the intersection while the vehicle velocity controller varies vehicle velocities to reduce vehicle stopping delays. The OPAC algorithm implemented with the vehicle velocity controller was found to have substantially lower delays than OPAC alone.

The tasks Autonomous Underwater Vehicles (AUVs) are expected to perform are becoming more and more challenging. Thus, to be able to address such tasks, we implemented a high maneuverability propulsion system: a vectored thruster. The design of a vehicle equipped with such a propulsion system will be presented, from a mechanical, electronic and software point of view. The motion control of the resulting system is fairly complex, and no suitable controller is available in the literature. Accordingly, we will present the derivation of a novel tracking controller, whose adaptive properties will compensate for the lack of knowledge of the system's parameters. Computer simulations are provided and show the performance and robustness of the proposed control algorithm to external perturbations, unmodelled dynamics and dynamics variation. We finally illustrate the advantage of using an adaptive controller by comparing the presented controller to a Proportional Integral Derivative controller.

This thesis describes the design and implementation of an adaptive control system for active noise control. The main approaches available for implementing an active noise controller are presented and discussed. A Least Mean Squares (LMS) based algorithm, the Filtered-X LMS (FXLMS) algorithm, is selected for implementation. The significance of factors, such as delays, system output noise, system complexity, type and size of adaptive filter, frequency bandwidth, etc..., which can limit the performance of the adaptive control, is investigated in simulations. For hardware implementation, a floating-point DSP is selected to implement the adaptive controller. The control program and its implementation on the DSP are discussed. The program is first tested with a hardware-in-the-loop set-up and then implemented on a physical system. Active Noise Control in a duct is finally successfully demonstrated. The hardware and the results are discussed.