Thesis (M.S.)--State University of New York at Binghamton, Thomas J. Watson School of Engineering and Applied Science, Dept. of Systems Science and Industrial Engineering, 2006. / Includes bibliographical references.

Thesis (M.S.)--Virginia Polytechnic Institute and State University, 1991. / Vita. Abstract. Includes bibliographical references (leaves 131-133). Also available via the Internet.

Thesis (doctoral)--University of Oulu, 2008. / Includes bibliographical references. Also available on the World Wide Web.

Conventional control systems express control solutions by means of expressions, usually mathematically based. In order to completely express the control solution, a vast amount of data is required. In contrast, knowledge-based solutions require far less plant data and mathematical expression. This reduces development time proportionally. In addition, because this type of processing does not require involved calculations, processing speed is increased, since rule process is separate and all processes can be performed simultaneously. These results in improved product quality, better plant efficiency, simplified process, etc. Within this project, conventional PID control has already been implemented, with the control parameter adjustment and loop tuning being problematic. This is mainly due to a number of external parameters that affects the stability of the process. In maintaining a consistent temperature, for example, the steam flow rate varies, the hot well temperature varies, the ambient may temperature vary. Another contributing factor, the time delay, also affects the optimization of the system, due to the fact that temperature measurement is based on principle of absorption. The normal practice in industry to avoid an unstable control condition is to have an experienced operator to switch the controller to manual, and make adjustments. After obtaining the desired PV, the controller is switched back to automatic. This research project focuses on eliminating this time loss, by implementing a knowledge-based controller, for intelligent decision-making. A FLC design tool, which allows full interaction, whilst designing the control algorithm, was used to optimize the control system. The design tool executed on a PC is connected to a PLC, which in turn is successfully integrated into the process plant.

A project report submitted to the Faculty of Engineering, University of Witwatersrand, Johannesburg, in partial fulfilment of the requirements for the degree of Master of Science in Engineering. Johannesburg 1997. / This project report describes the design of a fuzzy logic controller for automatic generation control (AGC) in Eskom in 1995 and the process of re-optimisation of the fuzzy logic controller in 1997. The main purpose of the AGC controller is to determine the shortfall or surplus generation of electricity for South Africa. The difficulties associated with optimising the original AGC controller, the design,implementation and optimisation of the fuzzy controller are described in detail. [Abbreviated Abstract. Open document to view full version] / AC2017

International Telemetering Conference Proceedings / October 22-25, 1984 / Riviera Hotel, Las Vegas, Nevada / The processing power afforded by embedded microcomputers in state-of-the-art control applications offers the design engineer greatly expanded opportunities for improved ergonomic design, even without the use of “soft” actuator and/or display devices (which are sometimes undesirable and/or unacceptable). Especially important is the exploitation of software to simplify the hardware design while simultaneously implementing decision/mode logic that would be prohibitively expensive if done in hardware alone. The designer is often confronted with an ocean of possibilisties, and must make intelligent decisions in order to satisfy increasingly demanding applications and sophisticated users. The design decisions and resulting features and behaviors of an automatic antenna control unit are discussed from the operators point of view (black box), but also with the intention to detail some of the logic necessary to implement these features. This is prefaced by a discussion of the characteristics of the primary operator interface, the front panel, and the factors that influenced its design. Areas for future improvement of the design are also mentioned.

published_or_final_version / Industrial and Manufacturing Systems Engineering / Doctoral / Doctor of Philosophy

published_or_final_version / Industrial and Manufacturing Systems Engineering / Doctoral / Doctor of Philosophy

This thesis addresses the problem of intelligent control of autonomous mobile robots, particularly under circumstances unforeseen by the designer. As the range of applications for autonomous robots widens and increasingly includes operation in unknown environments (exploration) and tasks which are not clearly specifiable a priori (maintenance work), this question is becoming more and more important. It is argued that in order to achieve such flexibility in unforeseen situations it is necessary to equip a mobile robot with the ability to autonomously acquire the necessary task achieving competences, through interaction with the world. Using mobile robots equipped with self-organising, behaviour-based controllers,experiments in the autonomous acquisition of motor competences and navigational skills were conducted to investigate the viability of this approach. A controller architecture is presented that allows extremely fast acquisition of motor competence such as obstacle avoidance, wall and corridor following and deadend escape: these skills are obtained in less than five learning steps,performed in under one minute of real time. This is considerably faster than previous approaches. Because the effective wiring between sensors and actuators is determined autonomously by the robot, sensors and actuators may initially be wired up arbitrarily,which reduces the risk of human error during the setting up phase of the robot. For the first time it was demonstrated that robots also become able to autonomously recover from unforeseen situations such as changes in the robot's morphology, the environment or the task. Rule-based approaches to error recovery obviously cannot offer recovery from unforeseen errors,as error situations covered by such approaches have to be identified beforehand. A robust and fast map building architecture is presented that enables mobile robots to autonomously construct internal representations of their environment, using self-organising feature maps. After a short training time the robots are able to use these self-organising feature maps successfully for location recognition. For the first time the staged acquisition of multiple competences in mobile robots is presented. First obtaining fundamental motor competences such as wall following and deadend escape (primary skills), the robots use these in a second stage to learn higher levels of competence such as the navigational task of location recognition (secondary skills). Besides laying the foundation of autonomous, staged acquisition of high level competences, this approach has the interesting property of securely grounding secondary skills in the robot's own experience, as these secondary skills are defined in terms of the primary ones.

Thesis (PhD) -- University of South Australia, 1999